Become 10x Vibe Coder. Awesome Vibe Coding guide, best practices, and tips for efficient and controlled AI assisted coding.

Persistent Linux workspaces for agentic development.

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.

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.

Workflow for AI Agents enables automated conversion of CAD files (such as `.rvt`, `.ifc`, `.dwg`) using command-line converters on a local Windows machine

Public repository for Advanced Unity MCP by Code Maestro (www.code-maestro.com).

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.

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.

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.

Emdash is the Open-Source Agentic Development Environment (🧡 YC W26). Run multiple coding agents in parallel. Use any provider.

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.

ToolHive is an application that allows you to install, manage and run MCP servers and connect them to AI agents

APISIX Model Context Protocol (MCP) server is used to bridge large language models (LLMs) with the APISIX Admin API.

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.

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.

Harness’ official MCP Server

MCP Fusion - The TypeScript framework for secure MCP servers.

Yet another WebUI for Nginx

Published in CNCF Landscape: A MCP server for Kubernetes.

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).

MCP Server for the Bitrise API, enabling app management, build operations, artifact management and more.

Agents and skills for building Windows apps with WinUI 3 and the Windows App SDK

MCP Aggregator, Orchestrator, Middleware, Gateway in one docker

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.