@barissozudogru/gha-intel-mcp

An MCP server for GitHub Actions workflow timing analysis, configuration auditing, and billing insights.

Tools

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.

Requirements

• Node.js >= 18 (uses native fetch)
• A GitHub personal access token with repo and read:org scopes

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-mcp

Cursor

~/.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_token

Zed

~/.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/health

Or set via environment variable instead of the flag:

TRANSPORT=http PORT=3000 GITHUB_TOKEN=ghp_your_token npx @barissozudogru/gha-intel-mcp

Cursor (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/mcp

Option C: Docker

docker build -t gha-intel-mcp .
docker run -p 3000:3000 -e GITHUB_TOKEN=ghp_your_token gha-intel-mcp

The 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
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.

analyze_workflow_config

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.

get_billing_usage

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.

Environment Variables

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).

License

MIT