Which integrations are available for this server?

Allows searching, retrieving, and managing runbooks stored in Confluence using CQL queries against page properties. Enables creating pull requests with drafted runbooks in GitHub repositories. Enables creating merge requests with drafted runbooks in GitLab repositories.

How do I use holmesgpt-runbook-mcp?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@holmesgpt-runbook-mcp find runbook for payments-api OOMKill" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

holmesgpt-runbook-mcp

by polarpoint-io

Overview Schema Related Servers Score Discussions

Python

Remote

holmesgpt-runbook-mcp

holmesgpt-runbook-mcp hero

License

MCP server for HolmesGPT — runbook search, gap detection, AI-assisted drafting, and root cause analysis.

Works with any LLM provider (Anthropic, OpenAI, Azure OpenAI, or any OpenAI-compatible endpoint) and any Git provider (GitHub, GitLab, or Azure DevOps).

What it does

Five tools that give HolmesGPT (and any Confluence MCP client) a structured runbook layer:

Tool	What it does
`runbook_search`	CQL search by `service`, `failure_mode`, `alert_name` via Confluence Page Properties — exact match, not fuzzy
`runbook_get`	Full runbook content by page ID or title
`investigation_classify`	Fast LLM (LLM_FAST_MODEL) classifies an investigation log as a runbook gap
`runbook_draft`	Capable LLM (LLM_CAPABLE_MODEL) drafts a runbook from investigation logs → opens draft PR/MR
`root_cause_analyse`	Pulls matching runbooks + capable LLM reasons over live incident data

Related MCP server: MCP Atlassian

Why CQL beats full-text search

Runbooks published via python-mkdocs-to-confluence include a confluence_properties: frontmatter block that renders as a Confluence Page Properties macro. This server queries those properties directly:

property["Service"]="payments-api" AND property["Failure-Mode"]="OOMKill"

Holmes finds the exact runbook on the first query instead of ranking 40 pages that mention both terms.

Runbook format

Runbooks must use the Polarpoint AI-optimised runbook format with confluence_properties frontmatter. The template is included in this repo at docs/runbook-template.md. runbook_draft generates this format automatically.

Prerequisites

HolmesGPT running in your cluster
Confluence space for runbooks (published via the MkDocs plugin)
A Git repo containing runbook markdown sources (GitHub, GitLab, or Azure DevOps)
An API key for your LLM provider of choice

Quickstart

1. Install with your providers

# Anthropic + GitHub (default)
pip install "holmesgpt-runbook-mcp[anthropic-github]"

# OpenAI + GitLab
pip install "holmesgpt-runbook-mcp[openai-gitlab]"

# Anthropic + Azure DevOps
pip install "holmesgpt-runbook-mcp[anthropic-azure-devops]"

# Everything
pip install "holmesgpt-runbook-mcp[all]"

2. Deploy to Kubernetes

# Create secrets (or use ExternalSecrets — see deploy/externalsecret.yaml)
kubectl create secret generic holmesgpt-runbook-mcp-secrets \
  --namespace platform-tools \
  --from-literal=llm-api-key=$LLM_API_KEY \
  --from-literal=confluence-url=$CONFLUENCE_URL \
  --from-literal=confluence-username=$CONFLUENCE_USERNAME \
  --from-literal=confluence-api-token=$CONFLUENCE_API_TOKEN \
  --from-literal=git-token=$GIT_TOKEN

kubectl apply -f deploy/

3. Wire into HolmesGPT

# holmes-config.yaml
mcpServers:
  - name: holmesgpt-runbook-mcp
    url: http://holmesgpt-runbook-mcp.platform-tools.svc.cluster.local:8080/mcp

4. Test the connection

curl http://holmesgpt-runbook-mcp.platform-tools.svc.cluster.local:8080/health

LLM provider configuration

Set LLM_PROVIDER and the relevant variables. Everything else is optional.

Anthropic (default)

LLM_PROVIDER=anthropic
LLM_API_KEY=sk-ant-...
# Optional overrides:
LLM_FAST_MODEL=claude-haiku-4-5-20251001
LLM_CAPABLE_MODEL=claude-sonnet-4-6

OpenAI

LLM_PROVIDER=openai
LLM_API_KEY=sk-...
LLM_FAST_MODEL=gpt-4o-mini        # default
LLM_CAPABLE_MODEL=gpt-4o          # default

Azure OpenAI

LLM_PROVIDER=azure
LLM_API_KEY=<azure-api-key>
LLM_BASE_URL=https://<resource>.openai.azure.com/
LLM_AZURE_API_VERSION=2024-02-01  # default
LLM_FAST_MODEL=gpt-4o-mini        # deployment name
LLM_CAPABLE_MODEL=gpt-4o          # deployment name

OpenAI-compatible (Ollama, vLLM, Together, Groq, etc.)

