What is MCP Jenkins Server and what does it do?
It is an MCP server that exposes Jenkins functions as tools, allowing MCP clients (such as AI assistants) to query Jenkins server info, list jobs, inspect builds, manage views, and trigger builds.
MCP Jenkins Server
@lieee1995
基本信息
关于 MCP Jenkins Server
暂无概览
MCP Jenkins Server 配置
MCP Jenkins Server 工具
工具列表暂未提供
当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。
工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。
概览
What is MCP Jenkins Server?
MCP Jenkins Server is a Model Context Protocol server that integrates with Jenkins, providing tools to interact with Jenkins jobs, builds, views, and server information. It is intended for developers using MCP-compatible clients who need programmatic access to Jenkins automation infrastructure.
How to use MCP Jenkins Server?
Configuration requires a .env file with JENKINS_URL, JENKINS_USER, and JENKINS_TOKEN (or alternate env variables JENKINS_USERNAME and JENKINS_PASSWORD in CLI setup). The server can be launched via uv with the provided JSON MCP configuration. Python 3.10+ and a Jenkins server with API access are required. Example client code: from mcp.client import Client; client = Client("http://localhost:8000"); response = client.call_tool("list_jobs").
Key features of MCP Jenkins Server
- Retrieve Jenkins server information.
- List and inspect Jenkins jobs.
- Get build details and console output.
- Manage and list Jenkins views.
- Trigger specific job builds.
Use cases of MCP Jenkins Server
- Automating CI/CD status checks from an AI assistant.
- Fetching build logs for debugging without opening the Jenkins UI.
- Triggering a demo job (e.g., “LLM_Demo”) with user parameters.
- Listing all jobs in a Jenkins view for project overview.
- Monitoring build history for a specific job.
常见问题
How do I configure MCP Jenkins Server?
Create a `.env` file with `JENKINS_URL`, `JENKINS_USER`, and `JENKINS_TOKEN`. Alternatively, set environment variables `JENKINS_URL`, `JENKINS_USERNAME`, and `JENKINS_PASSWORD` in the MCP client configuration.
What are the system requirements?
Python 3.10 or later, a Jenkins server with API access enabled, and a valid Jenkins API token (or username/password) for authentication.
What tools are available?
The server provides seven tools: `get_jenkins_info`, `list_jobs`, `get_job_info` (parameter: `job_name`), `get_build_info` (parameters: `job_name`, `build_number`), `get_build_console_output` (parameters: `job_name`, `build_number`), `get_views`, and `trriger_llm_demo_job_build` (parameter: `user`).
Which transport or client setup is supported?
The example client uses an HTTP endpoint (`http://localhost:8000`). The CLI configuration launches the server using `uv` with the `server.py` script, which uses stdio MCP transport. Both approaches are described in the README.
其他 分类下的更多 MCP 服务器
Glasswarp
GlasswarpSee and control a real Windows PC you own — from any MCP client, locally or remotely. Observe (UIA + screenshots), click/type/drag/scroll, launch apps, owner Live View. BYOH: your machine, your key.
FastMCP v2 🚀
jlowin🚀 The fast, Pythonic way to build MCP servers and clients.
26.0K
Blender
ahujasidOpen-source MCP to use Blender with any LLM
23.6K
Activepieces
activepiecesAI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
23.2K
Hindsight
vectorize-ioHindsight: Agent Memory That Learns
50.4K
评论