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.
Exposes 20+ Jenkins operations as MCP tools—from querying jobs and builds to triggering builds and retrieving console output—while supporting multiple transport protocols (stdio, SSE, streamable-http) for integration with IDEs like VSCode and JetBrains. Implements optional read-only mode, configurable SSL verification, and session-based Jenkins client management to balance flexibility with security constraints in different deployment scenarios.
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.
Implements 16+ MCP tools spanning artifact lifecycle management (AQL querying, repository CRUD), build and runtime visibility, and Xray vulnerability scanning—exposing JFrog's multi-product platform through a standardized protocol. Built as a TypeScript MCP server that communicates via stdio transport with AI clients, translating natural language requests into authenticated REST API calls against Artifactory, Xray, and other JFrog services. Integrates with Claude and other MCP-compatible AI assistants, enabling conversational access to DevOps workflows like repo creation, build tracking, and container image security auditing.
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