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Open-Source MCP servers

Production-ready MCP servers that extend AI capabilities through file access, database connections, API integrations, and other contextual services.

5,503 servers. Last updated -

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    Enables interaction with the Things app through Claude Desktop, allowing task creation, project analysis, and priority management using natural language commands.
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    An integration that allows Cursor AI to generate images through the Draw Things API using natural language prompts.
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    Lets you use Claude Desktop to interact with your task management data in Things app, enabling you to create tasks, analyze projects, manage priorities, and implement productivity workflows through natural language.
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    Lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things on your Cloudflare account.
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    Lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things with Neon.
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    Use HuggingFace Spaces directly from Claude. Use Open Source Image Generation, Chat, Vision tasks and more. Supports Image, Audio and text uploads/downloads.
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    This lets you use Claude Desktop, or any MCP Client, to use natural language to accomplish things with Neo4j and your Aura account.
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    Swiss MCP is your AI-powered command center for orchestrating complex tasks with ease. Think of it as your personal AI assistant that can coordinate multiple AI tools to accomplish amazing things!
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    This MCP server lets you use Cursor IDE, or any MCP Client enabled agent, to use natural language to accomplish things with CircleCI, e.g: Find the latest failed pipeline on my branch and get logs
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    vizro-mcp
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    Enables integration with Things3, allowing the creation and management of tasks and projects via the MCP protocol, including synchronization with Agenda projects.
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    An enhanced Model Context Protocol (MCP) server that allows running Claude Code in one-shot mode with permissions bypassed automatically, featuring advanced task
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    Provides AI assistants with enhanced reasoning capabilities through structured thinking, persistent knowledge graph memory, and intelligent tool orchestration for complex problem-solving.
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    A Model Context Protocol plugin for Chinese Tung Shing (黄历/通勝/通胜) almanac calculations
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    Implements Anthropic's 'think' tool for Claude, providing a dedicated space for structured reasoning during complex problem-solving tasks that improves performance in reasoning chains and policy adherence.
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    A Model Context Protocol server that provides Claude with a dedicated space for structured thinking during complex problem-solving tasks, helping improve its reasoning capabilities.
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    Official implementation of Anthropic's 'think' tool that provides Claude with a dedicated space for structured reasoning, improving performance by up to 54% on complex tasks requiring multi-step problem solving.
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    Enables Claude's explicit thinking mode in Cursor, allowing users to see Claude's step-by-step reasoning process when prefacing queries with 'think'.
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    An MCP server that implements the 'think' tool, providing Claude with a dedicated space for structured thinking during complex problem-solving tasks to improve reasoning capabilities.
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    A minimal MCP Server that provides Claude AI models with the 'think' tool capability, enabling better performance on complex reasoning tasks by allowing the model to pause during response generation for additional thinking steps.
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    Enables Claude's explicit thinking mode in Cursor, allowing you to see Claude's step-by-step reasoning process when you type 'think \[your question]'.
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    A Model Context Protocol server that provides AI assistants like Claude with a dedicated space for structured thinking during complex problem-solving tasks.
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    An MCP server implementation of Anthropic's Think Tool prompt engineering technique that enables Claude to break down complex problems and enhance its reasoning capabilities by providing a simple tool that echoes back thoughts.
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    An MCP server that provides a "think" tool enabling structured reasoning for AI agents, allowing them to pause and record explicit thoughts during complex tasks or multi-step tool use.
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    Chat with your codebase through intelligent code searching without embeddings by breaking files into logical chunks, giving the LLM tools to search these chunks, and letting it find specific code needed to answer your questions.
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