feat: add supports_parallel_tool_calls for MCP servers - #9944
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Port from openai/codex#17667: MCP servers can now opt-in to parallel tool execution by setting supports_parallel_tool_calls: true in their config. This allows tools from the same server to run concurrently within a single tool-call batch, matching the behavior already available for built-in tools like web_search and read_file. Previously all MCP tools were forced sequential because they weren't in the _PARALLEL_SAFE_TOOLS set. Now _should_parallelize_tool_batch checks is_mcp_tool_parallel_safe() which looks up the server's config flag. Config example: mcp_servers: docs: command: "docs-server" supports_parallel_tool_calls: true Changes: - tools/mcp_tool.py: Track parallel-safe servers in _parallel_safe_servers set, populated during register_mcp_servers(). Add is_mcp_tool_parallel_safe() public API. - run_agent.py: Add _is_mcp_tool_parallel_safe() lazy-import wrapper. Update _should_parallelize_tool_batch() to check MCP tools against server config. - 11 new tests covering the feature end-to-end. - Updated MCP docs and config reference.
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Closing in favor of #26825, which salvages this PR onto current main with the cherry-pick conflict (circuit breaker block landed on main after this PR's branch point) resolved and two stale test mocks of the removed |
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Correction on the earlier close comment: #26825 was squash-merged (not rebase-merged). Authorship is preserved in either case since both PRs were authored by you. |
cameronpyne-smith
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Jun 13, 2026
The post-filing decoration re-queried issues created since a timestamp and stopped at the first non-empty result — racing GitHub's index, so the last-created issue often wasn't returned yet and went undecorated (#9951 got no type/board this round; #9944 earlier). Capture each issue number straight from `gh issue create` output and decorate exactly those — no re-query, no race, no settle delay. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Summary
Port of openai/codex#17667: MCP servers can now opt-in to parallel tool execution via a per-server config flag.
Problem
All MCP tools were forced to run sequentially because they weren't in the static
_PARALLEL_SAFE_TOOLSset in run_agent.py. This was unnecessarily slow for MCP servers whose tools are safe to run concurrently (e.g. read-only query servers, independent API endpoints).Solution
Add
supports_parallel_tool_calls: trueconfig option for MCP servers:When set, tools from that server are eligible for concurrent execution in the same tool-call batch, matching the behavior already available for built-in read-only tools (web_search, read_file, etc.).
Implementation
_parallel_safe_serversset tracks sanitized server names with the flag enabled. Populated duringregister_mcp_servers()(idempotent, handles toggling on/off). New public APIis_mcp_tool_parallel_safe(tool_name)checks if a tool belongs to a parallel-safe server._is_mcp_tool_parallel_safe()lazy-import wrapper._should_parallelize_tool_batch()now checks MCP tools against server config when they're not in the static parallel-safe set.is_mcp_tool_parallel_safe()andregister_mcp_serverstracking, plus 4 integration tests for_should_parallelize_tool_batch()with MCP tools.Architectural differences from Codex
Codex is Rust and threads the config through
ToolRouterat the crate level. Hermes uses a module-level set (_parallel_safe_servers) populated during MCP server registration, queried via a function that does server name extraction from tool names. The server name matching handles underscores in sanitized server names by checking all registered parallel-safe prefixes.Test plan