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Github MCP Bridge
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Github MCP Bridge

A GitHub Enterprise data query service based on the MCP protocol that allows AI agents to securely obtain enterprise license usage, user permissions, and other data through the API. It supports dual - transport mode and Kubernetes deployment.
Developer toolsVersion control#GitHub management#Enterprise permissions#AI integration#Data query.Python
2 points
5.0K
Open Site

Overview

Content Details

Alternatives

What is MCP GitHub Enterprise?

This is a server based on the Model Context Protocol (MCP) that allows AI assistants (such as Claude, ChatGPT, etc.) to securely query your GitHub Enterprise license data. It provides information such as license usage, user permissions, and organizational structure through a standardized interface.

How to use MCP GitHub Enterprise?

You can query GitHub Enterprise data through simple natural language commands, such as 'Show our license usage' or 'Query the permissions of user johndoe'. The system supports multiple deployment methods, including local operation and Docker container deployment.

Use cases

It is suitable for scenarios such as enterprise IT management, license monitoring, user permission auditing, and organizational structure analysis. It is especially suitable for administrators who need to regularly check the usage of GitHub Enterprise.

Main features

License analysis
Provides a comparative analysis of the total number of licenses and the number of used licenses to help you understand license usage.
User query
Queries information such as the user's affiliated organization, role permissions, 2FA status, and SAML ID.
Automatic pagination
Automatically handles data pagination for large enterprises without manual operation.
Dual transport mode
Supports two communication methods: direct stdio interaction and SSE HTTP streaming transmission.
Advantages
Simplifies the process of querying GitHub Enterprise data
Supports natural language interaction, reducing the usage threshold
Can be integrated into existing AI assistants and workflows
Provides detailed user and organizational permission information
Limitations
Requires GitHub Enterprise administrator permissions
Depends on the Python 3.9+ environment
There may be delays in querying large - scale enterprise data

How to use

Environment preparation
Ensure that Python 3.9 or a higher version is installed, and prepare a GitHub personal access token (PAT) with appropriate permissions.
Clone the repository
Clone the project code from GitHub to the local machine.
Install dependencies
Create a virtual environment and install the required dependencies.
Configure environment variables
Copy the example environment file and fill in your GitHub credentials and enterprise URL.
Run the service
Select the transport mode and start the service.

Usage examples

License usage monitoring
Regularly check the enterprise license usage to ensure that the limit is not exceeded.
User permission auditing
Check the permissions and organizational affiliations of a specific user in the enterprise.
Security compliance check
Verify whether the user has enabled two - factor authentication (2FA).

Frequently Asked Questions

What permissions are required for the GitHub token?
Which GitHub versions are supported?
How to handle data for large enterprises?
Can it be deployed on Kubernetes?

Related resources

Model Context Protocol SDK
Python SDK documentation for the MCP protocol
GitHub Enterprise API documentation
Official GitHub REST API reference
Example deployment configuration
Examples of Docker and Kubernetes deployment

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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