Jenkins MCP Proxy

Model Context Protocol Integrated with Jenkins

Overview

This project demonstrates how to integrate Model Context Protocol (MCP) with Jenkins to enable intelligent, automated interaction with Jenkins pipelines. The MCP proxy acts as a middleware layer that:

• Exposes Jenkins capabilities via structured APIs
• Enables AI or external systems to interact with Jenkins
• Standardizes communication using MCP principles

Why MCP with Jenkins? By integrating MCP: - AI agents can trigger and monitor Jenkins jobs - CI/CD pipelines can be controlled programmatically - Build insights (status/logs) become easily accessible - External systems can integrate seamlessly

Prerequisites:-

Ensure the following tools are installed:

• Python3 3.11.15
• Docker
• Docker Compose
• Git

Project Structure

1) functions.py

Core logic layer for Jenkins interaction Handles:

• Job triggering
• Build status retrieval
• Logs fetching
• Acts as a service layer between proxy and Jenkins

2) proxy_mcp.py

Main entry point of MCP proxy

• Handles incoming requests
• Routes calls to functions.py
• Formats MCP-compatible responses

3) remote-test.py

Test script to validate MCP endpoints

• Simulates remote API calls
• Useful for debugging

4) requirements.txt

Lists Python dependencies

• Used for container build and local setup

5) Dockerfile

Builds container image

• Installs dependencies and runtime environment

6) docker-compose.yaml

Defines services and configurations

• Manages container orchestration

7) .env

Stores environment-specific configurations:

• Jenkins URL
• Credentials / API tokens
• Other runtime configs

Installation & Setup

- Clone Repository

'git clone https://github.com/ravi11196/Model-Context-Protocol-Integrated-with-Jenkins.git'

- Navigate to Directory

'cd Model-Context-Protocol-Integrated-with-Jenkins'

- Build Docker Image

'docker build --no-cache -t jenkins-mcp-proxy .'

- Start Services

'docker compose up -d

Verification & Health Check

- Check Running Containers

'docker ps'

- View Logs

'docker compose logs -f' or

'docker logs <container_name>'

- Health Validation

Verify the following in logs:

• MCP proxy server started successfully
• Jenkins connection established
• No authentication errors
• Health check endpoint responding (if configured)

Testing

Run the test script:

'python3 remote-test.py'

This will:

• Send test requests to MCP proxy
• Validate responses
• Confirm Jenkins integration

Use Cases

• AI-powered DevOps automation
• Remote Jenkins orchestration
• Build monitoring & reporting
• Integration with LLM-based tools