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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.

11,848 servers. Last updated -

Matching MCP tools:

Matching MCP servers:

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    Enables generation and visualization of bar and pie charts from structured data using FastAPI and Altair. Charts are saved as PNG images and served via REST API endpoints with unique URLs.
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    An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.
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    Enables AI agents to build and query a persistent knowledge graph with entities, relationships, and observations. Features a core index system that ensures critical information is always accessible across all memory operations.
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    Enables storage and retrieval of knowledge in a graph database format, allowing users to create, update, search, and delete entities and relationships in a Neo4j-powered knowledge graph through natural language.
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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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    Enables creating, managing, analyzing, and visualizing knowledge graphs with support for multiple graph types (topology, timelines, changelogs, requirements, knowledge bases, ontologies) including node/edge management and resource association.
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    An implementation of persistent memory for Claude using a local knowledge graph, allowing the AI to remember information about users across conversations with customizable storage location.
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    An MCP server that integrates AI assistants like Claude with GitLab's merge requests, allowing them to review code changes, add comments, and approve/unapprove merge requests directly through the GitLab API.
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    A Model Context Protocol server implementing the Random Tree Model for encoding, compressing, and recalling narrative information across different levels of abstraction with configurable cognitive parameters.
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    Provides secure access to Microsoft Entra ID (Azure AD) resources including users, devices, and applications through Microsoft Graph API. Enables querying organizational data with comprehensive audit logging to Azure Blob Storage.
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    Enables generating beautiful syntax-highlighted code screenshots with professional themes directly from Claude. Supports file reading, line selection, git diff visualization, and batch processing across 20+ programming languages.
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    Enables exploration and analysis of Azure infrastructure by querying Azure Resource Graph, ARM, and Network Watcher APIs to create interactive topology maps. Provides tools for searching resources, discovering relationships, finding connectivity paths, and visualizing complete Azure infrastructure topologies.
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    Enables comprehensive GitHub PR reviews through Cursor's AI by fetching PR diffs, running static analysis tools (ESLint, Prettier, TypeScript, Semgrep), executing tests, and generating detailed code review reports with inline comments.
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    Provides a scalable knowledge graph implementation for Model Context Protocol using Elasticsearch, enabling AI models to store and query information with advanced search capabilities, memory-like behavior, and multi-zone architecture.
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    Enhances user interaction through a persistent memory system that remembers information across chats and learns from past errors by utilizing a local knowledge graph and lesson management.
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    A Model Context Protocol server for querying and analyzing Azure resources at scale using Azure Resource Graph, enabling AI assistants to explore and monitor Azure infrastructure.
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    Connects Claude Code with multiple AI models (Gemini, Grok-3, ChatGPT, DeepSeek) simultaneously, allowing users to get diverse AI perspectives, conduct AI debates, and leverage each model's unique strengths.
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    Enables comprehensive code analysis including quality assessment, security vulnerability detection, refactoring suggestions, complexity calculations, and automatic documentation generation for multiple programming languages.
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    A FastMCP server providing powerful code editing tools including precise file modifications with diff-based operations, file creation and reading with line numbers, and more tools for code editing workflows.
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    Allows LLM tools like Claude Desktop and Cursor AI to access and summarize code files through a Model Context Protocol server, providing structured access to codebase content without manual copying.
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    Allows LLMs to execute Python code in a specified Conda environment, enabling access to necessary libraries and dependencies for efficient code execution.
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    A smart code retrieval tool based on Model Context Protocol that provides efficient and accurate code repository search capabilities for large language models.
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    Creates and maintains a semantic knowledge graph of code that allows maintaining context across sessions with Claude, providing advanced search capabilities without requiring the entire codebase in the context window.
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    This project aims to build a Claude Code MCP server and implement its associated tools (explain\_code, review\_code, fix\_code, edit\_code, test\_code, simulate\_command, your\_own\_query). The server is implemented using Node.js and the MCP SDK. It receives tool requests from clients via Stdio, dynamically
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    A comprehensive code analysis and management tool that integrates with Claude Desktop to analyze code at project and file levels, helping adapt changes to projects intelligently.
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    A Model Context Protocol server that helps large language models process code repositories by providing file tree generation, code merging, and code analysis capabilities.
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    An MCP server to create secure code sandbox environment for executing code within Docker containers.
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    A Model Context Protocol (MCP) server that helps large language models index, search, and analyze code repositories with minimal setup
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    A MCP server for managing and storing code snippets in various programming languages, allowing users to create, list, and delete snippets via a standardized interface.
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    A scientific reasoning framework that leverages graph structures and the Model Context Protocol (MCP) to process complex scientific queries through an Advanced Scientific Reasoning Graph-of-Thoughts (ASR-GoT) approach.
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    An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.
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    Enables AI agents to write and execute Python code in an isolated sandbox that can orchestrate multiple MCP tool calls, reducing context window bloat and improving efficiency for complex workflows.
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