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MCP Connector

Manage Jenkins Builds via MCP

Minimal MCP server for triggering and monitoring Jenkins build tasks, configured via a simple .env file.

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Works with jenkinsopenai
jasonkylelol
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60
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out of 100
Updated 10 months ago
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Version 1.0.0
Models
claude
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Why it matters

Automate the creation and management of Jenkins build jobs using the Model Context Protocol (MCP). This asset allows for programmatic control over your CI/CD pipeline, enabling dynamic job setup and monitoring.

Outcomes

What it gets done

01

Create new Jenkins build jobs programmatically.

02

Monitor the execution status of Jenkins builds.

03

Retrieve build results after job completion.

04

Integrate with OpenAI for potential intelligent job configuration.

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/vb-jenkins | bash

Capabilities

Tools your agent gets

create_jenkins_job

Create a new Jenkins build job

monitor_build_execution

Monitor the execution status of a Jenkins build job

retrieve_build_results

Retrieve build results upon job completion

Overview

Jenkins MCP Server

jenkins-mcp-server is a minimal MCP server that triggers a configured Jenkins build task and reports its result via a client script. Use it for a simple, self-hosted way to trigger and monitor a Jenkins build; it doesn't cover broader Jenkins job or pipeline management.

What it does

jenkins-mcp-server is an MCP server for running Jenkins build tasks. It's configured through a .env file specifying the Jenkins URL, user, and API token, plus an OpenAI-compatible API base URL, model, and API key. Once configured, running the included client triggers a Jenkins build task and reports back the result once the job completes.

When to use - and when NOT to

Use this connector when you want to trigger a Jenkins build job and get its result reported back through an MCP client, in a simple self-hosted setup.

Do not expect a broad Jenkins API surface here - the description covers running a build task and getting its result, not managing jobs, viewing pipelines, or other Jenkins administration features.

Inputs and outputs

Configuration inputs are the Jenkins URL, username, and API token (set in .env), plus the MCP server port (set in server_config.json). Running the client triggers a build; the output is the build result once the task finishes.

Capabilities

  • Trigger a Jenkins build task and report its result once complete

How to install

Configure .env with your Jenkins URL, user, and token (plus the OpenAI-compatible API settings), and set the MCP server port in server_config.json. Then:

python3 mcp_server.py

Run a build task with the included client:

python3 mcp_client.py

Who it's for

Developers who want a simple, self-hosted way to trigger Jenkins builds and get results through an MCP-based client.

Source README

jenkins-mcp-server

mcp server for jenkins build tasks

usage

  1. config environment
vim .env # config jenkins url, user, token and openai api base url, model, api key.

make sure to edit server_config.json for your own mcp server port

  1. launch server
python3 mcp_server.py # modify to config your own mcp server port
  1. run a jenkins build task
python3 mcp_client.py

then you will see the build task is running in jenkins, when the task is done, the client will show the result.

FAQ

Common questions

Discussion

Questions & comments · 0

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