avisangle/jenkins-mcp-server

Overview

An MCP server that connects AI agents to a Jenkins instance. It enables triggering jobs, checking build statuses, and managing Jenkins operations through the Model Context Protocol.

Best for

Best for
Developers who want to control Jenkins pipelines through an AI agent

Use cases

• Trigger Jenkins jobs from an AI assistant
• Check build status and logs without opening the Jenkins UI
• Automate CI/CD workflows via natural language commands

How to use

Install

pip install -e .

Tools exposed

• trigger_job
• get_job_info
• list_jobs
• search_jobs
• search_and_trigger
• get_folder_info
• get_build_status
• get_console_log
• summarize_build_log
• get_pipeline_status
• list_build_artifacts
• download_build_artifact
• search_build_artifacts

Tested with

Claude Desktop

Example client config

{\n  "mcpServers": {\n    "jenkins": {\n      "command": "node",\n      "args": [\n        "/path/to/jenkins-mcp-server/bin/jenkins-mcp.js"\n      ],\n      "env": {\n        "JENKINS_URL": "http://your-jenkins-server:8080",\n        "JENKINS_USER": "your-username",\n        "JENKINS_API_TOKEN": "your-api-token"\n      }\n    }\n  }\n}

Notes

An MCP server that connects AI agents to a Jenkins instance. It enables triggering jobs, checking build statuses, and managing Jenkins operations through the Model Context Protocol.

2 stars on GitHub. Last updated 2026-02-13.

Use cases

• Trigger Jenkins jobs from an AI assistant
• Check build status and logs without opening the Jenkins UI
• Automate CI/CD workflows via natural language commands

Pros

• Simple Python implementation easy to extend
• Direct integration with Jenkins for common operations
• Works with any MCP-compatible client

Cons

• Very early stage with only 2 GitHub stars
• Limited to basic job triggering and status checks
• Requires manual setup and Jenkins API credentials

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.