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MCP Server PR Agent

MCP Server PR Agent

Local
github.com/dux-simformAI & Agents0Updated 76w ago

About MCP Server PR Agent

MCP Server PR Agent is an MCP-framework server for managing and analyzing pull requests, intended for teams working with repository PRs. Its setup uses Git provider details, OpenAI API credentials, and a GitHub user token.

Key features

  1. 01Manage pull requests
  2. 02Analyze pull requests
  3. 03Configure the server with environment variables

Use cases

  1. 01Manage repository pull requests
  2. 02Analyze pull requests

MCP support

This server uses the MCP framework to manage and analyze pull requests; the README does not specify the tools exposed to MCP clients.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Server PR Agent

This project provides a server for managing and analyzing pull requests using the MCP framework.

Setup

  1. Clone the repository:

    git clone <repository-url>
    cd mcp-server-pr-agent
    
  2. Install dependencies:

    pip install -r requirements.txt
    
  3. Create a .env file: Copy the .env.sample file and fill in the required values:

    cp .env.sample .env
    
  4. Run the server:

    python server.py
    

Environment Variables

The .env file should contain the following variables:

  • GIT_PROVIDER: The Git provider (e.g., github).
  • OPENAI_API_KEY: Your OpenAI API key.
  • OPENAI_API_TYPE: The type of OpenAI API (e.g., azure).
  • OPENAI_API_VERSION: The version of the OpenAI API.
  • OPENAI_API_BASE: The base URL for the OpenAI API.
  • OPENAI_API_DEPLOYMENT: The deployment ID for the OpenAI API.
  • GITHUB_USER_TOKEN: Your GitHub user token.

Refer to .env.sample for an example configuration.

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