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.
High-performance AI pipeline engine with a C++ core and 50+ Python-extensible nodes. Build, debug, and scale LLM workflows with 13+ model providers, 8+ vector databases, and agent orchestration, all from your IDE. Includes VS Code extension, TypeScript/Python SDKs, and Docker deployment.
APISIX Model Context Protocol (MCP) server is used to bridge large language models (LLMs) with the APISIX Admin API.
Govern consequential AI agent actions in Docker with deterministic policy, human approval, and signed Decision Dossiers.
Official Pulumi Agent Skills for writing, migrating, and operating infrastructure with AI coding agents
AI API gateway that ends manual channel switching with smart routing, auto failover, exponential cooldown, multi-URL scheduling, live request monitoring and soft-error detection.
Agents and skills for building Windows apps with WinUI 3 and the Windows App SDK
Native local development environment for Windows, macOS & Linux. A modern alternative to XAMPP, MAMP, Laragon and Laravel Herd, with runtimes, databases, web servers, local sites, HTTPS, AI coding tools and MCP.
Open-source, self-hosted CMS platform on AWS serverless (Lambda, DynamoDB, S3). TypeScript framework with multi-tenancy, lifecycle hooks, GraphQL API, and AI-assisted development via MCP server. Built for developers at large organizations.
A Model Context Protocol (MCP) server that enables AI assistants to interact with AKS clusters. It serves as a bridge between AI tools (like Claude, Cursor, and GitHub Copilot) and AKS.
A specialized server implementation for the Model Context Protocol (MCP) designed to integrate with CircleCI's development workflow. This project serves as a bridge between CircleCI's infrastructure and the Model Context Protocol, enabling enhanced AI-powered development experiences.
All-in-one Kubernetes SDK: create, manage, and operate clusters across distributions (Kind, K3d, Talos, VCluster) with built-in GitOps, secrets, AI assistant, and MCP server. Only requires Docker or a Cloud Provider.
Express REST API and MCP Server Framework is a comprehensive development framework for building RESTful APIs and MCP servers with Express.js. It provides a complete template for creating production-ready APIs using Node.js, Express, Mongoose (MongoDB), and Sequelize (SQL databases).
Windows Computer Use for AI Agents. Both a tool (22 MCP tools for click, type, screenshot, OCR, UI inspection) and an agent (autonomous mission engine, macro recorder, intent-based discovery, event watchers). Built with opencode (DeepSeek V4). Ships as MCP server, web UI, and Tauri desktop app.
MCP Fusion - The TypeScript framework for secure MCP servers.
Yet another WebUI for Nginx
Microsoft Dataverse skills for AI coding agents. Wraps the Dataverse MCP server, Dataverse CLI, Python SDK, and PAC CLI behind specialist skills for building, querying, deploying, and administering Dataverse environments.
Emdash is the Open-Source Agentic Development Environment (🧡 YC W26). Run multiple coding agents in parallel. Use any provider.
MCP Aggregator, Orchestrator, Middleware, Gateway in one docker
Become 10x Vibe Coder. Awesome Vibe Coding guide, best practices, and tips for efficient and controlled AI assisted coding.
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.