The full upstream README, mirrored here for reference. Install config, tool schemas, adoption signals, and an original overview live on the Gha Intel listing page.
An MCP server for GitHub Actions workflow timing analysis, configuration auditing, and billing insights.
| Tool | Description |
|---|---|
list_workflow_performance | Computes average, min, max, and p95 duration statistics for recent workflow runs. |
analyze_workflow_config | Evaluates workflow YAML for caching, parallelism, concurrency, artifacts, checkout depth, timeouts, runner pinning, Docker caching, and triggers. |
get_billing_usage | Returns Actions billing minutes and estimated cost by runner type, plus per-repo cache utilisation. |
fetch)repo and read:org scopesThree transport modes are available. Choose whichever fits your deployment:
The server runs as a subprocess of the MCP client over stdin/stdout. No network port required.
~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
%APPDATA%\Claude\claude_desktop_config.json (Windows)
~/.cursor/mcp.json
~/.codeium/windsurf/mcp_config.json
.vscode/mcp.json (workspace) or user settings
Open Cline settings, navigate to MCP Servers, and add:
~/.continue/config.yaml
~/.config/zed/settings.json
Go to Settings > Tools > AI Assistant > MCP and add:
Start the server in HTTP mode and point clients at the endpoint:
Or set via environment variable instead of the flag:
~/.cursor/mcp.json
.vscode/mcp.json
~/.codeium/windsurf/mcp_config.json
~/.continue/config.yaml
The container starts in HTTP mode by default. Point your client at http://localhost:3000/mcp.
Fetch real run timing data and compute job-level statistics.
| Parameter | Type | Required | Description |
|---|---|---|---|
owner | string | yes | GitHub owner (user or org) |
repo | string | yes | Repository name |
workflow_id | string | yes | Workflow file name (e.g. ci.yml) or numeric ID |
count | number | no | Number of recent runs to analyse (default: 10, max: 100) |
Output: Per-job and per-step timing stats (avg, min, max, p95), overall run timing, and a list of recent run conclusions.
Parse and audit a workflow YAML for optimisation opportunities.
| Parameter | Type | Required | Description |
|---|---|---|---|
workflow_content | string | yes | Full YAML content of the workflow file |
Output: Findings grouped by severity (critical / warning / info / good) across nine categories, each with a concrete recommendation.
Categories analysed: Dependency caching, matrix strategy and fail-fast, concurrency groups and cancel-in-progress, artifact uploads, git checkout depth, job timeout-minutes, runner version pinning, Docker layer caching, and trigger path filters.
Retrieve billing and cache consumption data.
| Parameter | Type | Required | Description |
|---|---|---|---|
owner | string | yes | GitHub username or organisation |
repo | string | no | Repository name for repo-scoped cache and run stats |
Output: Total minutes used, plan utilisation, estimated cost broken down by runner type (Ubuntu / macOS / Windows / large runners), plus per-repo cache size and utilisation percentage.
| Variable | Required | Description |
|---|---|---|
GITHUB_TOKEN | yes | GitHub personal access token. Requires repo scope for private repos, read:org for org billing. |
TRANSPORT | no | Set to http to enable HTTP mode (default: stdio). |
PORT | no | HTTP port when running in HTTP mode (default: 3000). |
MIT