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Jenkins MCP Server

by truxt-ai

A Model Context Protocol (MCP) server that provides access to Jenkins data and functionality through a standardized interface for LLMs. It allows Large Language Models to access Jenkins job data and execute Jenkins-related operations.

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Jenkins MCP Server

A Model Context Protocol (MCP) server that provides access to Jenkins data and functionality through a standardized interface for LLMs.

Overview

This project implements an MCP server that connects to Jenkins instances, allowing Large Language Models to:

  • Access Jenkins job data as resources
  • Execute Jenkins-related operations through tools
  • Utilize predefined prompts for common Jenkins interactions

Installation

Prerequisites

  • Python 3.8+
  • Access to a Jenkins instance

Setting up with uv

We recommend using uv for managing Python environments:

# Install uv if you haven't already
curl -sSf https://install.ultraviolet.dev | sh

# Create a new project
uv init jenkins-mcp-server
cd jenkins-mcp-server

# Add dependencies
uv add "mcp[cli]"
uv add python-jenkins

Environment Variables

Create a .env file with your Jenkins configuration:

# Create .env file
cat > .env << EOL
JENKINS_URL=https://your-jenkins-instance.com
JENKINS_USERNAME=your_username
JENKINS_API_TOKEN=your_api_token
EOL

# Load environment variables in your shell
source .env

Usage

Running the server

Start the server in development mode with:

uv run mcp dev server.py

Features

  • Resources: Access Jenkins job configurations, build history, and status information
  • Tools: Trigger builds, update job configurations, and manage Jenkins tasks
  • Prompts: Pre-defined interaction patterns for common Jenkins operations

Contributing

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

License

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