"Open source MCP (Model Context Protocol) implementations" matching MCP servers:

Deterministic dependency + CVE context for AI coding tools, over the Model Context Protocol. A ~0.85 MB pure-Rust MCP server.

Exposes open automation platform capabilities to AI agents with tools for managing job templates, inventories, collections, EDA activations, audit events, and policy checks, governed by gateway auth, RBAC, and policy enforcement.

Enables auditing MCP servers' tools by their estimated context token cost, ranking verbose names, descriptions, and schemas before they consume the agent window. Can run as an MCP tool so agents can budget their own context.

Enables AI agents and external systems to programmatically trigger and monitor Jenkins jobs, retrieve build status and logs via MCP standards.

Enables structured role-to-role handoffs and merge gating for multi-agent collaboration. It persists evidence and computes approval gates without invoking LLMs.

Enables agents to run configured JSON equality checks and assigned pinned GitHub checks through a local stdio connector with operator-provisioned API access. It helps verify disclosed automation evidence against explicit check scopes.

A FastAPI-based JSON-RPC 2.0 server implementation that enables users to work with HDF5 files, submit Slurm jobs, retrieve CPU information, and visualize CSV data through standardized API endpoints.

Enables AI assistants to interact with Azure DevOps, providing tools for managing work items, repositories, pipelines, and more through the Model Context Protocol.

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.

An open-source server that enables AI agents to interact with Azure DevOps projects through the Model Context Protocol, providing tools for managing work items, wikis, and repositories to streamline development workflows.

Integrates GitLab with AI assistants to manage merge requests, analyze CI/CD pipelines, and create Architecture Decision Records. It enables seamless code searching, pipeline triggering, and deployment management through the Model Context Protocol.

A Model Context Protocol (MCP) server that provides tools for interacting with Bitbucket repositories, pull requests, issues, and more.

Enables AI-assisted code review and repository management for on-premise GitLab instances. It provides tools for interacting with merge requests, browsing source code, and searching repositories via the Model Context Protocol.

MCP Harbor is a Node.js application that provides a Model Context Protocol (MCP) server for interacting with Harbor container registry.

An open source MCP server empowering SREs with intelligent observability, predictive analytics, and AI-driven automation across Kubernetes, OpenShift, and Tekton environments.

Protect against malicious open source packages 🤖

Model Context Protocol server for Cyclops

A Model Context Protocol (MCP) server for integrating ArgoCD GitOps continuous delivery tool with GenAI applications, enabling intelligent Kubernetes deployment management.

Agent-readiness scorecard for any MCP server: protocol checks, 0-100 score and actionable findings.

Enables AI agents to deploy static files and get live HTTPS URLs instantly, with support for custom domains and data residency.