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mcp GitHub repositories

Explore 443 tracked GitHub repositories tagged mcp. Compare their recorded star activity and implementation languages, then follow related topics to find other projects.

Snapshot: 2026-10-29. The collection gained 10,075 stars since the previous daily snapshot.

Tracked repositories
443
Total stars
4,357,267
Stars gained · 7 days
+68,350
Stars gained · 30 days
+233,817

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Star activity for mcp repositories on this page
RepositoryTotal starsToday7 days30 days
hetpatel-11/Adobe_Premiere_Pro_MCP775+4+37+154
Haohao-end/openagent774+0+0+0
ronak-create/FableCut768+2+29+73
dapr/dapr-agents767+0+0+0
DemonDamon/AgenticX765+30+175+236

Explore repositories

Showing 351–400 of 443 tracked repositories.

cso1z/Feishu-MCP

Feishu / Lark 飞书文档与任务管理工具,支持 MCP 服务器和 CLI + Skill 两种使用方式,可无缝集成 Cursor、Claude Code、Cline 等 AI 编码工具
★ 744+0 todayTypeScript
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calmrocks/ai-engineer-notebooks

Hands-on, framework-free Colab notebooks for the AI Engineer / Forward Deployed Engineer (FDE) skill set — model APIs, structured output, tool calling, RAG, evals-as-the-spine, agents (loop from scratch, tool design, guardrails, MCP, Skills), fine-tuning vs LoRA, prompt-injection/security, LLMOps, and customer craft. Runs on the free Groq API.

Bessouat40/RAGLight

RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.

AgentiLoop/Agent

Agent! now supports macOS 14.6 or later, Apple Silicon and Intel, latest release. The Best AI agent for Mac: drives any app via Accessibility, codes/builds in Xcode, automates AppleScript, JXA, Swift and SMAppService shell (user/root). 23 LLM providers, local/cloud, plus on-device Apple Intelligence and Jev guard. Auto-Pilot, MCP, Avatar.

apache/casbin-gateway

See what every AI coding agent on your machine is doing, and whether the API behind it is the one you paid for. Claude Code, Codex, Cursor, Gemini CLI and more: one endpoint for 44 model vendors, A–F API authenticity grading, per-agent permissions, usage and prompt records.

Haozhe-Xing/agent_learning

A systematic AI Agent development tutorial covering LLM agents, RAG, tool use, memory systems, multi-agent systems, LangChain, LangGraph, MCP, and agentic RL.|从零开始学 AI Agent 开发 | 系统、全面、实战导向的 Agent 开发教程 | 每日自动追踪 arXiv 最新论文 | Learn AI Agent Development from Scratch