diff --git a/CLAUDE.md b/CLAUDE.md
index 23a0e97eaee..3cb67908076 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -90,6 +90,7 @@ LiteLLM is a unified interface for 100+ LLM providers with two main components:
- Pydantic v2 for data validation
- Async/await patterns throughout
- Type hints required for all public APIs
+- **Avoid imports within methods** — place all imports at the top of the file (module-level). Inline imports inside functions/methods make dependencies harder to trace and hurt readability. The only exception is avoiding circular imports where absolutely necessary.
### Testing Strategy
- Unit tests in `tests/test_litellm/`
diff --git a/docs/my-website/blog/litellm_observatory/index.md b/docs/my-website/blog/litellm_observatory/index.md
new file mode 100644
index 00000000000..f9944be8c27
--- /dev/null
+++ b/docs/my-website/blog/litellm_observatory/index.md
@@ -0,0 +1,136 @@
+---
+slug: litellm-observatory
+title: "LiteLLM Observatory: Raising the Bar for Release Reliability"
+date: 2026-02-06T10:00:00
+authors:
+ - name: Alexsander Hamir
+ title: "Performance Engineer, LiteLLM"
+ url: https://www.linkedin.com/in/alexsander-baptista/
+ image_url: https://github.com/AlexsanderHamir.png
+ - name: Krrish Dholakia
+ title: "CEO, LiteLLM"
+ url: https://www.linkedin.com/in/krish-d/
+ image_url: https://pbs.twimg.com/profile_images/1298587542745358340/DZv3Oj-h_400x400.jpg
+ - name: Ishaan Jaff
+ title: "CTO, LiteLLM"
+ url: https://www.linkedin.com/in/reffajnaahsi/
+ image_url: https://pbs.twimg.com/profile_images/1613813310264340481/lz54oEiB_400x400.jpg
+description: "How we built a long-running, release-validation system to catch regressions before they reach users."
+tags: [testing, observability, reliability, releases]
+hide_table_of_contents: false
+---
+
+
+
+# LiteLLM Observatory: Raising the Bar for Release Reliability
+
+As LiteLLM adoption has grown, so have expectations around reliability, performance, and operational safety. Meeting those expectations requires more than correctness-focused tests, it requires validating how the system behaves over time, under real-world conditions.
+
+This post introduces **LiteLLM Observatory**, a long-running release-validation system we built to catch regressions before they reach users.
+
+---
+
+## Why We Built the Observatory
+
+LiteLLM operates at the intersection of external providers, long-lived network connections, and high-throughput workloads. While our unit and integration tests do an excellent job validating correctness, they are not designed to surface issues that only appear after extended operation.
+
+A subtle lifecycle edge case discovered in v1.81.3 reinforced the need for stronger release validation in this area.
+
+---
+
+## A Real-World Lifecycle Edge Case
+
+In v1.81.3, we shipped a fix for an HTTP client memory leak. The change passed unit and integration tests and behaved correctly in short-lived runs.
+
+The issue that surfaced was not caused by a single incorrect line of logic, but by how multiple components interacted over time:
+
+- A cached `httpx` client was configured with a 1-hour TTL
+- When the cache expired, the underlying HTTP connection was closed as expected
+- A higher-level client continued to hold a reference to that connection
+- Subsequent requests failed with:
+
+```
+Cannot send a request, as the client has been closed
+```
+
+Our focus moving forward is on being the first to detect issues, even when they aren’t covered by unit tests. LiteLLM Observatory is designed to surface latency regressions, OOMs, and failure modes that only appear under real traffic patterns in **our own production deployments** during release validation.
+
+
+---
+
+## Introducing LiteLLM Observatory
+
+To systematically address this class of issues, we built **LiteLLM Observatory**.
+
+The Observatory is a long-running testing orchestrator used during release validation to exercise LiteLLM under production-like conditions for extended periods of time.
+
+Its core goals are:
+
+- Validate behavior over hours, not minutes
+- Turn production learnings into permanent release safeguards
+
+---
+
+### How the Observatory Works
+
+[LiteLLM Observatory](https://github.com/BerriAI/litellm-observatory) is a testing service that runs long-running tests against our LiteLLM deployments. We trigger tests by sending API requests, and results are automatically sent to Slack when tests complete.
+
+#### How Tests Run
+
+1. **Start a Test**: We send a request to the Observatory API with:
+ - Which LiteLLM deployment to test (URL and API key)
+ - Which test to run (e.g., `TestOAIAzureRelease`)
+ - Test settings (which models to test, how long to run, failure thresholds)
+
+2. **Smart Queueing**:
+ - The system checks whether we are attempting to run the exact same test more than once
+ - If a duplicate test is already running or queued, we receive an error to avoid wasting resources
+ - Otherwise, the test is added to a queue and runs when capacity is available (up to 5 tests can run concurrently by default)
+
+3. **Instant Response**: The API responds immediately—we do not wait for the test to finish. Tests may run for hours, but the request itself completes in milliseconds.
+
+4. **Background Execution**:
+ - The test runs in the background, issuing requests against our LiteLLM deployment
+ - It tracks request success and failure rates over time
+ - When the test completes, results are automatically posted to our Slack channel
+
+#### Example: The OpenAI / Azure Reliability Test
+
+The `TestOAIAzureRelease` test is designed to catch a class of bugs that only surface after sustained runtime:
+
+- **Duration**: Runs continuously for 3 hours
+- **Behavior**: Cycles through specified models (such as `gpt-4` and `gpt-3.5-turbo`), issuing requests continuously
+- **Why 3 Hours**: This helps catch issues where HTTP clients degrade or fail after extended use (for example, a bug observed in LiteLLM v1.81.3)
+- **Pass / Fail Criteria**: The test passes if fewer than 1% of requests fail. If the failure rate exceeds 1%, the test fails and we are notified in Slack
+- **Key Detail**: The same HTTP client is reused for the entire run, allowing us to detect lifecycle-related bugs that only appear under prolonged reuse
+
+#### When We Use It
+
+- **Before Deployments**: Run tests before promoting a new LiteLLM version to production
+- **Routine Validation**: Schedule regular runs (daily or weekly) to catch regressions early
+- **Issue Investigation**: Run tests on demand when we suspect a deployment issue
+- **Long-Running Failure Detection**: Identify bugs that only appear under sustained load, beyond what short smoke tests can reveal
+
+
+### Complementing Unit Tests
+
+Unit tests remain a foundational part of our development process. They are fast and precise, but they don’t cover:
+
+- Real provider behavior
+- Long-lived network interactions
+- Resource lifecycle edge cases
+- Time-dependent regressions
+
+LiteLLM Observatory complements unit tests by validating the system as it actually runs in production-like environments.
+
+---
+
+### Looking Ahead
+
+Reliability is an ongoing investment.
+
+LiteLLM Observatory is one of several systems we’re building to continuously raise the bar on release quality and operational safety. As LiteLLM evolves, so will our validation tooling, informed by real-world usage and lessons learned.
+
+We’ll continue to share those improvements openly as we go.
+```
+
diff --git a/docs/my-website/docs/mcp_public_internet.md b/docs/my-website/docs/mcp_public_internet.md
new file mode 100644
index 00000000000..69dd7464657
--- /dev/null
+++ b/docs/my-website/docs/mcp_public_internet.md
@@ -0,0 +1,251 @@
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+# Exposing MCPs on the Public Internet
+
+Control which MCP servers are visible to external callers (e.g., ChatGPT, Claude Desktop) vs. internal-only callers. This is useful when you want a subset of your MCP servers available publicly while keeping sensitive servers restricted to your private network.
+
+## Overview
+
+| Property | Details |
+|-------|-------|
+| Description | IP-based access control for MCP servers — external callers only see servers marked as public |
+| Setting | `available_on_public_internet` on each MCP server |
+| Network Config | `mcp_internal_ip_ranges` in `general_settings` |
+| Supported Clients | ChatGPT, Claude Desktop, Cursor, OpenAI API, or any MCP client |
+
+## How It Works
+
+When a request arrives at LiteLLM's MCP endpoints, LiteLLM checks the caller's IP address to determine whether they are an **internal** or **external** caller:
+
+1. **Extract the client IP** from the incoming request (supports `X-Forwarded-For` when configured behind a reverse proxy).
+2. **Classify the IP** as internal or external by checking it against the configured private IP ranges (defaults to RFC 1918: `10.0.0.0/8`, `172.16.0.0/12`, `192.168.0.0/16`, `127.0.0.0/8`).
+3. **Filter the server list**:
+ - **Internal callers** see all MCP servers (public and private).
+ - **External callers** only see servers with `available_on_public_internet: true`.
+
+This filtering is applied at every MCP access point: the MCP registry, tool listing, tool calling, dynamic server routes, and OAuth discovery endpoints.
+
+```mermaid
+flowchart TD
+ A[Incoming MCP Request] --> B[Extract Client IP Address]
+ B --> C{Is IP in private ranges?}
+ C -->|Yes - Internal caller| D[Return ALL MCP servers]
+ C -->|No - External caller| E[Return ONLY servers with available_on_public_internet = true]
+```
+
+## Walkthrough
+
+This walkthrough covers two flows:
+1. **Adding a public MCP server** (DeepWiki) and connecting to it from ChatGPT
+2. **Making an existing server private** (Exa) and verifying ChatGPT no longer sees it
+
+### Flow 1: Add a Public MCP Server (DeepWiki)
+
+DeepWiki is a free MCP server — a good candidate to expose publicly so AI gateway users can access it from ChatGPT.
+
+#### Step 1: Create the MCP Server
+
+Navigate to the MCP Servers page and click **"+ Add New MCP Server"**.
+
+
+
+The create dialog opens. Enter **"DeepWiki"** as the server name.
+
+
+
+For the transport type dropdown, select **HTTP** since DeepWiki uses the Streamable HTTP transport.
+
+
+
+Now scroll down to the MCP Server URL field.
+
+
+
+Enter the DeepWiki MCP URL: `https://mcp.deepwiki.com/mcp`.
