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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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Matching MCP servers:

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    A Python application that automatically generates different types of mind maps (presentation, comparison, beginner/intermediate content, problem analysis, and review) to help organize ideas visually through Claude Desktop integration.
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    A lightweight MCP server that provides a unified interface to various LLM providers including OpenAI, Anthropic, Google Gemini, Groq, DeepSeek, and Ollama.
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    An MCP server that provides LLMs access to other LLMs
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    Share code context with LLMs via MCP or clipboard
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    Intelligently analyzes codebases to enhance LLM prompts with relevant context, featuring adaptive context management and task detection to produce higher quality AI responses.
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    Enables AI agents to interact with multiple LLM providers (OpenAI, Anthropic, Google, DeepSeek) through a standardized interface, making it easy to switch between models or use multiple models in the same application.
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    An MCP server that allows agents to test and compare LLM prompts across OpenAI and Anthropic models, supporting single tests, side-by-side comparisons, and multi-turn conversations.
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    A Model Context Protocol server that provides specialized prompt suggestions for backend development, frontend development, and general tasks to help LLMs generate better content.
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    A server based on Model Context Protocol that provides predefined prompt templates for tasks like code review and API documentation generation, enabling more efficient workflows in Cursor/Windsurf editors.
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    Enables querying WolframAlpha's LLM API for natural language questions, providing structured and simplified answers optimized for LLM consumption.
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    MCP server for managing and serving dynamic prompt templates using elegant and powerful text template engine. Create reusable, logic-driven prompts with variables, partials, and conditionals that can be served to any compatible MCP client like Claude Code, Claude Desktop, Gemini CLI, etc.
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    Enables cleaning and sanitizing prompts through an LLM-powered tool that removes sensitive information, provides structured feedback with notes and risks, and normalizes prompt formatting. Supports configurable local or remote OpenAI-compatible APIs with automatic secret redaction.
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    An MCP server that lets Claude Code consult stronger AI models (o3, Gemini 2.5 Pro, DeepSeek Reasoner) when you need deeper analysis on complex problems.
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    A Model Context Protocol server that provides unified access to multiple LLM APIs including ChatGPT, Claude, and DeepSeek, allowing users to call different LLMs from MCP-compatible clients and combine their responses.
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    Provides pre-defined prompt templates for AI assistants to generate comprehensive plans for TypeScript projects, API architectures, and GitHub workflows.
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    A server that enables browser-based local LLM inference using Playwright to automate interactions with @mlc-ai/web-llm, supporting text generation, chat sessions, model switching, and status monitoring.
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    A Model Context Protocol server that saves prompts with timestamps and allows users to list previously saved prompts for Claude Desktop.
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    Enables Claude to solve complex problems systematically by breaking them down into 3-4 structured thinking steps. Features document caching and multiple profiles including specialized modes for SuperClaude and SuperGemini frameworks.
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    An MCP server that automatically optimizes AI prompts using evolutionary algorithms, helping improve prompt performance, creativity, and reliability through iterative testing and refinement.
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    Provides custom prompts for Amazon Q by serving markdown files from the local filesystem as prompt templates through the Model Context Protocol.
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    Transforms simple prompts into detailed, professional specifications using AI, designed to get better results from Claude, ChatGPT, and other AI assistants.
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    A Model-Client-Protocol server that enables users to search the Gallica digital library of the National Library of France and generate structured sequential research reports with formatted citations and relevant images.
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    Svelte and SvelteKit developer odcumentation
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    A server that transforms a standard Language Model into a dynamic multi-agent system where the model simulates both a Conductor (project manager) and Experts (specialized agents) to tackle complex problems through a collaborative workflow.
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    A Model Context Protocol (MCP) server that provides intelligent tools for optimizing and scoring LLM prompts using deterministic heuristics.
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    A Model Control Protocol server that integrates with Claude Desktop to enable simultaneous querying and cross-checking of responses from multiple LLM providers including OpenAI, Anthropic, Perplexity AI, and Google Gemini.
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    A lightweight MCP server that enables LLMs to search the web via DuckDuckGo, search GitHub code repositories, and extract clean content from web pages in LLM-friendly formats.
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    An MCP-native server that enables intelligent task delegation from advanced AI agents like Claude to more cost-effective LLMs, optimizing for cost while maintaining output quality.
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    Enables multiple AI agents to share and read each other's responses to the same prompt, allowing them to reflect on what other LLMs said to the same question.
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    An AI server that provides intelligent prompt optimization capabilities, enhancing prompts for clarity, specificity, structure, and other attributes to improve AI interactions.
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    Enables natural language 3D modeling in Fusion 360 through an MCP server that translates user commands into Fusion 360 API calls. Supports creating, editing, and managing 3D objects, executing Python code, and capturing model views through conversational interactions.
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