Discover the Power ofModel Context Protocol

A Model Context Protocol (MCP) server and CLI that provides tools for agent use when working on iOS and macOS projects.

Claude Code is powerful. Pilot makes it reliable. Tests enforced. Context preserved. Quality automated. ☑️

📻Terminal/ssh/sftp/ftp/telnet/serialport/RDP/VNC client(linux, mac, win)

LangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases. It makes implementing RAG, tool calling (including support for MCP), and agents easy. LangChain4j integrates seamlessly with various enterprise Java frameworks.

Memory for 24/7 proactive agents like openclaw (moltbot, clawdbot).

🚀Vite+Vue3+Gin拥有AI辅助的基础开发平台，企业级业务AI+开发解决方案，内置mcp辅助服务，内置skills管理，支持TS和JS混用。它集成了JWT鉴权、权限管理、动态路由、显隐可控组件、分页封装、多点登录拦截、资源权限、上传下载、代码生成器、表单生成器和可配置的导入导出等开发必备功能。

Enhanced ChatGPT Clone: Features Agents, MCP, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active.

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Open-source, AI-native, low-code platform for API orchestration, workflow automation, and AI agent integration across internal systems and SaaS products.

RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs

MCP Toolbox for Databases is an open source MCP server for databases.

The ultimate space for work and life — to find, build, and collaborate with agent teammates that grow with you. We are taking agent harness to the next level — enabling multi-agent collaboration, effortless agent team design, and introducing agents as the unit of work interaction.