+
+
+
+With the name, transport, and URL filled in, the basic server configuration is complete.
+
+
+
+#### Step 2: Enable "Available on Public Internet"
+
+Before creating, scroll down and expand the **Permission Management / Access Control** section. This is where you control who can see this server.
+
+
+
+Toggle **"Available on Public Internet"** on. This is the key setting — it tells LiteLLM that external callers (like ChatGPT connecting from the public internet) should be able to discover and use this server.
+
+
+
+With the toggle enabled, click **"Create"** to save the server.
+
+
+
+#### Step 3: Connect from ChatGPT
+
+Now let's verify it works. Open ChatGPT and look for the MCP server icon to add a new connection. The endpoint to use is `/mcp`.
+
+
+
+In the dropdown, select **"Add an MCP server"** to configure a new connection.
+
+
+
+ChatGPT asks for a server label. Give it a recognizable name like "LiteLLM".
+
+
+
+Next, enter the Server URL. This should be your LiteLLM proxy's MCP endpoint — `/mcp`.
+
+
+
+Paste your LiteLLM URL and confirm it looks correct.
+
+
+
+ChatGPT also needs authentication. Enter your LiteLLM API key in the authentication field so it can connect to the proxy.
+
+
+
+Click **"Connect"** to establish the connection.
+
+
+
+ChatGPT connects and shows the available tools. Since both DeepWiki and Exa are currently marked as public, ChatGPT can see tools from both servers.
+
+
+
+---
+
+### Flow 2: Make an Existing Server Private (Exa)
+
+Now let's do the reverse — take an existing MCP server (Exa) that's currently public and restrict it to internal access only. After this change, ChatGPT should no longer see Exa's tools.
+
+#### Step 1: Edit the Server
+
+Go to the MCP Servers table and click on the Exa server to open its detail view.
+
+
+
+Switch to the **"Settings"** tab to access the edit form.
+
+
+
+The edit form loads with Exa's current configuration.
+
+
+
+#### Step 2: Toggle Off "Available on Public Internet"
+
+Scroll down and expand the **Permission Management / Access Control** section to find the public internet toggle.
+
+
+
+Toggle **"Available on Public Internet"** off. This will hide Exa from any caller outside your private network.
+
+
+
+Click **"Save Changes"** to apply. The change takes effect immediately — no proxy restart needed.
+
+
+
+#### Step 3: Verify in ChatGPT
+
+Go back to ChatGPT to confirm Exa is no longer visible. You'll need to reconnect for ChatGPT to re-fetch the tool list.
+
+
+
+Open the MCP server settings and select to add or reconnect a server.
+
+
+
+Enter the same LiteLLM MCP URL as before.
+
+
+
+Set the server label.
+
+
+
+Enter your API key for authentication.
+
+
+
+Click **"Connect"** to re-establish the connection.
+
+
+
+This time, only DeepWiki's tools appear — Exa is gone. LiteLLM detected that ChatGPT is calling from a public IP and filtered out Exa since it's no longer marked as public. Internal users on your private network would still see both servers.
+
+
+
+## Configuration Reference
+
+### Per-Server Setting
+
+
+
+
+Toggle **"Available on Public Internet"** in the Permission Management section when creating or editing an MCP server.
+
+
+
+
+```yaml title="config.yaml" showLineNumbers
+mcp_servers:
+ deepwiki:
+ url: https://mcp.deepwiki.com/mcp
+ available_on_public_internet: true # visible to external callers
+
+ exa:
+ url: https://exa.ai/mcp
+ auth_type: api_key
+ auth_value: os.environ/EXA_API_KEY
+ available_on_public_internet: false # internal only (default)
+```
+
+
+
+
+```bash title="Create a public MCP server" showLineNumbers
+curl -X POST /v1/mcp/server \
+ -H "Authorization: Bearer sk-..." \
+ -H "Content-Type: application/json" \
+ -d '{
+ "server_name": "DeepWiki",
+ "url": "https://mcp.deepwiki.com/mcp",
+ "transport": "http",
+ "available_on_public_internet": true
+ }'
+```
+
+```bash title="Update an existing server" showLineNumbers
+curl -X PUT /v1/mcp/server \
+ -H "Authorization: Bearer sk-..." \
+ -H "Content-Type: application/json" \
+ -d '{
+ "server_id": "",
+ "available_on_public_internet": false
+ }'
+```
+
+
+
+
+### Custom Private IP Ranges
+
+By default, LiteLLM treats RFC 1918 private ranges as internal. You can customize this in the **Network Settings** tab under MCP Servers, or via config:
+
+```yaml title="config.yaml" showLineNumbers
+general_settings:
+ mcp_internal_ip_ranges:
+ - "10.0.0.0/8"
+ - "172.16.0.0/12"
+ - "192.168.0.0/16"
+ - "100.64.0.0/10" # Add your VPN/Tailscale range
+```
+
+When empty, the standard private ranges are used (`10.0.0.0/8`, `172.16.0.0/12`, `192.168.0.0/16`, `127.0.0.0/8`).
diff --git a/docs/my-website/docs/proxy/guardrails/custom_code_guardrail.md b/docs/my-website/docs/proxy/guardrails/custom_code_guardrail.md
index cb246144497..8cbc247ae5e 100644
--- a/docs/my-website/docs/proxy/guardrails/custom_code_guardrail.md
+++ b/docs/my-website/docs/proxy/guardrails/custom_code_guardrail.md
@@ -61,15 +61,23 @@ curl -X POST http://localhost:4000/chat/completions \
### Function Signature
-Your code must define an `apply_guardrail` function:
+Your code must define an `apply_guardrail` function. It can be either sync or async:
```python
+# Sync version
def apply_guardrail(inputs, request_data, input_type):
# inputs: see table below
# request_data: {"model": "...", "user_id": "...", "team_id": "...", "metadata": {...}}
# input_type: "request" or "response"
return allow() # or block() or modify()
+
+# Async version (recommended when using HTTP primitives)
+async def apply_guardrail(inputs, request_data, input_type):
+ response = await http_post("https://api.example.com/check", body={"text": inputs["texts"][0]})
+ if response["success"] and response["body"].get("flagged"):
+ return block("Content flagged")
+ return allow()
```
### `inputs` Parameter
@@ -145,6 +153,29 @@ def apply_guardrail(inputs, request_data, input_type):
| `char_count(text)` | Count characters |
| `lower(text)` / `upper(text)` / `trim(text)` | String transforms |
+### HTTP Requests (Async)
+
+Make async HTTP requests to external APIs for additional validation or content moderation.
+
+| Function | Description |
+|----------|-------------|
+| `await http_request(url, method, headers, body, timeout)` | General async HTTP request |
+| `await http_get(url, headers, timeout)` | Async GET request |
+| `await http_post(url, body, headers, timeout)` | Async POST request |
+
+**Response format:**
+```python
+{
+ "status_code": 200, # HTTP status code
+ "body": {...}, # Response body (parsed JSON or string)
+ "headers": {...}, # Response headers
+ "success": True, # True if status code is 2xx
+ "error": None # Error message if request failed
+}
+```
+
+**Note:** When using HTTP primitives, define your function as `async def apply_guardrail(...)` for non-blocking execution.
+
## Examples
### Block PII (SSN)
@@ -213,6 +244,29 @@ def apply_guardrail(inputs, request_data, input_type):
return allow()
```
+### Call External Moderation API (Async)
+
+```python
+async def apply_guardrail(inputs, request_data, input_type):
+ # Call an external moderation API
+ for text in inputs["texts"]:
+ response = await http_post(
+ "https://api.example.com/moderate",
+ body={"text": text, "user_id": request_data["user_id"]},
+ headers={"Authorization": "Bearer YOUR_API_KEY"},
+ timeout=10
+ )
+
+ if not response["success"]:
+ # API call failed - decide whether to allow or block
+ return allow()
+
+ if response["body"].get("flagged"):
+ return block(response["body"].get("reason", "Content flagged"))
+
+ return allow()
+```
+
### Combine Multiple Checks
```python
@@ -241,8 +295,8 @@ Custom code runs in a restricted environment:
- ❌ No `import` statements
- ❌ No file I/O
-- ❌ No network access
- ❌ No `exec()` or `eval()`
+- ✅ HTTP requests via built-in `http_request`, `http_get`, `http_post` primitives
- ✅ Only LiteLLM-provided primitives available
## Per-Request Usage
diff --git a/docs/my-website/sidebars.js b/docs/my-website/sidebars.js
index 688ad714370..545d46f7f37 100644
--- a/docs/my-website/sidebars.js
+++ b/docs/my-website/sidebars.js
@@ -543,6 +543,7 @@ const sidebars = {
items: [
"mcp",
"mcp_usage",
+ "mcp_public_internet",
"mcp_semantic_filter",
"mcp_control",
"mcp_cost",
diff --git a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma
index e713e6ca87a..c2d2299fb25 100644
--- a/litellm-proxy-extras/litellm_proxy_extras/schema.prisma
+++ b/litellm-proxy-extras/litellm_proxy_extras/schema.prisma
@@ -263,6 +263,7 @@ model LiteLLM_MCPServerTable {
token_url String?
registration_url String?
