MCP GITHUB ENTERPRISE 🌉

A Model Context Protocol (MCP) server that lets AI agents (Claude, ChatGPT, etc.) query your GitHub Enterprise license data. Securely fetch license summaries, per-user details, org memberships, and enterprise roles via the /consumed-licenses endpoint.

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📊 Capabilities & Example Prompts

• License Summary
  • "Show me our GitHub Enterprise license summary"
  • "How many licenses are we currently using?"

• Detailed License Usage
  • "List all consumed GitHub licenses"
  • "Do we have any unused GitHub licenses?"

• User Lookup
  • "What GitHub orgs does johndoe belong to?"
  • "What enterprise roles does johndoe have?"
  • "Is johndoe an owner in our enterprise?"
  • "Get detailed info about johndoe"
  • "Does johndoe have 2FA enabled?"

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🌟 Features

• License Analytics: Total vs. consumed seats
• User Lookup: Org memberships, roles, 2FA, SAML ID
• Pagination: Handles large enterprises automatically
• Dual Transports: stdio for direct MCP, SSE for HTTP
• Kubernetes-Ready: Deploy on EKS/GKE or any K8s cluster

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📋 Prerequisites

• Python 3.9+
• GitHub PAT with read:enterprise / license scopes
• GitHub Enterprise Cloud tenant

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🚀 Quick Start

1. Clone & Install

git clone https://github.com/vipink1203/mcp-github-enterprise.git
cd mcp-github-enterprise
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

2. Configure

cp .env.example .env
# Edit .env: set GITHUB_TOKEN and GITHUB_ENTERPRISE_URL

3. Run

stdio transport

export TRANSPORT=stdio
python main.py

SSE transport

export TRANSPORT=sse PORT=8050
python main.py

🐳 Docker & n8n

Add this service to your docker-compose.yml alongside n8n:

services:
  github-mcp:
    image: ghcr.io/vipink1203/mcp-github-enterprise:latest
    environment:
      - GITHUB_TOKEN=${GITHUB_TOKEN}
      - GITHUB_ENTERPRISE_URL=${GITHUB_ENTERPRISE_URL}
      - TRANSPORT=sse
      - PORT=8050
    ports:
      - "8050:8050"
    restart: unless-stopped
    networks:
      - n8n-network

In n8n's UI, enable the MCP client: - Settings → Credentials → New Credential - Choose MCP Client API, set URL to http://github-mcp:8050/sse

🔌 Client Configuration

### Claude Desktop / Windsurf / Cursor

Add this configuration to your Claude Desktop settings:

json { "mcpServers": { "github-ent": { "command": "/path/to/your/venv/python", "args": ["/path/to/main.py"], "env": { "GITHUB_TOKEN": "", "GITHUB_ENTERPRISE_URL": "https://api.github.com/enterprises/{enterprise_name}", "TRANSPORT": "stdio" } } }

### SSE Configuration

json { "mcpServers": { "github": { "transport": "sse", "url": "http://localhost:8050/sse" } } }

## 📊 Example Use Cases

• Enterprise User Management: Automate user onboarding and offboarding
• License Monitoring: Get alerts when licenses are close to expiration
• Organization Analysis: Analyze organization structures and relationships
• User Access Auditing: Track user permissions and access levels
• AI-powered GitHub Insights: Let AI analyze your enterprise GitHub data

🔌 MCP Tools & Resources

Tools

Name	Description
list_consumed_licenses	Summarize licenses, optionally include users
get_user_organizations	List a user's GitHub org memberships
get_user_enterprise_roles	List a user's enterprise roles
get_user_detail	Full license detail for a user

Resources

URI	Description
github://consumed-licenses/{dummy}	Full license usage + user details
github://user/{username}/roles	Org & enterprise roles for a user

## 🔒 Security Considerations

• Store your GitHub token securely
• Use appropriate scopes for your GitHub token
• For production, consider using AWS Secrets Manager or similar
• Implement network policies in Kubernetes deployments

## 🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

## 📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

## 🙏 Acknowledgements

• Model Context Protocol for the Python SDK
• MCP-Mem0 for providing a great template structure
• GitHub API for the comprehensive API

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Built with ❤️ for seamless AI ↔️ GitHub Enterprise integration.