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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.

9,457 servers. Last updated -

Matching MCP tools:

Matching MCP servers:

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    A server that enables retrieval of Sentry issues through two simple tools - get a specific issue by URL/ID or get a list of issues from a project.
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    A dynamic MCP server that automatically discovers Python files in a directory and exposes them as tools to any MCP-compatible AI client, allowing users to easily create and deploy custom AI tools.
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    Enables LLMs to perform sophisticated web searches through proxy servers using Tavily's API, supporting comprehensive web searches, direct question answering, and recent news article retrieval with AI-extracted content.
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    An MCP server providing read-only access to Linear issues for language models, allowing them to fetch issue details and comments using a Linear API token.
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    A flexible proxy that enables discovery and execution of tools across multiple Model Context Protocol (MCP) servers and JavaScript functions, reducing context size even when dealing with hundreds of tools.
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    • Apple

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    A MCP Proxy (Local <-> SSE) with token based authentication.
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    A proxy server that enables AI assistants to run and interact with command-line applications like Expo through the Model Context Protocol (MCP), capturing logs and allowing keypress forwarding.
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    Intelligent HTTP/HTTPS proxy server with MCP integration for automated traffic monitoring, analysis, and browser setup.
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    Enables interaction with remote MCP servers using SSE transport instead of STDIO for enhanced communication capabilities.
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    Middleware that converts a serverless handler with OpenAPI spec into an MCP endpoint following stateless MCP principles.
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    An MCP server that provides tools for exploring large OpenAPI schemas without loading entire schemas into LLM context. Perfect for discovering and analyzing endpoints, data models, and API structure efficiently.
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    Bridges Ethereum JSON-RPC queries from Geth nodes to the Model Context Protocol ecosystem, exposing blockchain operations as MCP tools. Enables AI models and applications to securely interact with Ethereum data including blocks, transactions, balances, and advanced debug functions through schema-validated access.
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    A tool that accelerates MCP protocol adoption by automatically generating MCP-compatible server components from OpenAPI specifications, enabling seamless integration with existing services as a sidecar.
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    A modified JetBrains MCP Server that adds WebSocket monitoring capabilities, allowing users to monitor MCP tool calls in real-time while maintaining compatibility with the original implementation.
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    Apache 2.0
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    A central hub that aggregates multiple MCP resource servers into a single unified interface, enabling users to access tools and capabilities from multiple backend servers through one connection point.
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    A service that converts existing MCP protocols (stdio/sse) to streamable\_http transmission type, allowing compatibility between different MCP implementations.
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    Bridges STDIO-based MCP clients with SSE-based MCP servers, allowing applications like Claude Desktop to connect to remote MCP servers that use SSE transport.
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    Enables structured, iterative reasoning for complex problem-solving with features like confidence tracking, revision mechanisms, and branching support. Provides flexible validation and multiple output formats for systematic analysis and decision-making tasks.
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    A FastMCP server that proxies the Poe.com API, allowing users to query various AI models (including Claude 3.7 Sonnet) and share files with models that support it.
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    An unofficial JavaScript SDK to create customized servers for the Model Context Protocol, allowing definition of prompts, resources, and tools for tailored interactions.
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    A server that enables AI assistants to execute JavaScript code with persistent context through stateful REPL sessions, file operations, and package management features.
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    Enables AI agents to break down complex tasks into manageable pieces using a structured JSON format with task tracking, context preservation, and progress monitoring capabilities.
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    Allows AI models to run JavaScript/TypeScript code through Model Context Protocol tool calls, supporting both one-time script execution and stateful REPL sessions with npm package integration.
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    A server that implements the Model Context Protocol for managing dynamic forms, allowing users to create, retrieve, and handle responses for web forms via the @dynamicfrm/js library.
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    An MCP Server that provides a conversational interface to the UK Open Banking account information API, allowing agents to interact with bank account data through natural language commands.
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    Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.
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    A Model Context Protocol server that provides AI assistants access to AWS CloudWatch Logs, enabling browsing, searching, summarizing, and correlating logs across multiple AWS services.
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    Provides a secure, isolated JavaScript execution environment with configurable time and memory limits for safely running code from Claude.
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    A simple MCP server implementation in TypeScript that communicates over stdio, allowing users to ask questions that end with 'yes or no' to trigger the MCP tool in Cursor.
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