allow_all_keys Boolean @default(false)
+ available_on_public_internet Boolean @default(false)
}
// Generate Tokens for Proxy
diff --git a/litellm/a2a_protocol/exception_mapping_utils.py b/litellm/a2a_protocol/exception_mapping_utils.py
index 8463080b358..49dbb22b158 100644
--- a/litellm/a2a_protocol/exception_mapping_utils.py
+++ b/litellm/a2a_protocol/exception_mapping_utils.py
@@ -30,7 +30,7 @@
A2A_SDK_AVAILABLE = True
except ImportError:
- _A2AClient = None # type: ignore[misc]
+ _A2AClient = None # type: ignore[assignment, misc]
class A2AExceptionCheckers:
diff --git a/litellm/caching/redis_cache.py b/litellm/caching/redis_cache.py
index ea7e3f5a979..03d09ecc041 100644
--- a/litellm/caching/redis_cache.py
+++ b/litellm/caching/redis_cache.py
@@ -1123,7 +1123,7 @@ async def test_connection(self) -> dict:
redis_client = redis_async.Redis(**self.redis_kwargs)
# Test the connection
- ping_result = await redis_client.ping()
+ ping_result = await redis_client.ping() # type: ignore[misc]
# Close the connection
await redis_client.aclose() # type: ignore[attr-defined]
diff --git a/litellm/caching/redis_cluster_cache.py b/litellm/caching/redis_cluster_cache.py
index 91fcf1d7288..664578c8700 100644
--- a/litellm/caching/redis_cluster_cache.py
+++ b/litellm/caching/redis_cluster_cache.py
@@ -83,7 +83,7 @@ async def test_connection(self) -> dict:
)
# Test the connection
- ping_result = await redis_client.ping() # type: ignore[attr-defined]
+ ping_result = await redis_client.ping() # type: ignore[attr-defined, misc]
# Close the connection
await redis_client.aclose() # type: ignore[attr-defined]
diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py
index 1652ec2aa0c..bbd55a59bce 100644
--- a/litellm/integrations/custom_guardrail.py
+++ b/litellm/integrations/custom_guardrail.py
@@ -268,6 +268,7 @@ def get_guardrail_from_metadata(
"""
Returns the guardrail(s) to be run from the metadata or root
"""
+
if "guardrails" in data:
return data["guardrails"]
metadata = data.get("litellm_metadata") or data.get("metadata", {})
diff --git a/litellm/litellm_core_utils/token_counter.py b/litellm/litellm_core_utils/token_counter.py
index a99bd1cd0f3..6b9e51034c0 100644
--- a/litellm/litellm_core_utils/token_counter.py
+++ b/litellm/litellm_core_utils/token_counter.py
@@ -706,7 +706,7 @@ def _count_content_list(
if isinstance(c, str):
num_tokens += count_function(c)
elif c["type"] == "text":
- num_tokens += count_function(c.get("text", ""))
+ num_tokens += count_function(str(c.get("text", "")))
elif c["type"] == "image_url":
image_url = c.get("image_url")
num_tokens += _count_image_tokens(
@@ -722,7 +722,7 @@ def _count_content_list(
elif c["type"] == "thinking":
# Claude extended thinking content block
# Count the thinking text and skip signature (opaque signature blob)
- thinking_text = c.get("thinking", "")
+ thinking_text = str(c.get("thinking", ""))
if thinking_text:
num_tokens += count_function(thinking_text)
else:
diff --git a/litellm/llms/a2a/chat/guardrail_translation/README.md b/litellm/llms/a2a/chat/guardrail_translation/README.md
new file mode 100644
index 00000000000..1e18f5cda3a
--- /dev/null
+++ b/litellm/llms/a2a/chat/guardrail_translation/README.md
@@ -0,0 +1,155 @@
+# A2A Protocol Guardrail Translation Handler
+
+Handler for processing A2A (Agent-to-Agent) Protocol messages with guardrails.
+
+## Overview
+
+This handler processes A2A JSON-RPC 2.0 input/output by:
+1. Extracting text from message parts (`kind: "text"`)
+2. Applying guardrails to text content
+3. Mapping guardrailed text back to original structure
+
+## A2A Protocol Format
+
+### Input Format (JSON-RPC 2.0)
+
+```json
+{
+ "jsonrpc": "2.0",
+ "id": "request-id",
+ "method": "message/send",
+ "params": {
+ "message": {
+ "kind": "message",
+ "messageId": "...",
+ "role": "user",
+ "parts": [
+ {"kind": "text", "text": "Hello, my SSN is 123-45-6789"}
+ ]
+ },
+ "metadata": {
+ "guardrails": ["block-ssn"]
+ }
+ }
+}
+```
+
+### Output Formats
+
+The handler supports multiple A2A response formats:
+
+**Direct message:**
+```json
+{
+ "result": {
+ "kind": "message",
+ "parts": [{"kind": "text", "text": "Response text"}]
+ }
+}
+```
+
+**Nested message:**
+```json
+{
+ "result": {
+ "message": {
+ "parts": [{"kind": "text", "text": "Response text"}]
+ }
+ }
+}
+```
+
+**Task with artifacts:**
+```json
+{
+ "result": {
+ "kind": "task",
+ "artifacts": [
+ {"parts": [{"kind": "text", "text": "Artifact text"}]}
+ ]
+ }
+}
+```
+
+**Task with status message:**
+```json
+{
+ "result": {
+ "kind": "task",
+ "status": {
+ "message": {
+ "parts": [{"kind": "text", "text": "Status message"}]
+ }
+ }
+ }
+}
+```
+
+**Streaming artifact-update:**
+```json
+{
+ "result": {
+ "kind": "artifact-update",
+ "artifact": {
+ "parts": [{"kind": "text", "text": "Streaming text"}]
+ }
+ }
+}
+```
+
+## Usage
+
+The handler is automatically discovered and applied when guardrails are used with A2A endpoints.
+
+### Via LiteLLM Proxy
+
+```bash
+curl -X POST 'http://localhost:4000/a2a/my-agent' \
+-H 'Content-Type: application/json' \
+-H 'Authorization: Bearer your-api-key' \
+-d '{
+ "jsonrpc": "2.0",
+ "id": "1",
+ "method": "message/send",
+ "params": {
+ "message": {
+ "kind": "message",
+ "messageId": "msg-1",
+ "role": "user",
+ "parts": [{"kind": "text", "text": "Hello, my SSN is 123-45-6789"}]
+ },
+ "metadata": {
+ "guardrails": ["block-ssn"]
+ }
+ }
+}'
+```
+
+### Specifying Guardrails
+
+Guardrails can be specified in the A2A request via the `metadata.guardrails` field:
+
+```json
+{
+ "params": {
+ "message": {...},
+ "metadata": {
+ "guardrails": ["block-ssn", "pii-filter"]
+ }
+ }
+}
+```
+
+## Extension
+
+Override these methods to customize behavior:
+
+- `_extract_texts_from_result()`: Custom text extraction from A2A responses
+- `_extract_texts_from_parts()`: Custom text extraction from message parts
+- `_apply_text_to_path()`: Custom application of guardrailed text
+
+## Call Types
+
+This handler is registered for:
+- `CallTypes.send_message`: Synchronous A2A message sending
+- `CallTypes.asend_message`: Asynchronous A2A message sending
diff --git a/litellm/llms/a2a/chat/guardrail_translation/__init__.py b/litellm/llms/a2a/chat/guardrail_translation/__init__.py
new file mode 100644
index 00000000000..13c20677485
--- /dev/null
+++ b/litellm/llms/a2a/chat/guardrail_translation/__init__.py
@@ -0,0 +1,11 @@
+"""A2A Protocol handler for Unified Guardrails."""
+
+from litellm.llms.a2a.chat.guardrail_translation.handler import A2AGuardrailHandler
+from litellm.types.utils import CallTypes
+
+guardrail_translation_mappings = {
+ CallTypes.send_message: A2AGuardrailHandler,
+ CallTypes.asend_message: A2AGuardrailHandler,
+}
+
+__all__ = ["guardrail_translation_mappings"]
diff --git a/litellm/llms/a2a/chat/guardrail_translation/handler.py b/litellm/llms/a2a/chat/guardrail_translation/handler.py
new file mode 100644
index 00000000000..770453f2def
--- /dev/null
+++ b/litellm/llms/a2a/chat/guardrail_translation/handler.py
@@ -0,0 +1,315 @@
+"""
+A2A Protocol Handler for Unified Guardrails
+
+This module provides guardrail translation support for A2A (Agent-to-Agent) Protocol.
+It handles both JSON-RPC 2.0 input requests and output responses, extracting text
+from message parts and applying guardrails.
+
+A2A Protocol Format:
+- Input: JSON-RPC 2.0 with params.message.parts containing text parts
+- Output: JSON-RPC 2.0 with result containing message/artifact parts
+"""
+
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
+
+from litellm._logging import verbose_proxy_logger
+from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
+from litellm.types.utils import GenericGuardrailAPIInputs
+
+if TYPE_CHECKING:
+ from litellm.integrations.custom_guardrail import CustomGuardrail
+ from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
+ from litellm.proxy._types import UserAPIKeyAuth
+
+
+class A2AGuardrailHandler(BaseTranslation):
+ """
+ Handler for processing A2A Protocol messages with guardrails.
+
+ This class provides methods to:
+ 1. Process input messages (pre-call hook) - extracts text from A2A message parts
+ 2. Process output responses (post-call hook) - extracts text from A2A response parts
+
+ A2A Message Format:
+ - Input: params.message.parts[].text (where kind == "text")
+ - Output: result.message.parts[].text or result.artifacts[].parts[].text
+ """
+
+ async def process_input_messages(
+ self,
+ data: dict,
+ guardrail_to_apply: "CustomGuardrail",
+ litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
+ ) -> Any:
+ """
+ Process A2A input messages by applying guardrails to text content.
+
+ Extracts text from A2A message parts and applies guardrails.
