gha-intel-mcp
Provides tools to analyze GitHub Actions workflow performance, audit workflow configurations, and retrieve billing usage data from GitHub.
Offers MCP tools for GitHub Actions workflow timing analysis, configuration auditing, and billing/cache usage insights.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@gha-intel-mcpWhat's the p95 runtime for our CI workflow runs?"
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.
An MCP server for GitHub Actions workflow timing analysis, configuration auditing, and billing insights.
Tools
Tool | Description |
| Computes average, min, max, and p95 duration statistics for recent workflow runs. |
| Evaluates workflow YAML for caching, parallelism, concurrency, artifacts, checkout depth, timeouts, runner pinning, Docker caching, and triggers. |
| Returns Actions billing minutes and estimated cost by runner type, plus per-repo cache utilisation. |
Related MCP server: copilot-usage-mcp
Requirements
Node.js >= 18 (uses native
fetch)A GitHub personal access token with
repoandread:orgscopes
Setup
Three transport modes are available. Choose whichever fits your deployment:
Option A: stdio (local, recommended for desktop clients)
The server runs as a subprocess of the MCP client over stdin/stdout. No network port required.
Claude Desktop
~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
%APPDATA%\Claude\claude_desktop_config.json (Windows)
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}Claude Code
claude mcp add gha-intel -e GITHUB_TOKEN=ghp_your_token -- npx -y @barissozudogru/gha-intel-mcpCursor
~/.cursor/mcp.json
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}Windsurf
~/.codeium/windsurf/mcp_config.json
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}VS Code + Copilot
.vscode/mcp.json (workspace) or user settings
{
"servers": {
"gha-intel": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}Cline
Open Cline settings, navigate to MCP Servers, and add:
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}Continue.dev
~/.continue/config.yaml
mcpServers:
- name: gha-intel
command: npx
args:
- -y
- "@barissozudogru/gha-intel-mcp"
env:
GITHUB_TOKEN: ghp_your_tokenZed
~/.config/zed/settings.json
{
"context_servers": {
"gha-intel": {
"command": {
"path": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}
}JetBrains (IntelliJ, PyCharm, WebStorm, etc.)
Go to Settings > Tools > AI Assistant > MCP and add:
{
"mcpServers": {
"gha-intel": {
"command": "npx",
"args": ["-y", "@barissozudogru/gha-intel-mcp"],
"env": {
"GITHUB_TOKEN": "ghp_your_token"
}
}
}
}Option B: HTTP (remote or cloud clients)
Start the server in HTTP mode and point clients at the endpoint:
GITHUB_TOKEN=ghp_your_token npx @barissozudogru/gha-intel-mcp --http
# Server listens on http://0.0.0.0:3000/mcp
# Health check: http://localhost:3000/healthOr set via environment variable instead of the flag:
TRANSPORT=http PORT=3000 GITHUB_TOKEN=ghp_your_token npx @barissozudogru/gha-intel-mcpCursor (HTTP)
~/.cursor/mcp.json
{
"mcpServers": {
"gha-intel": {
"url": "http://localhost:3000/mcp"
}
}
}VS Code + Copilot (HTTP)
.vscode/mcp.json
{
"servers": {
"gha-intel": {
"type": "http",
"url": "http://localhost:3000/mcp"
}
}
}Windsurf (HTTP)
~/.codeium/windsurf/mcp_config.json
{
"mcpServers": {
"gha-intel": {
"serverUrl": "http://localhost:3000/mcp"
}
}
}Continue.dev (HTTP)
~/.continue/config.yaml
mcpServers:
- name: gha-intel
url: http://localhost:3000/mcpOption C: Docker
docker build -t gha-intel-mcp .
docker run -p 3000:3000 -e GITHUB_TOKEN=ghp_your_token gha-intel-mcpThe container starts in HTTP mode by default. Point your client at http://localhost:3000/mcp.
Tool Reference
list_workflow_performance
Fetch real run timing data and compute job-level statistics.
Parameter | Type | Required | Description |
| string | yes | GitHub owner (user or org) |
| string | yes | Repository name |
| string | yes | Workflow file name (e.g. |
| 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.
analyze_workflow_config
Parse and audit a workflow YAML for optimisation opportunities.
Parameter | Type | Required | Description |
| 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.
get_billing_usage
Retrieve billing and cache consumption data.
Parameter | Type | Required | Description |
| string | yes | GitHub username or organisation |
| 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.
Environment Variables
Variable | Required | Description |
| yes | GitHub personal access token. Requires |
| no | Set to |
| no | HTTP port when running in HTTP mode (default: |
License
MIT
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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