Add new integrations and update integration documentation

[aantn]

Summary

This PR updates the integrations documentation in the README and adds support for new MCP (Model Context Protocol) integrations while improving the presentation of existing ones.

Key Changes

• New Integrations Added:

  • Confluence (MCP) - Private runbooks and documentation via MCP protocol
  • Kubernetes Remediation (MCP) - Apply fixes like scaling, rollbacks, and resource edits
  • Prefect (MCP) - Workflow orchestration monitoring, flow runs, and worker health

• Integration Documentation Improvements:

  • Added proper documentation links and logos for Sentry integration (previously listed without link)
  • Added Sentry integration icon (sentry-icon.svg and sentry-icon.png)
  • Added Prefect integration icon (prefect-icon.svg and prefect-icon.png)
  • Converted Sentry from plain text to properly formatted table entry with icon and link

• Documentation Updates:

  • Updated the "See the full list" reference to remove Prefect and Sentry from the "additional integrations" list since they are now documented in the main table
  • Maintained alphabetical ordering in the integrations table

Notable Details

• All new integrations are marked with (MCP) to indicate they use the Model Context Protocol
• Added SVG and PNG icon files for visual consistency in the integrations table
• Sentry integration was previously undocumented in the table; now properly linked and formatted

https://claude.ai/code/session_01GD3S9yEts4nixLCFamKnek

Summary by CodeRabbit

• Documentation
  • Added Confluence, Kubernetes Remediation, and Prefect integrations to the supported data sources list.
  • Updated Sentry integration documentation for consistency with other data source entries.

[claude]

Claude Code Review

This repository is configured for manual code reviews. Comment @claude review to trigger a review.

[github-actions]

✅ Results of HolmesGPT evals

Automatically triggered by commit deceb64 on branch claude/fix-readme-data-sources-3zzzv

View workflow logs

Results of HolmesGPT evals

• ask_holmes: 10/10 test cases were successful, 0 regressions

Status	Test case	Time	Turns	Tools	Cost	Total tokens	Input	Max input	Output	Max output	Cached	Non-cached	Reasoning	Compactions
✅	09_crashpod	28.4s	6	11	$0.2411	121,361	119,539	23,136	1,822	493	95,801	23,738	—	—
✅	101_loki_historical_logs_pod_deleted	40.8s	7	12	$0.2771	148,602	146,131	24,419	2,471	562	121,295	24,836	—	—
✅	111_pod_names_contain_service	30.7s	7	10	$0.2422	139,082	137,285	22,170	1,797	472	114,862	22,423	—	—
✅	112_find_pvcs_by_uuid	19.9s	4	6	$0.2082	81,713	80,345	22,761	1,368	593	56,919	23,426	—	—
✅	12_job_crashing	28.8s	6	12	$0.2526	126,483	124,653	24,064	1,830	447	99,212	25,441	—	—
✅	176_network_policy_blocking_traffic_no_runbooks	31.1s	5	13	$0.2645	108,972	106,664	24,595	2,308	595	79,387	27,277	—	—
✅	227_count_configmaps_per_namespace[0]	28.8s	8	11	$0.2325	150,344	148,837	20,687	1,507	422	127,823	21,014	—	—
✅	24_misconfigured_pvc	29.5s	6	14	$0.2460	121,476	119,524	22,908	1,952	541	95,339	24,185	—	—
✅	43_current_datetime_from_prompt	4.1s	1	—	$0.1087	16,987	16,853	16,853	134	134	0	16,853	—	—
✅	61_exact_match_counting	13.2s	4	4	$0.1507	70,828	70,381	18,132	447	226	52,237	18,144	—	—
	Total	25.5s avg	5.4 avg	10.3 avg	$2.2237	1,085,848	1,070,212	24,595	15,636	595	842,875	227,337	—	—

Benchmark Comparison Details

Baseline: latest ci-benchmark experiment on master

Status: Success - 73 test/model combinations loaded

Benchmark experiment:

• ci-benchmark-23102181491 (created: 2026-03-15)

No benchmark data available for comparison.

Benchmark has no cost, total tokens, cached tokens data. Will appear after the next weekly benchmark run.

Comparison indicators:

• ±0% — diff under 10% (within noise threshold)
• ↑N%/↓N% — diff 10-25%
• ↑N%/↓N% — diff over 25% (significant)

📖 Legend

Icon	Meaning
✅	The test was successful
➖	The test was skipped
⚠️	The test failed but is known to be flaky or known to fail
🚧	The test had a setup failure (not a code regression)
🔧	The test failed due to mock data issues (not a code regression)
🚫	The test was throttled by API rate limits/overload
❌	The test failed and should be fixed before merging the PR

🔄 Re-run evals manually

⚠️ Warning: /eval comments always run using the workflow from master, not from this PR branch. If you modified the GitHub Action (e.g., added secrets or env vars), those changes won't take effect.