+
+ Args:
+ data: The A2A JSON-RPC 2.0 request data
+ guardrail_to_apply: The guardrail instance to apply
+ litellm_logging_obj: Optional logging object
+
+ Returns:
+ Modified data with guardrails applied to text content
+ """
+ # A2A request format: { "params": { "message": { "parts": [...] } } }
+ params = data.get("params", {})
+ message = params.get("message", {})
+ parts = message.get("parts", [])
+
+ if not parts:
+ verbose_proxy_logger.debug("A2A: No parts in message, skipping guardrail")
+ return data
+
+ texts_to_check: List[str] = []
+ text_part_indices: List[int] = [] # Track which parts contain text
+
+ # Step 1: Extract text from all text parts
+ for part_idx, part in enumerate(parts):
+ if part.get("kind") == "text":
+ text = part.get("text", "")
+ if text:
+ texts_to_check.append(text)
+ text_part_indices.append(part_idx)
+
+ # Step 2: Apply guardrail to all texts in batch
+ if texts_to_check:
+ inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
+
+ # Pass the structured A2A message to guardrails
+ inputs["structured_messages"] = [message]
+
+ # Include agent model info if available
+ model = data.get("model")
+ if model:
+ inputs["model"] = model
+
+ guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
+ inputs=inputs,
+ request_data=data,
+ input_type="request",
+ logging_obj=litellm_logging_obj,
+ )
+
+ guardrailed_texts = guardrailed_inputs.get("texts", [])
+
+ # Step 3: Apply guardrailed text back to original parts
+ if guardrailed_texts and len(guardrailed_texts) == len(text_part_indices):
+ for task_idx, part_idx in enumerate(text_part_indices):
+ parts[part_idx]["text"] = guardrailed_texts[task_idx]
+
+ verbose_proxy_logger.debug("A2A: Processed input message: %s", message)
+
+ return data
+
+ async def process_output_response(
+ self,
+ response: Any,
+ guardrail_to_apply: "CustomGuardrail",
+ litellm_logging_obj: Optional["LiteLLMLoggingObj"] = None,
+ user_api_key_dict: Optional["UserAPIKeyAuth"] = None,
+ ) -> Any:
+ """
+ Process A2A output response by applying guardrails to text content.
+
+ Handles multiple A2A response formats:
+ - Direct message: {"result": {"kind": "message", "parts": [...]}}
+ - Nested message: {"result": {"message": {"parts": [...]}}}
+ - Task with artifacts: {"result": {"kind": "task", "artifacts": [{"parts": [...]}]}}
+ - Task with status message: {"result": {"kind": "task", "status": {"message": {"parts": [...]}}}}
+
+ Args:
+ response: A2A JSON-RPC 2.0 response dict or object
+ guardrail_to_apply: The guardrail instance to apply
+ litellm_logging_obj: Optional logging object
+ user_api_key_dict: User API key metadata
+
+ Returns:
+ Modified response with guardrails applied to text content
+ """
+ # Handle both dict and Pydantic model responses
+ if hasattr(response, "model_dump"):
+ response_dict = response.model_dump()
+ is_pydantic = True
+ elif isinstance(response, dict):
+ response_dict = response
+ is_pydantic = False
+ else:
+ verbose_proxy_logger.warning(
+ "A2A: Unknown response type %s, skipping guardrail", type(response)
+ )
+ return response
+
+ result = response_dict.get("result", {})
+ if not result or not isinstance(result, dict):
+ verbose_proxy_logger.debug("A2A: No result in response, skipping guardrail")
+ return response
+
+ # Find all text-containing parts in the response
+ texts_to_check: List[str] = []
+ # Each mapping is (path_to_parts_list, part_index)
+ # path_to_parts_list is a tuple of keys to navigate to the parts list
+ task_mappings: List[Tuple[Tuple[str, ...], int]] = []
+
+ # Extract texts from all possible locations
+ self._extract_texts_from_result(
+ result=result,
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ if not texts_to_check:
+ verbose_proxy_logger.debug("A2A: No text content in response")
+ return response
+
+ # Step 2: Apply guardrail to all texts in batch
+ # Create a request_data dict with response info and user API key metadata
+ request_data: dict = {"response": response_dict}
+
+ # Add user API key metadata with prefixed keys
+ user_metadata = self.transform_user_api_key_dict_to_metadata(user_api_key_dict)
+ if user_metadata:
+ request_data["litellm_metadata"] = user_metadata
+
+ inputs = GenericGuardrailAPIInputs(texts=texts_to_check)
+
+ guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
+ inputs=inputs,
+ request_data=request_data,
+ input_type="response",
+ logging_obj=litellm_logging_obj,
+ )
+
+ guardrailed_texts = guardrailed_inputs.get("texts", [])
+
+ # Step 3: Apply guardrailed text back to original response
+ if guardrailed_texts and len(guardrailed_texts) == len(task_mappings):
+ for task_idx, (path, part_idx) in enumerate(task_mappings):
+ self._apply_text_to_path(
+ result=result,
+ path=path,
+ part_idx=part_idx,
+ text=guardrailed_texts[task_idx],
+ )
+
+ verbose_proxy_logger.debug("A2A: Processed output response")
+
+ # Update the original response
+ if is_pydantic:
+ # For Pydantic models, we need to update the underlying dict
+ # and the model will reflect the changes
+ response_dict["result"] = result
+ return response
+ else:
+ response["result"] = result
+ return response
+
+ def _extract_texts_from_result(
+ self,
+ result: Dict[str, Any],
+ texts_to_check: List[str],
+ task_mappings: List[Tuple[Tuple[str, ...], int]],
+ ) -> None:
+ """
+ Extract text from all possible locations in an A2A result.
+
+ Handles multiple response formats:
+ 1. Direct message with parts: {"parts": [...]}
+ 2. Nested message: {"message": {"parts": [...]}}
+ 3. Task with artifacts: {"artifacts": [{"parts": [...]}]}
+ 4. Task with status message: {"status": {"message": {"parts": [...]}}}
+ 5. Streaming artifact-update: {"artifact": {"parts": [...]}}
+ """
+ # Case 1: Direct parts in result (direct message)
+ if "parts" in result:
+ self._extract_texts_from_parts(
+ parts=result["parts"],
+ path=("parts",),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ # Case 2: Nested message
+ message = result.get("message")
+ if message and isinstance(message, dict) and "parts" in message:
+ self._extract_texts_from_parts(
+ parts=message["parts"],
+ path=("message", "parts"),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ # Case 3: Streaming artifact-update (singular artifact)
+ artifact = result.get("artifact")
+ if artifact and isinstance(artifact, dict) and "parts" in artifact:
+ self._extract_texts_from_parts(
+ parts=artifact["parts"],
+ path=("artifact", "parts"),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ # Case 4: Task with status message
+ status = result.get("status", {})
+ if isinstance(status, dict):
+ status_message = status.get("message")
+ if (
+ status_message
+ and isinstance(status_message, dict)
+ and "parts" in status_message
+ ):
+ self._extract_texts_from_parts(
+ parts=status_message["parts"],
+ path=("status", "message", "parts"),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ # Case 5: Task with artifacts (plural, array)
+ artifacts = result.get("artifacts", [])
+ if artifacts and isinstance(artifacts, list):
+ for artifact_idx, art in enumerate(artifacts):
+ if isinstance(art, dict) and "parts" in art:
+ self._extract_texts_from_parts(
+ parts=art["parts"],
+ path=("artifacts", str(artifact_idx), "parts"),
+ texts_to_check=texts_to_check,
+ task_mappings=task_mappings,
+ )
+
+ def _extract_texts_from_parts(
+ self,
+ parts: List[Dict[str, Any]],
+ path: Tuple[str, ...],
+ texts_to_check: List[str],
+ task_mappings: List[Tuple[Tuple[str, ...], int]],
+ ) -> None:
+ """Extract text from message parts."""
+ for part_idx, part in enumerate(parts):
+ if part.get("kind") == "text":
+ text = part.get("text", "")
+ if text:
+ texts_to_check.append(text)
+ task_mappings.append((path, part_idx))
+
+ def _apply_text_to_path(
+ self,
+ result: Dict[Union[str, int], Any],
+ path: Tuple[str, ...],
+ part_idx: int,
+ text: str,
+ ) -> None:
+ """Apply guardrailed text back to the specified path in the result."""
