"Guidelines for Interfacing with Jenkins" matching MCP servers:

MCP server that connects AI agents to Jenkins, supporting stdio and HTTP transports with tools for jobs, builds, logs, and queue management.

MCP server for Jenkins (with optional GitLab integration) that lets AI assistants list jobs, trigger and track deployments, fetch build logs, and verify whether tickets are deployed, without touching the Jenkins UI.

Provides design system guidelines and component documentation to Cursor Desktop, enabling accurate advice on UI components, patterns, and best practices.

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.

Provides AI assistants with full access to Jenkins CI/CD systems, enabling querying, managing, and controlling Jenkins jobs, builds, nodes, and queues through natural language.

MCP server that triggers Jenkins automation jobs and returns their results, with an action registry, parameter validation, and credential redaction.

Jenkins HOT/QAT deployment assistant MCP server that enables agents to locate jobs, check branches, perform safe deployments with overwrite protection, and rollback deployments via natural language.

Enables triggering Jenkins builds from IDEs with Slack notifications, requiring only a one-time login.

Exposes a Jenkins controller's REST API to MCP-compatible clients, enabling job management, build triggering, and log retrieval through natural language.

A local MCP server for Jenkins that provides 17 tools to interact with Jenkins jobs, builds, logs, SCM, and test results via REST API, no plugin required.

A Jenkins MCP server with 37 tools for managing jobs, builds, nodes, views, and CI/CD workflows.

Enables AI assistants to interact with Jenkins CI/CD servers, including checking build status, triggering builds, and retrieving build logs.

A comprehensive MCP server with 53 tools for managing Jenkins CI/CD operations, including job, build, pipeline, node, credential, and plugin management, enabling AI assistants to control Jenkins servers through natural language.

Provides code review and guideline loading based on Andrej Karpathy's coding principles, helping LLMs avoid common pitfalls like over-engineering and unnecessary changes.

Enables interaction with Jenkins servers through HTTP APIs, allowing users to list jobs, trigger builds, view logs, and manage configurations without requiring plugins or admin access.

Converts Jenkins declarative pipelines into GitHub Actions workflow YAML files, facilitating migration from Jenkins to GitHub Actions CI/CD.

An MCP server that enables LLMs to automate browser interactions using Playwright to fetch real-time Israeli weather data.

Implements a secure MCP server with API Key and JWT authentication, providing tools like echo, login, secure_action, and admin_action. Includes MCP Inspector integration for testing and debugging.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.

50 tools and 400 functions for working with Excel/.xlsx spreadsheets — read/write, recalculate formulas, diff, repair broken references, and audit. Built for AI agents.