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基于大模型(DeepSeek,OpenAI等)的 GitLab 自动代码审查工具；支持钉钉/企业微信/飞书推送消息和生成日报；支持Docker部署；可视化 Dashboard。
A Model Context Protocol (MCP) server that enables secure interaction with MySQL databases
MCP 资源精选， MCP指南，Claude MCP，MCP Servers, MCP Clients
Suna - Open Source Generalist AI Agent
Daytona is a Secure and Elastic Infrastructure for Running AI-Generated Code
Universal memory layer for AI Agents; Announcing OpenMemory MCP - local and secure memory management.
🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
🤗 smolagents: a barebones library for agents that think in code.
This repository contains the Hugging Face Agents Course.
🚀 The fast, Pythonic way to build MCP servers and clients
Build resilient language agents as graphs.
A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
LightAgent: Lightweight AI agent framework with memory, tools & tree-of-thought. Supports multi-agent collaboration, self-learning, and major LLMs (OpenAI/DeepSeek/Qwen). Open-source with MCP/SSE p…
This Streamlit application provides a user interface for connecting to MCP (Model Context Protocol) servers and interacting with them using different LLM providers (OpenAI, Anthropic, Google, Ollama).
Specification and documentation for the Model Context Protocol
MCP Markdown Server 是一个基于 Model Context Protocol (MCP) 的服务器应用，提供 Markdown 文档的创建**、**编辑**、**搜索**、**转换为html和管理的功能。该项目结合了讯飞星火大模型 API 和 MCP 协议，实现了智能化的 Markdown 文档处理能力。
Model Context Protocol Servers
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
Interactive roadmaps, guides and other educational content to help developers grow in their careers.
A chatbot implementation compatible with MCP (terminal / streamlit supported)
LeetCode solutions in Python2. LeetCode题解 in Python2。
code for EMNLP 2019 paper Text Summarization with Pretrained Encoders