+ # Navigate to the parts list
+ current = result
+ for key in path:
+ if key.isdigit():
+ # Array index
+ current = current[int(key)]
+ else:
+ current = current[key]
+
+ # Update the text in the part
+ current[part_idx]["text"] = text
diff --git a/litellm/llms/custom_httpx/llm_http_handler.py b/litellm/llms/custom_httpx/llm_http_handler.py
index d2ea7e872a2..64fc62b4722 100644
--- a/litellm/llms/custom_httpx/llm_http_handler.py
+++ b/litellm/llms/custom_httpx/llm_http_handler.py
@@ -4408,6 +4408,37 @@ async def _call_agentic_completion_hooks(
stream=stream,
kwargs=kwargs_with_provider,
)
+
+ # Check if we need to convert agentic loop response to fake stream
+ # This happens when the original request was streaming but was converted
+ # to non-streaming for WebSearch interception, and the agentic loop ran
+ websearch_converted_stream = (
+ logging_obj.model_call_details.get("websearch_interception_converted_stream", False)
+ if logging_obj is not None
+ else False
+ )
+
+ if websearch_converted_stream and agentic_response is not None:
+ from typing import cast
+
+ from litellm.llms.anthropic.experimental_pass_through.messages.fake_stream_iterator import (
+ FakeAnthropicMessagesStreamIterator,
+ )
+ from litellm.types.llms.anthropic_messages.anthropic_response import (
+ AnthropicMessagesResponse,
+ )
+
+ verbose_logger.debug(
+ "WebSearchInterception: Agentic loop completed, converting response to fake stream"
+ )
+
+ # Convert the non-streaming response to a fake stream
+ if isinstance(agentic_response, dict):
+ fake_stream = FakeAnthropicMessagesStreamIterator(
+ response=cast(AnthropicMessagesResponse, agentic_response)
+ )
+ return fake_stream
+
# First hook that runs agentic loop wins
return agentic_response
diff --git a/litellm/llms/deprecated_providers/palm.py b/litellm/llms/deprecated_providers/palm.py
index 3039222c0e2..657a6fdb229 100644
--- a/litellm/llms/deprecated_providers/palm.py
+++ b/litellm/llms/deprecated_providers/palm.py
@@ -139,7 +139,7 @@ def completion(
)
## COMPLETION CALL
try:
- response = palm.generate_text(prompt=prompt, **inference_params)
+ response = palm.generate_text(prompt=prompt, **inference_params) # type: ignore[attr-defined]
except Exception as e:
raise PalmError(
message=str(e),
diff --git a/litellm/model_prices_and_context_window_backup.json b/litellm/model_prices_and_context_window_backup.json
index 0da47634a94..4704549e716 100644
--- a/litellm/model_prices_and_context_window_backup.json
+++ b/litellm/model_prices_and_context_window_backup.json
@@ -1263,6 +1263,36 @@
"supports_vision": true,
"tool_use_system_prompt_tokens": 346
},
+ "au.anthropic.claude-opus-4-6-v1:0": {
+ "cache_creation_input_token_cost": 6.875e-06,
+ "cache_creation_input_token_cost_above_200k_tokens": 1.375e-05,
+ "cache_read_input_token_cost": 5.5e-07,
+ "cache_read_input_token_cost_above_200k_tokens": 1.1e-06,
+ "input_cost_per_token": 5.5e-06,
+ "input_cost_per_token_above_200k_tokens": 1.1e-05,
+ "litellm_provider": "bedrock_converse",
+ "max_input_tokens": 200000,
+ "max_output_tokens": 128000,
+ "max_tokens": 128000,
+ "mode": "chat",
+ "output_cost_per_token": 2.75e-05,
+ "output_cost_per_token_above_200k_tokens": 4.125e-05,
+ "search_context_cost_per_query": {
+ "search_context_size_high": 0.01,
+ "search_context_size_low": 0.01,
+ "search_context_size_medium": 0.01
+ },
+ "supports_assistant_prefill": false,
+ "supports_computer_use": true,
+ "supports_function_calling": true,
+ "supports_pdf_input": true,
+ "supports_prompt_caching": true,
+ "supports_reasoning": true,
+ "supports_response_schema": true,
+ "supports_tool_choice": true,
+ "supports_vision": true,
+ "tool_use_system_prompt_tokens": 346
+ },
"anthropic.claude-sonnet-4-20250514-v1:0": {
"cache_creation_input_token_cost": 3.75e-06,
"cache_read_input_token_cost": 3e-07,
diff --git a/litellm/proxy/_experimental/mcp_server/auth/litellm_auth_handler.py b/litellm/proxy/_experimental/mcp_server/auth/litellm_auth_handler.py
index 081d83dd1c8..75b75d3ba44 100644
--- a/litellm/proxy/_experimental/mcp_server/auth/litellm_auth_handler.py
+++ b/litellm/proxy/_experimental/mcp_server/auth/litellm_auth_handler.py
@@ -27,6 +27,7 @@ def __init__(
oauth2_headers: Optional[Dict[str, str]] = None,
mcp_protocol_version: Optional[str] = None,
raw_headers: Optional[Dict[str, str]] = None,
+ client_ip: Optional[str] = None,
):
self.user_api_key_auth = user_api_key_auth
self.mcp_auth_header = mcp_auth_header
@@ -35,3 +36,4 @@ def __init__(
self.mcp_protocol_version = mcp_protocol_version
self.oauth2_headers = oauth2_headers
self.raw_headers = raw_headers
+ self.client_ip = client_ip
diff --git a/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py b/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py
index 56feff548ad..8b052dd0da1 100644
--- a/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/discoverable_endpoints.py
@@ -9,13 +9,14 @@
get_async_httpx_client,
httpxSpecialProvider,
)
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
from litellm.proxy.common_utils.encrypt_decrypt_utils import (
decrypt_value_helper,
encrypt_value_helper,
)
from litellm.proxy.common_utils.http_parsing_utils import _read_request_body
-from litellm.types.mcp_server.mcp_server_manager import MCPServer
from litellm.proxy.utils import get_server_root_path
+from litellm.types.mcp_server.mcp_server_manager import MCPServer
router = APIRouter(
tags=["mcp"],
@@ -300,7 +301,10 @@ async def authorize(
)
lookup_name = mcp_server_name or client_id
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(lookup_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ lookup_name, client_ip=client_ip
+ )
if mcp_server is None:
raise HTTPException(status_code=404, detail="MCP server not found")
return await authorize_with_server(
@@ -342,7 +346,10 @@ async def token_endpoint(
)
lookup_name = mcp_server_name or client_id
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(lookup_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ lookup_name, client_ip=client_ip
+ )
if mcp_server is None:
raise HTTPException(status_code=404, detail="MCP server not found")
return await exchange_token_with_server(
@@ -425,7 +432,10 @@ def _build_oauth_protected_resource_response(
request_base_url = get_request_base_url(request)
mcp_server: Optional[MCPServer] = None
if mcp_server_name:
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(mcp_server_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ mcp_server_name, client_ip=client_ip
+ )
# Build resource URL based on the pattern
if mcp_server_name:
@@ -538,7 +548,10 @@ def _build_oauth_authorization_server_response(
mcp_server: Optional[MCPServer] = None
if mcp_server_name:
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(mcp_server_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ mcp_server_name, client_ip=client_ip
+ )
return {
"issuer": request_base_url, # point to your proxy
@@ -629,7 +642,10 @@ async def register_client(request: Request, mcp_server_name: Optional[str] = Non
if not mcp_server_name:
return dummy_return
- mcp_server = global_mcp_server_manager.get_mcp_server_by_name(mcp_server_name)
+ client_ip = IPAddressUtils.get_mcp_client_ip(request)
+ mcp_server = global_mcp_server_manager.get_mcp_server_by_name(
+ mcp_server_name, client_ip=client_ip
+ )
if mcp_server is None:
return dummy_return
return await register_client_with_server(
diff --git a/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py b/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py
index 4d53ae7059d..14bbb82808d 100644
--- a/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py
+++ b/litellm/proxy/_experimental/mcp_server/guardrail_translation/handler.py
@@ -1,26 +1,37 @@
"""
MCP Guardrail Handler for Unified Guardrails.
-This handler works with the synthetic "messages" payload generated by
-`ProxyLogging._convert_mcp_to_llm_format`, which always produces a single user
-message whose `content` string encodes the MCP tool name and arguments. The
-handler simply feeds that text through the configured guardrail and writes the
-result back onto the message.
+Converts an MCP call_tool (name + arguments) into a single OpenAI-compatible
+tool_call and passes it to apply_guardrail. Works with the synthetic payload
+from ProxyLogging._convert_mcp_to_llm_format.
+
+Note: For MCP tool definitions (schema) -> OpenAI tools=[], see
+litellm.experimental_mcp_client.tools.transform_mcp_tool_to_openai_tool
+when you have a full MCP Tool from list_tools. Here we only have the call
+payload (name + arguments) so we just build the tool_call.
"""
from typing import TYPE_CHECKING, Any, Dict, Optional
+from mcp.types import Tool as MCPTool
+
from litellm._logging import verbose_proxy_logger
+from litellm.experimental_mcp_client.tools import transform_mcp_tool_to_openai_tool
from litellm.llms.base_llm.guardrail_translation.base_translation import BaseTranslation
+from litellm.types.llms.openai import (
+ ChatCompletionToolParam,
+ ChatCompletionToolParamFunctionChunk,
+)
from litellm.types.utils import GenericGuardrailAPIInputs
if TYPE_CHECKING:
- from litellm.integrations.custom_guardrail import CustomGuardrail
from mcp.types import CallToolResult
+ from litellm.integrations.custom_guardrail import CustomGuardrail
+
class MCPGuardrailTranslationHandler(BaseTranslation):
- """Guardrail translation handler for MCP tool calls."""
+ """Guardrail translation handler for MCP tool calls (passes a single tool_call to guardrail)."""
async def process_input_messages(
self,
@@ -28,56 +39,51 @@ async def process_input_messages(
guardrail_to_apply: "CustomGuardrail",
litellm_logging_obj: Optional[Any] = None,
) -> Dict[str, Any]:
- messages = data.get("messages")
- if not isinstance(messages, list) or not messages:
- verbose_proxy_logger.debug("MCP Guardrail: No messages to process")
- return data
-
- first_message = messages[0]
- content: Optional[str] = None
- if isinstance(first_message, dict):
- content = first_message.get("content")
- else:
- content = getattr(first_message, "content", None)
+ mcp_tool_name = data.get("mcp_tool_name") or data.get("name")
+ mcp_arguments = data.get("mcp_arguments") or data.get("arguments")
+ mcp_tool_description = data.get("mcp_tool_description") or data.get(
+ "description"
+ )
+ if mcp_arguments is None or not isinstance(mcp_arguments, dict):
+ mcp_arguments = {}
- if not isinstance(content, str):
- verbose_proxy_logger.debug(
- "MCP Guardrail: Message content missing or not a string",
- )
+ if not mcp_tool_name:
+ verbose_proxy_logger.debug("MCP Guardrail: mcp_tool_name missing")
return data
- inputs = GenericGuardrailAPIInputs(texts=[content])
- # Include model information if available
- model = data.get("model")
- if model:
- inputs["model"] = model
- guardrailed_inputs = await guardrail_to_apply.apply_guardrail(
+ # Convert MCP input via transform_mcp_tool_to_openai_tool, then map to litellm
+ # ChatCompletionToolParam (openai SDK type has incompatible strict/cache_control).