To test workflow changes, use the GitHub CLI or Actions UI instead:

gh workflow run eval-regression.yaml --repo HolmesGPT/holmesgpt --ref claude/fix-readme-data-sources-3zzzv -f markers=regression -f filter=

---

Option 1: Comment on this PR with /eval:

/eval
tags: regression

Or with more options (one per line):

/eval
model: gpt-4o
tags: regression
filter: 09_crashpod
iterations: 5

Run evals on a different branch (e.g., master) for comparison:

/eval
branch: master
tags: regression

Option	Description
model	Model(s) to test (default: same as automatic runs)
tags	Pytest tags / markers (no default - runs all tests!)
filter	Pytest -k filter (use /list to see valid eval names)
iterations	Number of runs, max 10
branch	Run evals on a different branch (for cross-branch comparison)

Quick re-run: Use /rerun to re-run the most recent /eval on this PR with the same parameters.

Option 2: Trigger via GitHub Actions UI → "Run workflow"

Option 3: Add PR labels to include extra evals in automatic regression runs:

Label	Effect
evals-tag-<name>	Run tests with tag <name> alongside regression
evals-id-<name>	Run a specific eval by test ID

Examples: evals-tag-easy, evals-id-09_crashpod

🏷️ Valid tags

benchmark, chain-of-causation, compaction, confluence, context_window, coralogix, counting, database, datadog, datetime, db-connectors, easy, elasticsearch, embeds, fast, frontend, grafana, hard, integration, kafka, kubernetes, leaked-information, logs, loki, medium, metrics, network, newrelic, no-cicd, numerical, one-test, port-forward, prometheus, question-answer, regression, runbooks, slackbot, storage, toolset-limitation, traces, transparency

---

Commands: /eval · /rerun · /list

CLI: gh workflow run eval-regression.yaml --repo HolmesGPT/holmesgpt --ref claude/fix-readme-data-sources-3zzzv -f markers=regression -f filter=

[github-actions]

✅ Docker images ready for 94202e50 (built in 7m 34s)

• us-central1-docker.pkg.dev/robusta-development/temporary-builds/holmes:94202e50
• us-central1-docker.pkg.dev/robusta-development/temporary-builds/holmes-operator:94202e50

⚠️ Warning: does not support ARM (ARM images are built on release only - not on every PR)

Use these tags to pull the images for testing.

📋 Copy commands

⚠️ Temporary images are deleted after 30 days. Copy to a permanent registry before using them:

gcloud auth configure-docker us-central1-docker.pkg.dev
docker pull us-central1-docker.pkg.dev/robusta-development/temporary-builds/holmes:94202e50
docker tag us-central1-docker.pkg.dev/robusta-development/temporary-builds/holmes:94202e50 me-west1-docker.pkg.dev/robusta-development/development/holmes-dev:94202e50
docker push me-west1-docker.pkg.dev/robusta-development/development/holmes-dev:94202e50
docker pull us-central1-docker.pkg.dev/robusta-development/temporary-builds/holmes-operator:94202e50
docker tag us-central1-docker.pkg.dev/robusta-development/temporary-builds/holmes-operator:94202e50 me-west1-docker.pkg.dev/robusta-development/development/holmes-operator-dev:94202e50
docker push me-west1-docker.pkg.dev/robusta-development/development/holmes-operator-dev:94202e50

Patch Helm values in one line (choose the chart you use):

HolmesGPT chart:

helm upgrade --install holmesgpt ./helm/holmes \
  --set registry=me-west1-docker.pkg.dev/robusta-development/development \
  --set image=holmes-dev:94202e50 \
  --set operator.registry=me-west1-docker.pkg.dev/robusta-development/development \
  --set operator.image=holmes-operator-dev:94202e50

Robusta wrapper chart:

helm upgrade --install robusta robusta/robusta \
  --reuse-values \
  --set holmes.registry=me-west1-docker.pkg.dev/robusta-development/development \
  --set holmes.image=holmes-dev:94202e50 \
  --set holmes.operator.registry=me-west1-docker.pkg.dev/robusta-development/development \
  --set holmes.operator.image=holmes-operator-dev:94202e50

[coderabbitai]

Caution

Review failed

Pull request was closed or merged during review

Walkthrough

README.md updated to add three new MCP data source entries: Confluence, Kubernetes Remediation, and Prefect. Sentry entry replaced with Sentry (MCP) version. Prefect mention removed from final toolsets description.

Changes

Cohort / File(s)	Summary
Data Sources Documentation README.md	Added three new MCP data source entries (Confluence, Kubernetes Remediation, Prefect) and replaced Sentry with Sentry (MCP). Removed Prefect mention from final toolsets description.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~2 minutes

Possibly related PRs

• Updating HolmesGPT readme #705: Modifies README's built-in data sources/toolsets list with new entries and links.
• Readme tools updated with integration logos #451: Updates the "Data Sources" section in README with integration entries and status changes.
• Add "Why HolmesGPT?" documentation page #1635: Modifies README's data-sources/toolsets content by adding and replacing toolset entries.

Suggested reviewers

• arikalon1
• moshemorad

🚥 Pre-merge checks | ✅ 3

✅ Passed checks (3 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately summarizes the main changes: adding new integrations (Confluence, Kubernetes Remediation, Prefect MCPs) and updating integration documentation in README.md.
Docstring Coverage	✅ Passed	No functions found in the changed files to evaluate docstring coverage. Skipping docstring coverage check.

_{✏️ Tip: You can configure your own custom pre-merge checks in the settings.}

📝 Coding Plan

• Generate coding plan for human review comments

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