LLM_PROVIDER=openai-compatible
LLM_BASE_URL=http://ollama.platform-tools.svc.cluster.local:11434/v1
LLM_API_KEY=none                  # use 'none' if endpoint doesn't require a key
LLM_FAST_MODEL=llama3
LLM_CAPABLE_MODEL=llama3:70b

Git provider configuration

Set GIT_PROVIDER and the relevant variables.

GitHub (default)

GIT_PROVIDER=github
GIT_TOKEN=ghp_...                 # PAT with repo write scope
GIT_RUNBOOK_REPO=org/repo
GIT_BASE_BRANCH=main              # default
# Self-hosted GitHub Enterprise:
# GIT_HOST=github.myco.com

GitLab

GIT_PROVIDER=gitlab
GIT_TOKEN=glpat-...               # Personal access token with api scope
GIT_RUNBOOK_REPO=group/repo       # or group/subgroup/repo
GIT_BASE_BRANCH=main
# Self-hosted:
GIT_HOST=https://gitlab.myco.com  # default: https://gitlab.com

Azure DevOps

GIT_PROVIDER=azure-devops
GIT_TOKEN=<pat>                   # PAT with Code (Read & Write) scope
GIT_HOST=https://dev.azure.com/my-org
GIT_RUNBOOK_REPO=ProjectName/RepoName
GIT_BASE_BRANCH=main

Full environment variable reference

Variable	Required	Default	Description
`LLM_PROVIDER`		`anthropic`	`anthropic` \| `openai` \| `azure` \| `openai-compatible`
`LLM_API_KEY`	✅	—	API key for your LLM provider
`LLM_FAST_MODEL`		provider default	Model for classification (cheap/fast)
`LLM_CAPABLE_MODEL`		provider default	Model for drafting and RCA (more capable)
`LLM_BASE_URL`	✅ azure/compatible	—	Endpoint URL for Azure or self-hosted
`LLM_AZURE_API_VERSION`		`2024-02-01`	Azure OpenAI API version
`GIT_PROVIDER`		`github`	`github` \| `gitlab` \| `azure-devops`
`GIT_TOKEN`	✅	—	Git provider personal access token
`GIT_RUNBOOK_REPO`		`polarpoint-io/markdown-pol-docs`	`org/repo` (GitHub/GitLab) or `Project/Repo` (Azure DevOps)
`GIT_BASE_BRANCH`		`main`	Branch to open PRs/MRs against
`GIT_HOST`	✅ azure-devops	—	Self-hosted URL or Azure DevOps org URL
`CONFLUENCE_URL`	✅	—	e.g. `https://your-org.atlassian.net/wiki`
`CONFLUENCE_USERNAME`	✅	—	Atlassian email
`CONFLUENCE_API_TOKEN`	✅	—	Atlassian API token
`CONFLUENCE_RUNBOOK_SPACE`		`RUNBOOKS`	Confluence space key
`RUNBOOK_PATH_PREFIX`		`docs/technical-practices/...`	Path prefix for runbook files in repo

Development

# Install dev dependencies (includes all providers)
pip install -e ".[dev]"

# Run tests
pytest tests/

# Lint
ruff check src/ tests/
black --check src/ tests/

# Run locally (stdio transport for MCP Inspector)
python -m holmesgpt_runbook_mcp.server

How runbook_draft works

Holmes calls investigation_classify during an active investigation — the fast LLM classifies the log and returns has_gap=true with service/failure_mode/resolution extracted
Holmes accumulates classified gaps (in memory or a simple store)
When gap count for a (service, failure_mode) pair hits threshold, Holmes calls runbook_draft with the accumulated logs
The capable LLM drafts the runbook in the AI-optimised format, extracting real commands from the investigation logs
runbook_draft opens a draft PR/MR with Status: Draft — a platform engineer reviews and merges
The MkDocs CI build publishes the merged runbook to Confluence
Next time the same alert fires, runbook_search finds it on the first CQL query

HolmesGPT — the AI troubleshooting assistant this server extends
python-mkdocs-to-confluence — MkDocs plugin that publishes the Page Properties this server queries
Blog: HolmesGPT Knows What Your Runbooks Are Missing — the post this repo was built from

License

Apache 2.0

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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