+ mcp_tool = MCPTool(
+ name=mcp_tool_name,
+ description=mcp_tool_description or "",
+ inputSchema={}, # Call payload has no schema; guardrail gets args from request_data
+ )
+ openai_tool = transform_mcp_tool_to_openai_tool(mcp_tool)
+ fn = openai_tool["function"]
+ tool_def: ChatCompletionToolParam = {
+ "type": "function",
+ "function": ChatCompletionToolParamFunctionChunk(
+ name=fn["name"],
+ description=fn.get("description") or "",
+ parameters=fn.get("parameters")
+ or {
+ "type": "object",
+ "properties": {},
+ "additionalProperties": False,
+ },
+ strict=fn.get("strict", False) or False, # Default to False if None
+ ),
+ }
+ inputs: GenericGuardrailAPIInputs = GenericGuardrailAPIInputs(
+ tools=[tool_def],
+ )
+
+ await guardrail_to_apply.apply_guardrail(
inputs=inputs,
request_data=data,
input_type="request",
logging_obj=litellm_logging_obj,
)
- guardrailed_texts = (
- guardrailed_inputs.get("texts", []) if guardrailed_inputs else []
- )
-
- if guardrailed_texts:
- new_content = guardrailed_texts[0]
- if isinstance(first_message, dict):
- first_message["content"] = new_content
- else:
- setattr(first_message, "content", new_content)
-
- verbose_proxy_logger.debug(
- "MCP Guardrail: Updated content for tool %s",
- data.get("mcp_tool_name"),
- )
- else:
- verbose_proxy_logger.debug(
- "MCP Guardrail: Guardrail returned no text updates for tool %s",
- data.get("mcp_tool_name"),
- )
-
return data
async def process_output_response(
@@ -87,7 +93,6 @@ async def process_output_response(
litellm_logging_obj: Optional[Any] = None,
user_api_key_dict: Optional[Any] = None,
) -> Any:
- # Not implemented: MCP guardrail translation never calls this path today.
verbose_proxy_logger.debug(
"MCP Guardrail: Output processing not implemented for MCP tools",
)
diff --git a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
index 4c17a2ff3e0..e7174f943b2 100644
--- a/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
+++ b/litellm/proxy/_experimental/mcp_server/mcp_server_manager.py
@@ -53,6 +53,7 @@
MCPTransportType,
UserAPIKeyAuth,
)
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
from litellm.proxy.common_utils.encrypt_decrypt_utils import decrypt_value_helper
from litellm.proxy.utils import ProxyLogging
from litellm.types.llms.custom_http import httpxSpecialProvider
@@ -65,20 +66,23 @@
from litellm.types.utils import CallTypes
try:
- from mcp.shared.tool_name_validation import ( # type: ignore
+ from mcp.shared.tool_name_validation import (
+ validate_tool_name, # pyright: ignore[reportAssignmentType]
+ )
+ from mcp.shared.tool_name_validation import (
SEP_986_URL,
- validate_tool_name,
)
except ImportError:
from pydantic import BaseModel
+
SEP_986_URL = "https://github.com/modelcontextprotocol/protocol/blob/main/proposals/0001-tool-name-validation.md"
- class ToolNameValidationResult(BaseModel):
+ class _ToolNameValidationResult(BaseModel):
is_valid: bool = True
warnings: list = []
- def validate_tool_name(name: str) -> ToolNameValidationResult: # type: ignore[misc]
- return ToolNameValidationResult()
+ def validate_tool_name(name: str) -> _ToolNameValidationResult: # type: ignore[misc]
+ return _ToolNameValidationResult()
# Probe includes characters on both sides of the separator to mimic real prefixed tool names.
@@ -324,6 +328,9 @@ async def load_servers_from_config(
access_groups=server_config.get("access_groups", None),
static_headers=server_config.get("static_headers", None),
allow_all_keys=bool(server_config.get("allow_all_keys", False)),
+ available_on_public_internet=bool(
+ server_config.get("available_on_public_internet", False)
+ ),
)
self.config_mcp_servers[server_id] = new_server
@@ -469,12 +476,12 @@ def _register_openapi_tools(self, spec_path: str, server: MCPServer, base_url: s
)
# Update tool name to server name mapping (for both prefixed and base names)
- self.tool_name_to_mcp_server_name_mapping[
- base_tool_name
- ] = server_prefix
- self.tool_name_to_mcp_server_name_mapping[
- prefixed_tool_name
- ] = server_prefix
+ self.tool_name_to_mcp_server_name_mapping[base_tool_name] = (
+ server_prefix
+ )
+ self.tool_name_to_mcp_server_name_mapping[prefixed_tool_name] = (
+ server_prefix
+ )
registered_count += 1
verbose_logger.debug(
@@ -622,6 +629,9 @@ async def build_mcp_server_from_table(
allowed_tools=getattr(mcp_server, "allowed_tools", None),
disallowed_tools=getattr(mcp_server, "disallowed_tools", None),
allow_all_keys=mcp_server.allow_all_keys,
+ available_on_public_internet=bool(
+ getattr(mcp_server, "available_on_public_internet", False)
+ ),
updated_at=getattr(mcp_server, "updated_at", None),
)
return new_server
@@ -696,6 +706,23 @@ async def get_allowed_mcp_servers(
verbose_logger.warning(f"Failed to get allowed MCP servers: {str(e)}.")
return allow_all_server_ids
+ def filter_server_ids_by_ip(
+ self, server_ids: List[str], client_ip: Optional[str]
+ ) -> List[str]:
+ """
+ Filter server IDs by client IP — external callers only see public servers.
+
+ Returns server_ids unchanged when client_ip is None (no filtering).
+ """
+ if client_ip is None:
+ return server_ids
+ return [
+ sid
+ for sid in server_ids
+ if (s := self.get_mcp_server_by_id(sid)) is not None
+ and self._is_server_accessible_from_ip(s, client_ip)
+ ]
+
async def get_tools_for_server(self, server_id: str) -> List[MCPTool]:
"""
Get the tools for a given server
@@ -1929,7 +1956,9 @@ async def _call_regular_mcp_tool(
)
async def _call_tool_via_client(client, params):
- return await client.call_tool(params, host_progress_callback=host_progress_callback)
+ return await client.call_tool(
+ params, host_progress_callback=host_progress_callback
+ )
tasks.append(
asyncio.create_task(_call_tool_via_client(client, call_tool_params))
@@ -1967,7 +1996,6 @@ async def call_tool(
oauth2_headers: Optional[Dict[str, str]] = None,
raw_headers: Optional[Dict[str, str]] = None,
host_progress_callback: Optional[Callable] = None,
-
) -> CallToolResult:
"""
Call a tool with the given name and arguments
@@ -2200,6 +2228,42 @@ def get_mcp_servers_from_ids(self, server_ids: List[str]) -> List[MCPServer]:
servers.append(server)
return servers
+ def _get_general_settings(self) -> Dict[str, Any]:
+ """Get general_settings, importing lazily to avoid circular imports."""
+ try:
+ from litellm.proxy.proxy_server import (
+ general_settings as proxy_general_settings,
+ )
+ return proxy_general_settings
+ except ImportError:
+ # Fallback if proxy_server not available
+ return {}
+
+ def _is_server_accessible_from_ip(
+ self, server: MCPServer, client_ip: Optional[str]
+ ) -> bool:
+ """
+ Check if a server is accessible from the given client IP.
+
+ - If client_ip is None, no IP filtering is applied (internal callers).
+ - If the server has available_on_public_internet=True, it's always accessible.
+ - Otherwise, only internal/private IPs can access it.
+ """
+ if client_ip is None:
+ return True
+ if server.available_on_public_internet:
+ return True
+ # Check backwards compat: litellm.public_mcp_servers
+ public_ids = set(litellm.public_mcp_servers or [])
+ if server.server_id in public_ids:
+ return True
+ # Non-public server: only accessible from internal IPs
+ general_settings = self._get_general_settings()
+ internal_networks = IPAddressUtils.parse_internal_networks(
+ general_settings.get("mcp_internal_ip_ranges")
+ )
+ return IPAddressUtils.is_internal_ip(client_ip, internal_networks)
+
def get_mcp_server_by_id(self, server_id: str) -> Optional[MCPServer]:
"""
Get the MCP Server from the server id
@@ -2212,27 +2276,72 @@ def get_mcp_server_by_id(self, server_id: str) -> Optional[MCPServer]:
def get_public_mcp_servers(self) -> List[MCPServer]:
"""
- Get the public MCP servers
+ Get the public MCP servers (available_on_public_internet=True flag on server).
+ Also includes servers from litellm.public_mcp_servers for backwards compat.
"""
servers: List[MCPServer] = []
- if litellm.public_mcp_servers is None:
- return servers
- for server_id in litellm.public_mcp_servers:
- server = self.get_mcp_server_by_id(server_id)
- if server:
+ public_ids = set(litellm.public_mcp_servers or [])
+ for server in self.get_registry().values():
+ if server.available_on_public_internet or server.server_id in public_ids:
servers.append(server)
return servers
- def get_mcp_server_by_name(self, server_name: str) -> Optional[MCPServer]:
+ def get_mcp_server_by_name(
+ self, server_name: str, client_ip: Optional[str] = None
+ ) -> Optional[MCPServer]:
"""
- Get the MCP Server from the server name
+ Get the MCP Server from the server name.
+
+ Uses priority-based matching to avoid collisions:
+ 1. First pass: exact alias match (highest priority)
+ 2. Second pass: exact server_name match
+ 3. Third pass: exact name match (lowest priority)
+
+ Args:
+ server_name: The server name to look up.
+ client_ip: Optional client IP for access control. When provided,
+ non-public servers are hidden from external IPs.
"""
registry = self.get_registry()
+ # Pass 1: Match by alias (highest priority)
+ for server in registry.values():
+ if server.alias == server_name:
+ if not self._is_server_accessible_from_ip(server, client_ip):
+ return None
+ return server
+ # Pass 2: Match by server_name
for server in registry.values():
if server.server_name == server_name:
+ if not self._is_server_accessible_from_ip(server, client_ip):
+ return None
+ return server
+ # Pass 3: Match by name (lowest priority)
+ for server in registry.values():
+ if server.name == server_name:
+ if not self._is_server_accessible_from_ip(server, client_ip):
+ return None
return server
return None
+ def get_filtered_registry(
+ self, client_ip: Optional[str] = None
+ ) -> Dict[str, MCPServer]:
+ """
+ Get registry filtered by client IP access control.
+
+ Args:
+ client_ip: Optional client IP. When provided, non-public servers
+ are hidden from external IPs. When None, returns all servers.
