mcp-jenkins and mcp-jfrog
These are complements that operate at different stages of a CI/CD pipeline: Jenkins MCP handles workflow orchestration and execution, while JFrog MCP manages artifact repositories and build lifecycle tracking downstream.
About mcp-jenkins
lanbaoshen/mcp-jenkins
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.
This project integrates Jenkins, a popular automation server, with AI language models like those from Anthropic. It allows developers to use natural language to interact with their Jenkins instances, securely fetching information about jobs, builds, and nodes, or even triggering actions. It takes natural language queries and Jenkins credentials as input, providing structured Jenkins data or executing commands as output. This tool is for software developers and DevOps engineers who manage continuous integration/continuous delivery (CI/CD) pipelines using Jenkins.
About mcp-jfrog
jfrog/mcp-jfrog
Model Context Protocol (MCP) Server for the JFrog Platform API, enabling repository management, build tracking, release lifecycle management, and more.
This tool helps DevOps and software release managers orchestrate software components within the JFrog Platform. It takes in configurations for repositories, build pipelines, and access controls, and outputs managed repositories, tracked builds, and organized project environments. It's designed for professionals who manage the lifecycle of software artifacts.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work