About MCP GITHUB ENTERPRISE π
MCP server for GitHub Enterprise Cloud that lets AI agents inspect license usage and user access details. It supports stdio and SSE transports and handles pagination for large enterprises.
Key features
- 01License totals and consumption
- 02User organizations and roles
- 03User details including 2FA and SAML ID
- 04Automatic pagination
- 05stdio and SSE transports
Use cases
- 01Review enterprise license use
- 02Check a user's organization access
- 03Audit enterprise roles and 2FA
MCP support
Exposes license and user lookup tools, plus license and role resources, to MCP clients over stdio or SSE.
Configuration
Local server config is the same for every client. Copy it into your clientβs MCP config file.
We havenβt collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEMCP GITHUB ENTERPRISE π
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.
π Capabilities & Example Prompts
-
License Summary
β’"Show me our GitHub Enterprise license summary"
β’"How many licenses are we currently using?" -
Detailed License Usage
β’"List all consumed GitHub licenses"
β’"Do we have any unused GitHub licenses?" -
User Lookup
β’"What GitHub orgs does johndoe belong to?"
β’"What enterprise roles does johndoe have?"
β’"Is johndoe an owner in our enterprise?"
β’"Get detailed info about johndoe"
β’"Does johndoe have 2FA enabled?"
π 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
π Prerequisites
- Python 3.9+
- GitHub PAT with
read:enterprise/ license scopes - GitHub Enterprise Cloud tenant
π 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
π³ 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 β Credentials β New Credential
- Choose MCP Client API, set URL to http://github-mcp:8050/sse
π Client Configuration
Claude Desktop / Windsurf / Cursor
Add this configuration to your Claude Desktop settings:
{
"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
{
"mcpServers": {
"github": {
"transport": "sse",
"url": "http://localhost:8050/sse"
}
}
}
π 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
π 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 |
π 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
π€ Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature) - Commit your changes (
git commit -m 'Add some amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
π License
This project is licensed under the MIT License - see the LICENSE file for details.
π Acknowledgements
- Model Context Protocol for the Python SDK
- MCP-Mem0 for providing a great template structure
- GitHub API for the comprehensive API
Built with β€οΈ for seamless AI βοΈ GitHub Enterprise integration.
Comments
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From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.