+ """
+ registry = self.get_registry()
+ if client_ip is None:
+ return registry
+ return {
+ k: v
+ for k, v in registry.items()
+ if self._is_server_accessible_from_ip(v, client_ip)
+ }
+
def _generate_stable_server_id(
self,
server_name: str,
@@ -2462,6 +2571,7 @@ def _build_mcp_server_table(self, server: MCPServer) -> LiteLLM_MCPServerTable:
token_url=server.token_url,
registration_url=server.registration_url,
allow_all_keys=server.allow_all_keys,
+ available_on_public_internet=server.available_on_public_internet,
)
async def get_all_mcp_servers_unfiltered(self) -> List[LiteLLM_MCPServerTable]:
diff --git a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
index d93f852f22d..2cd56e0ff3f 100644
--- a/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
+++ b/litellm/proxy/_experimental/mcp_server/rest_endpoints.py
@@ -10,8 +10,10 @@
)
from litellm.proxy._experimental.mcp_server.utils import merge_mcp_headers
from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
from litellm.types.mcp import MCPAuth
+from litellm.types.utils import CallTypes
MCP_AVAILABLE: bool = True
try:
@@ -28,6 +30,7 @@
if MCP_AVAILABLE:
from mcp.types import Tool as MCPTool
+
from litellm.proxy._experimental.mcp_server.mcp_server_manager import (
global_mcp_server_manager,
)
@@ -76,6 +79,26 @@ def _create_tool_response_objects(tools, server_mcp_info):
for tool in tools
]
+ def _extract_mcp_headers_from_request(
+ request: Request,
+ mcp_request_handler_cls,
+ ) -> tuple:
+ """
+ Extract MCP auth headers from HTTP request.
+
+ Returns:
+ Tuple of (mcp_auth_header, mcp_server_auth_headers, raw_headers)
+ """
+ headers = request.headers
+ raw_headers = dict(headers)
+ mcp_auth_header = mcp_request_handler_cls._get_mcp_auth_header_from_headers(
+ headers
+ )
+ mcp_server_auth_headers = (
+ mcp_request_handler_cls._get_mcp_server_auth_headers_from_headers(headers)
+ )
+ return mcp_auth_header, mcp_server_auth_headers, raw_headers
+
async def _get_tools_for_single_server(
server,
server_auth_header,
@@ -96,6 +119,35 @@ async def _get_tools_for_single_server(
return _create_tool_response_objects(tools, server.mcp_info)
+ async def _resolve_allowed_mcp_servers_for_tool_call(
+ user_api_key_dict: UserAPIKeyAuth,
+ server_id: str,
+ ) -> List[MCPServer]:
+ """Resolve allowed MCP servers for the given user and validate server_id access."""
+ auth_contexts = await build_effective_auth_contexts(user_api_key_dict)
+ allowed_server_ids_set = set()
+ for auth_context in auth_contexts:
+ servers = await global_mcp_server_manager.get_allowed_mcp_servers(
+ user_api_key_auth=auth_context
+ )
+ allowed_server_ids_set.update(servers)
+ if server_id not in allowed_server_ids_set:
+ raise HTTPException(
+ status_code=403,
+ detail={
+ "error": "access_denied",
+ "message": f"The key is not allowed to access server {server_id}",
+ },
+ )
+ allowed_mcp_servers: List[MCPServer] = []
+ for allowed_server_id in allowed_server_ids_set:
+ server = global_mcp_server_manager.get_mcp_server_by_id(
+ allowed_server_id
+ )
+ if server is not None:
+ allowed_mcp_servers.append(server)
+ return allowed_mcp_servers
+
########################################################
@router.get("/tools/list", dependencies=[Depends(user_api_key_auth)])
async def list_tool_rest_api(
@@ -142,21 +194,25 @@ async def list_tool_rest_api(
auth_contexts = await build_effective_auth_contexts(user_api_key_dict)
+ _rest_client_ip = IPAddressUtils.get_mcp_client_ip(request)
+
allowed_server_ids_set = set()
for auth_context in auth_contexts:
servers = await global_mcp_server_manager.get_allowed_mcp_servers(
- user_api_key_auth=auth_context
+ user_api_key_auth=auth_context,
)
allowed_server_ids_set.update(servers)
- allowed_server_ids = list(allowed_server_ids_set)
+ allowed_server_ids = global_mcp_server_manager.filter_server_ids_by_ip(
+ list(allowed_server_ids_set), _rest_client_ip
+ )
list_tools_result = []
error_message = None
# If server_id is specified, only query that specific server
if server_id:
- if server_id not in allowed_server_ids_set:
+ if server_id not in allowed_server_ids:
raise HTTPException(
status_code=403,
detail={
@@ -164,7 +220,9 @@ async def list_tool_rest_api(
"message": f"The key is not allowed to access server {server_id}",
},
)
- server = global_mcp_server_manager.get_mcp_server_by_id(server_id)
+ server = global_mcp_server_manager.get_mcp_server_by_id(
+ server_id
+ )
if server is None:
return {
"tools": [],
@@ -261,7 +319,14 @@ async def call_tool_rest_api(
from litellm.proxy._experimental.mcp_server.auth.user_api_key_auth_mcp import (
MCPRequestHandler,
)
- from litellm.proxy.proxy_server import add_litellm_data_to_request, proxy_config
+ from litellm.proxy.common_request_processing import (
+ ProxyBaseLLMRequestProcessing,
+ )
+ from litellm.proxy.proxy_server import (
+ general_settings,
+ proxy_config,
+ proxy_logging_obj,
+ )
try:
data = await request.json()
@@ -289,28 +354,22 @@ async def call_tool_rest_api(
tool_arguments = data.get("arguments")
- data = await add_litellm_data_to_request(
- data=data,
- request=request,
- user_api_key_dict=user_api_key_dict,
- proxy_config=proxy_config,
+ proxy_base_llm_response_processor = ProxyBaseLLMRequestProcessing(data=data)
+ data, logging_obj = (
+ await proxy_base_llm_response_processor.common_processing_pre_call_logic(
+ request=request,
+ user_api_key_dict=user_api_key_dict,
+ proxy_config=proxy_config,
+ route_type=CallTypes.call_mcp_tool.value,
+ proxy_logging_obj=proxy_logging_obj,
+ general_settings=general_settings,
+ )
)
- # FIX: Extract MCP auth headers from request
- # The UI sends bearer token in x-mcp-auth header and server-specific headers,
- # but they weren't being extracted and passed to call_mcp_tool.
- # This fix ensures auth headers are properly extracted from the HTTP request
- # and passed through to the MCP server for authentication.
- headers = request.headers
- raw_headers_from_request = dict(headers)
- mcp_auth_header = MCPRequestHandler._get_mcp_auth_header_from_headers(
- headers
- )
- mcp_server_auth_headers = (
- MCPRequestHandler._get_mcp_server_auth_headers_from_headers(headers)
+ # Extract MCP auth headers from request and add to data dict
+ mcp_auth_header, mcp_server_auth_headers, raw_headers_from_request = (
+ _extract_mcp_headers_from_request(request, MCPRequestHandler)
)
-
- # Add extracted headers to data dict to pass to call_mcp_tool
if mcp_auth_header:
data["mcp_auth_header"] = mcp_auth_header
if mcp_server_auth_headers:
@@ -325,14 +384,21 @@ async def call_tool_rest_api(
# Get all auth contexts
auth_contexts = await build_effective_auth_contexts(user_api_key_dict)
- # Collect allowed server IDs from all contexts
+ # Collect allowed server IDs from all contexts, then apply IP filtering
+ _rest_client_ip = IPAddressUtils.get_mcp_client_ip(request)
allowed_server_ids_set = set()
for auth_context in auth_contexts:
servers = await global_mcp_server_manager.get_allowed_mcp_servers(
- user_api_key_auth=auth_context
+ user_api_key_auth=auth_context,
)
allowed_server_ids_set.update(servers)
+ allowed_server_ids_set = set(
+ global_mcp_server_manager.filter_server_ids_by_ip(
+ list(allowed_server_ids_set), _rest_client_ip
+ )
+ )
+
# Check if the specified server_id is allowed
if server_id not in allowed_server_ids_set:
raise HTTPException(
diff --git a/litellm/proxy/_experimental/mcp_server/server.py b/litellm/proxy/_experimental/mcp_server/server.py
index 79cd88227a9..890c4ae8fb2 100644
--- a/litellm/proxy/_experimental/mcp_server/server.py
+++ b/litellm/proxy/_experimental/mcp_server/server.py
@@ -5,12 +5,24 @@
import asyncio
import contextlib
-from datetime import datetime
import traceback
import uuid
-from typing import Any, AsyncIterator, Dict, List, Optional, Tuple, Union, cast, Callable
+from datetime import datetime
+from typing import (
+ Any,
+ AsyncIterator,
+ Callable,
+ Dict,
+ List,
+ Optional,
+ Tuple,
+ Union,
+ cast,
+)
+
from fastapi import FastAPI, HTTPException
from pydantic import AnyUrl, ConfigDict
+from starlette.requests import Request as StarletteRequest
from starlette.types import Receive, Scope, Send
from litellm._logging import verbose_logger
@@ -25,6 +37,7 @@
LITELLM_MCP_SERVER_VERSION,
)
from litellm.proxy._types import UserAPIKeyAuth
+from litellm.proxy.auth.ip_address_utils import IPAddressUtils
from litellm.types.mcp import MCPAuth
from litellm.types.mcp_server.mcp_server_manager import MCPInfo, MCPServer
from litellm.types.utils import CallTypes, StandardLoggingMCPToolCall
@@ -213,6 +226,7 @@ async def list_tools() -> List[MCPTool]:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
f"MCP list_tools - User API Key Auth from context: {user_api_key_auth}"
@@ -276,6 +290,7 @@ async def mcp_server_tool_call(
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
@@ -288,7 +303,7 @@ async def mcp_server_tool_call(
host_token = getattr(host_ctx.meta, 'progressToken', None)
if host_token and hasattr(host_ctx, 'session') and host_ctx.session:
host_session = host_ctx.session
-
+
async def forward_progress(progress: float, total: float | None):
"""Forward progress notifications from external MCP to Host"""
try:
@@ -300,7 +315,7 @@ async def forward_progress(progress: float, total: float | None):
verbose_logger.debug(f"Forwarded progress {progress}/{total} to Host")
except Exception as e:
verbose_logger.error(f"Failed to forward progress to Host: {e}")
-
+
host_progress_callback = forward_progress
verbose_logger.debug(f"Host progressToken captured: {host_token[:8]}...")
except Exception as e:
@@ -387,6 +402,7 @@ async def list_prompts() -> List[Prompt]:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
f"MCP list_prompts - User API Key Auth from context: {user_api_key_auth}"
@@ -440,6 +456,7 @@ async def get_prompt(
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
@@ -467,6 +484,7 @@ async def list_resources() -> List[Resource]:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
f"MCP list_resources - User API Key Auth from context: {user_api_key_auth}"
@@ -505,6 +523,7 @@ async def list_resource_templates() -> List[ResourceTemplate]:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
verbose_logger.debug(
f"MCP list_resource_templates - User API Key Auth from context: {user_api_key_auth}"
@@ -544,6 +563,7 @@ async def read_resource(url: AnyUrl) -> list[ReadResourceContents]:
mcp_server_auth_headers,
oauth2_headers,
raw_headers,
+ _client_ip,
) = get_auth_context()
read_resource_result = await mcp_read_resource(
@@ -702,13 +722,57 @@ def filter_tools_by_allowed_tools(
return tools_to_return
+ def _get_client_ip_from_context() -> Optional[str]:
+ """
+ Extract client_ip from auth context.
