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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.

9,443 servers. Last updated -

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    A service discovery and proxy for MCP servers that enables registration, discovery, and execution of tools on remote MCP servers. Uses vector-based similarity search through Alibaba Cloud services to intelligently route requests to appropriate MCP services.
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    An enhanced sequential thinking tool optimized for programming tasks that helps break down complex coding problems into structured, self-auditing thought steps with branching and revision capabilities.
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    Implements Anthropic's 'reasoning' tool as an MCP server for Claude, providing a dedicated scratchpad for structured thinking that dramatically improves performance on complex problem-solving tasks.
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    An open-source Model Context Protocol application management platform that allows users to create applications from GitHub repositories with automatic information extraction and database integration.
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    A Model Context Protocol server that enhances Claude in Cursor AI with advanced reasoning capabilities including Monte Carlo Tree Search, Beam Search, R1 Transformer, and Hybrid Reasoning methods.
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    An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.
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    A sophisticated MCP server that provides a multi-dimensional, adaptive reasoning framework for AI assistants, replacing linear reasoning with a graph-based architecture for more nuanced cognitive processes.
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    Web search using free multi-engine search (NO API KEYS REQUIRED) — Supports Bing, Baidu, DuckDuckGo, Brave, Exa, and CSDN.
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    An open-source MCP implementation providing document management functionality. This project aims to replicate Cursor's @Docs functionality.
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    A Model Context Protocol (MCP) server for the Open Library API that enables AI assistants to search for book information.
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    A Model Context Protocol (MCP) server implementation for the Google Gemini language model. This server allows Claude Desktop users to access the powerful reasoning capabilities of Gemini-2.0-flash-thinking-exp-01-21 model.
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    A comprehensive Model Context Protocol server providing 33 specialized research and search tools for Claude Desktop, enabling powerful search capabilities across academic, technical, and general domains.
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    This is a MCP server that implements an unreasonable thinking system. It helps generate unconventional solutions: Generating unreasonable thoughts that challenge conventional wisdom. Creating branches of thinking in different directions
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    Enables access to Hong Kong government's official open data portal (DATA.GOV.HK) through natural language queries. Supports searching datasets, browsing categories, and retrieving detailed information about Hong Kong's public data resources.
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    Enhances AI model capabilities with structured, retrieval-augmented thinking processes that enable dynamic thought chains, parallel exploration paths, and recursive refinement cycles for improved reasoning.
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    An MCP server that enables managing multiple lines of thought with features like branch navigation, cross-references between related thoughts, and insight generation from key points.
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    A server that integrates Blender with local AI models via the Model Context Protocol, allowing users to control Blender using natural language prompts for 3D modeling tasks.
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    Pairs Claude Code with Google's Gemini AI for complementary code analysis, enabling intelligent routing where Claude handles local-context operations while Gemini leverages its 1M token context for distributed system debugging and long-trace analysis.
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    An MCP server that enables Claude to break down complex problems into manageable steps with support for revision and branching, facilitating dynamic and reflective problem-solving through a structured thinking process.
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    A tool that implements Claude Shannon's problem-solving methodology to help break down complex problems into structured steps including problem definition, constraints, modeling, validation, and implementation.
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    An advanced MCP server that implements sophisticated sequential thinking using a coordinated team of specialized AI agents (Planner, Researcher, Analyzer, Critic, Synthesizer) to deeply analyze problems and provide high-quality, structured reasoning.
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    A TypeScript Model Context Protocol (MCP) server to allow LLMs to programmatically construct mind maps to explore an idea space, with enforced "metacognitive" self-reflection.
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    An MCP server for navigating thought processes using branches, supporting thought cross-references and priority tracking to enhance insight generation and structured idea exploration.
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    This MCP server enables interaction with the Open States API, allowing users to access legislative data from US state governments through natural language commands.
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    Enables structured problem-solving through sequential thinking stages with persistent storage and analysis. Helps break down complex problems into manageable cognitive steps while tracking progress and generating summaries of the entire thought process.
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    A Model Context Protocol (MCP) server implementation for the OpenLedger API. This server provides structured context to AI models according to the MCP specification.
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    Enables AI assistants to access the Open Food Facts database to query detailed food product information, nutritional data, and environmental scores. Supports product lookup by barcode, smart search with filtering, nutritional analysis, product comparison, and dietary recommendations to help users make informed food choices.
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    This server facilitates structured problem-solving by breaking down complex issues into sequential steps, supporting revisions, and enabling multiple solution paths through full MCP integration.
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    • Apple
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    Provides dual-perspective analysis through alternating actor (creator/performer) and critic (analyzer/evaluator) viewpoints, generating comprehensive performance evaluations with balanced, actionable feedback.
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