GitHub Enterprise MCP Server

What does “GitHub Enterprise” MCP Server do?

The GitHub Enterprise MCP Server acts as an integration layer between AI assistants and GitHub Enterprise repositories. It enables seamless connectivity for AI tools to interact with GitHub Enterprise data, allowing developers to enhance their workflows by automating tasks such as repository management, issue tracking, and pull request operations. By serving as a bridge between AI clients and GitHub Enterprise, this MCP server empowers assistants to query repositories, manage files, and interact with organizational data more effectively. This connectivity is particularly valuable for enterprises seeking to streamline development, improve codebase insights, and automate repetitive tasks through AI-driven interactions with their private GitHub infrastructure.

List of Prompts

The repository does not explicitly list any prompt templates. No information available.

List of Resources

The repository does not explicitly document core MCP resources. No information available.

List of Tools

The repository does not provide a direct list of tools in server.py. No information available.

Use Cases of this MCP Server

• Repository Automation
  Enable AI assistants to automate repository management tasks, such as creating, updating, and deleting repositories within GitHub Enterprise.

• Issue Tracking
  Allow developers to interact with issues, including creating, closing, and commenting on issues, directly through AI-powered workflows.

• Pull Request Operations
  Streamline code review processes by automating pull request creation, merging, and review notifications within enterprise environments.

• Enterprise Data Insights
  Facilitate the extraction and summarization of organizational codebase statistics and activity for project managers and leads.

How to set it up

Windsurf

1. Ensure prerequisites (e.g., Node.js) are installed.
2. Locate your Windsurf configuration file.
3. Add the GitHub Enterprise MCP Server with the following JSON snippet:

   {
     "mcpServers": {
       "github-enterprise-mcp": {
         "command": "npx",
         "args": ["@containerelic/github-enterprise-mcp@latest"]
       }
     }
   }
   

4. Save your configuration and restart Windsurf.
5. Verify the MCP server is running.

Securing API Keys:

{
  "mcpServers": {
    "github-enterprise-mcp": {
      "command": "npx",
      "args": ["@containerelic/github-enterprise-mcp@latest"],
      "env": {
        "GITHUB_TOKEN": "${GITHUB_TOKEN}"
      },
      "inputs": {
        "org": "your-org"
      }
    }
  }
}

Claude

1. Ensure Node.js is installed.
2. Open or create the Claude configuration file.
3. Insert the MCP server configuration:

   {
     "mcpServers": {
       "github-enterprise-mcp": {
         "command": "npx",
         "args": ["@containerelic/github-enterprise-mcp@latest"]
       }
     }
   }
   

4. Save the file and restart Claude.
5. Confirm connectivity to the MCP server.

Cursor

1. Install prerequisites (Node.js).
2. Open cursor_mcp.json or create one if it doesn’t exist.
3. Add the following configuration:

   {
     "mcpServers": {
       "github-enterprise-mcp": {
         "command": "npx",
         "args": ["@containerelic/github-enterprise-mcp@latest"]
       }
     }
   }
   

4. Save and restart Cursor.
5. Check the MCP server status.

Cline

1. Verify Node.js is installed.
2. Find the Cline configuration JSON file.
3. Append or create the MCP server entry:

   {
     "mcpServers": {
       "github-enterprise-mcp": {
         "command": "npx",
         "args": ["@containerelic/github-enterprise-mcp@latest"]
       }
     }
   }
   

4. Save changes and restart Cline.
5. Validate the MCP server is active.

Note:
Always secure API tokens using environment variables. Example:

{
  "mcpServers": {
    "github-enterprise-mcp": {
      "command": "npx",
      "args": ["@containerelic/github-enterprise-mcp@latest"],
      "env": {
        "GITHUB_TOKEN": "${GITHUB_TOKEN}"
      },
      "inputs": {
        "org": "your-org"
      }
    }
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "github-enterprise-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “github-enterprise-mcp” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Roots support: ⛔ Not documented
Sampling support: ⛔ Not documented

Based on the available documentation, the GitHub Enterprise MCP Server provides basic integration information and setup instructions, but lacks explicit documentation for prompts, resources, and tools. Therefore, its score is moderate for enterprise use but limited by missing technical detail.

MCP Score