+ Returns None if context not set (caller should handle this as "no IP filtering").
+ """
+ try:
+ auth_user = auth_context_var.get()
+ if auth_user and isinstance(auth_user, MCPAuthenticatedUser):
+ return auth_user.client_ip
+ except Exception:
+ pass
+ return None
+
async def _get_allowed_mcp_servers(
user_api_key_auth: Optional[UserAPIKeyAuth],
mcp_servers: Optional[List[str]],
+ client_ip: Optional[str] = None,
) -> List[MCPServer]:
- """Return allowed MCP servers for a request after applying filters."""
+ """Return allowed MCP servers for a request after applying filters.
+
+ Args:
+ user_api_key_auth: The authenticated user's API key info.
+ mcp_servers: Optional list of server names to filter to.
+ client_ip: Client IP for IP-based access control. If None, falls back to
+ auth context. Pass explicitly from request handlers for safety.
+ Note: If client_ip is None and auth context is not set, IP filtering is skipped.
+ This is intentional for internal callers but may indicate a bug if called
+ from a request handler without proper context setup.
+ """
+ # Use explicit client_ip if provided, otherwise try auth context
+ if client_ip is None:
+ client_ip = _get_client_ip_from_context()
+ if client_ip is None:
+ verbose_logger.debug(
+ "MCP _get_allowed_mcp_servers called without client_ip and no auth context. "
+ "IP filtering will be skipped. This is expected for internal calls."
+ )
+
allowed_mcp_server_ids = (
- await global_mcp_server_manager.get_allowed_mcp_servers(user_api_key_auth)
+ await global_mcp_server_manager.get_allowed_mcp_servers(
+ user_api_key_auth
+ )
+ )
+ allowed_mcp_server_ids = (
+ global_mcp_server_manager.filter_server_ids_by_ip(
+ allowed_mcp_server_ids, client_ip
+ )
+ )
+ verbose_logger.debug(
+ "MCP IP filter: client_ip=%s, allowed_server_ids=%s",
+ client_ip, allowed_mcp_server_ids,
)
allowed_mcp_servers: List[MCPServer] = []
for allowed_mcp_server_id in allowed_mcp_server_ids:
@@ -1715,7 +1779,7 @@ async def _handle_managed_mcp_tool(
oauth2_headers: Optional[Dict[str, str]] = None,
raw_headers: Optional[Dict[str, str]] = None,
litellm_logging_obj: Optional[Any] = None,
- host_progress_callback: Optional[Callable] = None,
+ host_progress_callback: Optional[Callable] = None,
) -> CallToolResult:
"""Handle tool execution for managed server tools"""
# Import here to avoid circular import
@@ -1891,6 +1955,10 @@ async def handle_streamable_http_mcp(
oauth2_headers,
raw_headers,
) = await extract_mcp_auth_context(scope, path)
+
+ # Extract client IP for MCP access control
+ _client_ip = IPAddressUtils.get_mcp_client_ip(StarletteRequest(scope))
+
verbose_logger.debug(
f"MCP request mcp_servers (header/path): {mcp_servers}"
)
@@ -1899,11 +1967,11 @@ async def handle_streamable_http_mcp(
)
# https://datatracker.ietf.org/doc/html/rfc9728#name-www-authenticate-response
for server_name in mcp_servers or []:
- server = global_mcp_server_manager.get_mcp_server_by_name(server_name)
+ server = global_mcp_server_manager.get_mcp_server_by_name(
+ server_name, client_ip=_client_ip
+ )
if server and server.auth_type == MCPAuth.oauth2 and not oauth2_headers:
- from starlette.requests import Request
-
- request = Request(scope)
+ request = StarletteRequest(scope)
base_url = str(request.base_url).rstrip("/")
authorization_uri = (
@@ -1925,6 +1993,7 @@ async def handle_streamable_http_mcp(
mcp_server_auth_headers=mcp_server_auth_headers,
oauth2_headers=oauth2_headers,
raw_headers=raw_headers,
+ client_ip=_client_ip,
)
# Ensure session managers are initialized
@@ -1936,12 +2005,13 @@ async def handle_streamable_http_mcp(
_strip_stale_mcp_session_header(scope, session_manager)
await session_manager.handle_request(scope, receive, send)
+ except HTTPException:
+ # Re-raise HTTP exceptions to preserve status codes and details
+ raise
except Exception as e:
- raise e
verbose_logger.exception(f"Error handling MCP request: {e}")
- # Instead of re-raising, try to send a graceful error response
+ # Try to send a graceful error response for non-HTTP exceptions
try:
- # Send a proper HTTP error response instead of letting the exception bubble up
from starlette.responses import JSONResponse
from starlette.status import HTTP_500_INTERNAL_SERVER_ERROR
@@ -1969,6 +2039,10 @@ async def handle_sse_mcp(scope: Scope, receive: Receive, send: Send) -> None:
oauth2_headers,
raw_headers,
) = await extract_mcp_auth_context(scope, path)
+
+ # Extract client IP for MCP access control
+ _sse_client_ip = IPAddressUtils.get_mcp_client_ip(StarletteRequest(scope))
+
verbose_logger.debug(
f"MCP request mcp_servers (header/path): {mcp_servers}"
)
@@ -1982,6 +2056,7 @@ async def handle_sse_mcp(scope: Scope, receive: Receive, send: Send) -> None:
mcp_server_auth_headers=mcp_server_auth_headers,
oauth2_headers=oauth2_headers,
raw_headers=raw_headers,
+ client_ip=_sse_client_ip,
)
if not _SESSION_MANAGERS_INITIALIZED:
@@ -2045,6 +2120,7 @@ def set_auth_context(
mcp_server_auth_headers: Optional[Dict[str, Dict[str, str]]] = None,
oauth2_headers: Optional[Dict[str, str]] = None,
raw_headers: Optional[Dict[str, str]] = None,
+ client_ip: Optional[str] = None,
) -> None:
"""
Set the UserAPIKeyAuth in the auth context variable.
@@ -2054,6 +2130,7 @@ def set_auth_context(
mcp_auth_header: MCP auth header to be passed to the MCP server (deprecated)
mcp_servers: Optional list of server names and access groups to filter by
mcp_server_auth_headers: Optional dict of server-specific auth headers {server_alias: auth_value}
+ client_ip: Client IP address for MCP access control
"""
auth_user = MCPAuthenticatedUser(
user_api_key_auth=user_api_key_auth,
@@ -2062,6 +2139,7 @@ def set_auth_context(
mcp_server_auth_headers=mcp_server_auth_headers,
oauth2_headers=oauth2_headers,
raw_headers=raw_headers,
+ client_ip=client_ip,
)
auth_context_var.set(auth_user)
@@ -2073,14 +2151,15 @@ def get_auth_context() -> (
Optional[Dict[str, Dict[str, str]]],
Optional[Dict[str, str]],
Optional[Dict[str, str]],
+ Optional[str],
]
):
"""
Get the UserAPIKeyAuth from the auth context variable.
Returns:
- Tuple[Optional[UserAPIKeyAuth], Optional[str], Optional[List[str]], Optional[Dict[str, str]]]:
- UserAPIKeyAuth object, MCP auth header (deprecated), MCP servers (can include access groups), and server-specific auth headers
+ Tuple containing: UserAPIKeyAuth, MCP auth header (deprecated),
+ MCP servers, server-specific auth headers, OAuth2 headers, raw headers, client IP
"""
auth_user = auth_context_var.get()
if auth_user and isinstance(auth_user, MCPAuthenticatedUser):
@@ -2091,8 +2170,9 @@ def get_auth_context() -> (
auth_user.mcp_server_auth_headers,
auth_user.oauth2_headers,
auth_user.raw_headers,
+ auth_user.client_ip,
)
- return None, None, None, None, None, None
+ return None, None, None, None, None, None, None
########################################################
############ End of Auth Context Functions #############
diff --git a/litellm/proxy/_experimental/out/404.html b/litellm/proxy/_experimental/out/404.html
new file mode 100644
index 00000000000..e40a85b4ddb
--- /dev/null
+++ b/litellm/proxy/_experimental/out/404.html
@@ -0,0 +1 @@
+404: This page could not be found.LiteLLM Dashboard
404
This page could not be found.
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/404/index.html b/litellm/proxy/_experimental/out/404/index.html
deleted file mode 100644
index a8bd30680ab..00000000000
--- a/litellm/proxy/_experimental/out/404/index.html
+++ /dev/null
@@ -1 +0,0 @@
-404: This page could not be found.LiteLLM Dashboard
404
This page could not be found.
\ No newline at end of file
diff --git a/litellm/proxy/_experimental/out/_next/static/chunks/1059-26bdac09bbb12a4b.js b/litellm/proxy/_experimental/out/_next/static/chunks/1059-26bdac09bbb12a4b.js
deleted file mode 100644
index cd4f5e4e326..00000000000
--- a/litellm/proxy/_experimental/out/_next/static/chunks/1059-26bdac09bbb12a4b.js
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