mcp-jenkins

MCP Jenkins

PyPI Version PyPI - Downloads License

The Model Context Protocol (MCP) is an open-source implementation that bridges Jenkins with AI language models following Anthropic's MCP specification. This project enables secure, contextual AI interactions with Jenkins tools while maintaining data privacy and security.

Cursor Demo

cursor demo

Setup Guide

Installation

Choose one of these installation methods:

# Using uv (recommended)
pip install uv
uvx mcp-jenkins

# Using pip
pip install mcp-jenkins

# Using Smithery
npx -y @smithery/cli@latest install @lanbaoshen/mcp-jenkins --client claude

Configuration and Usage

Cursor

Open Cursor Settings
Navigate to MCP
Click + Add new global MCP server

This will create or edit the ~/.cursor/mcp.json file with your MCP server configuration.

{
  "mcpServers": {
    "mcp-jenkins": {
      "command": "uvx",
      "args": [
        "mcp-jenkins",
        "--jenkins-url=xxx",
        "--jenkins-username=xxx",
        "--jenkins-password=xxx"
      ]
    }
  }
}

line arguments

# Stdio Mode
uvx mcp-jenkins --jenkins-url xxx --jenkins-username xxx --jenkins-password xxx

# SSE Mode
uvx mcp-jenkins --jenkins-url xxx --jenkins-username xxx --jenkins-password xxx --transport sse --port 9887

AutoGen

Install autogen:

pip install "autogen-ext[azure,ollama,openai,mcp]" autogen-chat

Run python scripts:

import asyncio

from autogen_ext.tools.mcp import StdioMcpToolAdapter, StdioServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.ui import Console
from autogen_core import CancellationToken


async def main() -> None:
    # Create server params for the remote MCP service
    server_params = StdioServerParams(
        command='uvx',
        args=[
            'mcp-jenkins',
            '--jenkins-username',
            'xxx',
            '--jenkins-password',
            'xxx',
            '--jenkins-url',
            'xxx'
        ],
    )

    # Get the translation tool from the server
    adapter = await StdioMcpToolAdapter.from_server_params(server_params, 'get_all_jobs')

    # Create an agent that can use the translation tool
    agent = AssistantAgent(
        name='jenkins_assistant',
        model_client=[Replace_with_your_model_client],
        tools=[adapter],
    )

    # Let the agent translate some text
    await Console(
        agent.run_stream(task='Get all jobs', cancellation_token=CancellationToken())
    )


if __name__ == "__main__":
    asyncio.run(main())

Available Tools

Tool	Description
get_all_jobs	Get all jobs
get_job_config	Get job config
search_jobs	Search job by specific field
get_running_builds	Get running builds
get_build_info	Get build info
get_job_info	Get job info
build_job	Build a job with param
get_build_logs	Get build logs
get_all_nodes	Get nodes
get_node_config	Get the config of node
get_all_queue_items	Get all queue items
get_queue_item	Get queue item info
cancel_queue_item	Cancel queue item

Development & Debugging

# Using MCP Inspector
# For installed package
npx @modelcontextprotocol/inspector uvx mcp-jenkins --jenkins-url xxx --jenkins-username xxx --jenkins-password xxx

# For local development version
npx @modelcontextprotocol/inspector uv --directory /path/to/your/mcp-jenkins run mcp-jenkins --jenkins-url xxx --jenkins-username xxx --jenkins-password xxx

Pre-Commit Hook

# Install Dependency
uv sync --all-extras --dev
pre-commit install

# Manually execute
pre-commit run --all-files

UT

# Install Dependency
uv sync --all-extras --dev

# Execute UT
uv run pytest --cov=mcp_jenkins

License

Licensed under MIT - see LICENSE file. This is not an official Jenkins product.

This server cannot be installed

security - not tested

license - permissive license

quality - not tested

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

The Model Context Protocol (MCP) Jenkins integration is an open-source implementation that bridges Jenkins with AI language models following Anthropic's MCP specification. This project enables secure, contextual AI interactions with Jenkins tools while maintaining data privacy and security.

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