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gha-intel-mcp

gha-intel-mcp

gha-intel-mcp

npm version License: MIT

npm · Source · Issues

Inspect GitHub Actions run timing and review workflow configuration through MCP.

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

Reads repository cache usage and recent run timing. Account billing uses retired endpoints; see limitations below.

Related MCP server: copilot-usage-mcp

Requirements

  • Node.js >= 18 (uses native fetch)

  • A GitHub token with access to the repositories you want to inspect. See your token type and endpoint permissions before granting access.

Setup

Three 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)

{
  "mcpServers": {
    "gha-intel": {
      "command": "npx",
      "args": ["-y", "@barissozudogru/gha-intel-mcp"],
      "env": {
        "GITHUB_TOKEN": "ghp_your_token"
      }
    }
  }
}
claude mcp add gha-intel -e GITHUB_TOKEN=ghp_your_token -- npx -y @barissozudogru/gha-intel-mcp

~/.cursor/mcp.json

{
  "mcpServers": {
    "gha-intel": {
      "command": "npx",
      "args": ["-y", "@barissozudogru/gha-intel-mcp"],
      "env": {
        "GITHUB_TOKEN": "ghp_your_token"
      }
    }
  }
}

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "gha-intel": {
      "command": "npx",
      "args": ["-y", "@barissozudogru/gha-intel-mcp"],
      "env": {
        "GITHUB_TOKEN": "ghp_your_token"
      }
    }
  }
}

.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"
      }
    }
  }
}

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/config.yaml

mcpServers:
  - name: gha-intel
    command: npx
    args:
      - -y
      - "@barissozudogru/gha-intel-mcp"
    env:
      GITHUB_TOKEN: ghp_your_token

~/.config/zed/settings.json

{
  "context_servers": {
    "gha-intel": {
      "command": {
        "path": "npx",
        "args": ["-y", "@barissozudogru/gha-intel-mcp"],
        "env": {
          "GITHUB_TOKEN": "ghp_your_token"
        }
      }
    }
  }
}

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/mcp.json

{
  "mcpServers": {
    "gha-intel": {
      "url": "http://localhost:3000/mcp"
    }
  }
}

.vscode/mcp.json

{
  "servers": {
    "gha-intel": {
      "type": "http",
      "url": "http://localhost:3000/mcp"
    }
  }
}

~/.codeium/windsurf/mcp_config.json

{
  "mcpServers": {
    "gha-intel": {
      "serverUrl": "http://localhost:3000/mcp"
    }
  }
}

~/.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 repository cache consumption and recent run estimates. Account billing is currently limited by a retired API integration.

Parameter

Type

Required

Description

owner

string

yes

GitHub username or organisation

repo

string

no

Repository name for repo-scoped cache and run stats

Output: With repo supplied, cache usage and recent run timing where accessible. Account billing requests use retired GitHub endpoints and can fail. Existing cost estimates use a historical rate table and should not be treated as current charges.


Environment Variables

Variable

Required

Description

GITHUB_TOKEN

yes

GitHub personal access token. Access must match the requested repository and endpoint. Keep the token outside version control.

TRANSPORT

no

Set to http to enable HTTP mode (default: stdio).

PORT

no

HTTP port when running in HTTP mode (default: 3000).

Limitations and deployment

  • Account billing uses /settings/billing/actions, which GitHub retired in September 2025. Granting broader token scopes does not restore those endpoints. Repository cache and run timing requests use separate endpoints.

  • Current cost estimates use historical rates, and cache utilisation assumes a fixed 10 GB limit. Review account configuration before using either for capacity or budget decisions.

  • HTTP mode listens on all interfaces and does not implement client authentication. Keep it on a trusted network or place an authenticated gateway in front of it. The server uses its configured GitHub token for client requests.

  • Timing statistics describe the fetched runs, rather than predicting a future run.

Development and support

Report problems through GitHub issues. See CONTRIBUTING.md for the contribution workflow.

To build and test a source checkout with Node.js 22:

npm ci
npm test
npm run build

The default branch can contain changes that have not yet been published to npm.

License

MIT

Available Tools

3 tools
analyze_workflow_configAnalyze Workflow ConfigA

Parse a GitHub Actions workflow YAML (provided as a string) and identify optimization opportunities: missing caches, matrix strategy, concurrency controls, slow dependency installs, artifact handling, and more.

Inputs: workflow_content (required).

get_billing_usageGet Billing UsageA

Retrieve GitHub Actions billing and cache usage statistics for an owner (user or org), optionally scoped to a specific repository.

Inputs: owner (required), repo.

list_workflow_performanceList Workflow PerformanceA

Fetch the last N workflow runs and compute job-level timing statistics (avg, min, max, p95) across those runs. Useful for identifying slow jobs and trends.

Inputs: repo (required), owner (required), workflow_id (required), count.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

    TDQS

    A3.9/5.0

    Scored across 3 tools

    Disambiguation5/5

    Each tool addresses a clearly distinct aspect: runtime performance metrics, static configuration analysis, and billing/cost usage. There is no overlap in purpose or data source, so an agent can reliably select the right tool.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern: list_workflow_performance, analyze_workflow_config, get_billing_usage. The verbs (list, analyze, get) and nouns clearly indicate the action and subject, maintaining uniformity across the set.

    Tool Count4/5

    With only 3 tools, the server is minimally scoped but each tool serves a distinct, valuable function within the GitHub Actions intel domain. The count is within the typical 3-15 range, though one could argue it's slightly on the lower end for comprehensive coverage.

    Completeness3/5

    The tools cover performance metrics, config analysis, and billing, but there's a notable gap: no tool to fetch the workflow YAML directly, forcing an external step for configuration analysis. Additionally, lifecycle operations like listing workflows or runs are missing, though performance stats partially address that.

    Maintenance

    ActivityActive
    ResponsivenessNo recent community issues

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