🚀 The fast, Pythonic way to build MCP servers and clients
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Updated
Jan 17, 2026 - Python
🚀 The fast, Pythonic way to build MCP servers and clients
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
mcp-use is the easiest way to interact with mcp servers with custom agents
AWS MCP Servers — helping you get the most out of AWS, wherever you use MCP.
HexStrike AI MCP Agents is an advanced MCP server that lets AI agents (Claude, GPT, Copilot, etc.) autonomously run 150+ cybersecurity tools for automated pentesting, vulnerability discovery, bug bounty automation, and security research. Seamlessly bridge LLMs with real-world offensive security capabilities.
MCP 资源精选, MCP指南,Claude MCP,MCP Servers, MCP Clients
Master Claude Code with this Guide! Includes: Setup, SKILL.md files, Agents, Commands, workflows and tricks making Claude's potential skyrocket!
ClaudeCode Workflow Studio
A single hub to find Claude Skills, Agents, Commands, Hooks, Plugins, and Marketplace collections to extend Claude Code
MCP Aggregator, Orchestrator, Middleware, Gateway in one docker
A Unified MCP Server Management App (MCP Manager).
Local inspector for ChatGPT apps & MCP apps (ext-apps)
ToolHive makes deploying MCP servers easy, secure and fun
Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
PentestAgent is an AI agent framework for black-box security testing, supporting bug bounty, red-team, and penetration testing workflows.
The batteries-included, No-Code FinOps automation platform, with the AI you trust.
Production-Ready MCP Server Framework • Build, deploy & scale secure AI agent infrastructure • Includes Auth, Observability, Debugger, Telemetry & Runtime • Run real-world MCPs powering AI Agents
The best way to create, deploy, and share MCP Servers
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.
MCP Playbooks for AI agents
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