Aderyn is an open - source Solidity smart contract static analysis tool written in Rust, which helps developers and security researchers discover vulnerabilities in Solidity code. It supports Foundry and Hardhat projects, can generate reports in multiple formats, and provides a VSCode extension.

Cognee is an open - source project that provides memory functions for AI agents. It builds a dynamic knowledge graph through a modular ECL pipeline, supports multiple data sources and formats, reduces hallucinations, and lowers costs.

Klavis AI is an open - source project that provides a multi - functional computing platform (MCP) for use on Slack, Discord, and web pages. It allows non - technical users to easily configure AI workflows, and developers can expand and build on it.

MCPAdapt is an open - source project aiming to seamlessly integrate the tools of over 650 MCP servers into various agent frameworks, enabling developers to easily use these tools in their agent workflows.

Open Data MCP is an open - source project aiming to quickly connect public data sets to LLM applications through the MCP protocol. The project provides a CLI tool to achieve a 2 - minute connection (currently supporting Claude) and establishes a community collaboration framework that allows developers to easily contribute and publish public data sets. The core goal is to build an infrastructure that connects all LLM applications with millions of public data sets.

Open Data MCP is an open - source project aiming to quickly connect public data sets to LLM applications through the MCP protocol, enabling convenient access to open data and community - based publishing.

The HubSpot MCP Server is an open - source project that provides functions to interact with the HubSpot CRM API, supporting the management of contacts, deals, and companies, as well as sales analysis and forecasting.

A Claude - based code analysis tool for analyzing open - source projects and generating intelligent merge strategies

MCP is an open-source protocol for standardizing LLM interactions, providing a unified framework for connecting data sources, obtaining context, using tools, and executing standard prompts. Project examples demonstrate how to build MCP servers and clients to implement knowledge base chatbot functionality.

This project compiles a list of popular Model Context Protocol (MCP) servers based on Smithery.ai usage data. MCP is an open-source standard developed by Anthropic for establishing secure two-way connections between data sources and AI tools.

Auth0 MCP Server is an open - source project that integrates Auth0 management functions into LLMs and AI agents through the Model Context Protocol, allowing users to perform Auth0 management operations through natural language.

Unity-MCP is an open - source project that connects the Unity game engine with AI assistants. It implements AI - assisted development, automated testing, and runtime debugging functions through the Model Context Protocol.

MCPRepository is an open - source Next.js project aimed at centrally managing MCP servers and simplifying the discovery, listing, and installation processes of MCP servers.

MCP Servers is a project hosted on GitHub, which includes workflows such as automated testing, code coverage checking, and security scanning, and follows open - source licenses and community codes of conduct.

This is a curated list of Model Context Protocol (MCP) servers in the cryptocurrency field, containing multiple open - source projects that provide services such as blockchain data query, cryptocurrency trading, real - time market indices, and news and information.

This project is an implementation of an MCP server based on OpenSearch, providing semantic memory storage and retrieval functions for LLM applications such as Claude, and supporting the connection of AI tools and data sources through a standard protocol.

PhonePi MCP is an open - source project that can transform your phone into a toolbox for AI assistants. It enables remote control of phone functions through the Model Context Protocol, including managing contacts, messages, settings, etc. It emphasizes local deployment and network security.

The Vaali MCP server is an open - source project that demonstrates advanced AI agent capabilities. Through interactive parameter collection and workflow automation, it implements two modes: official MCP inquiry and intelligent parameter guidance, and supports cloud deployment and local integration.

The Browserbase MCP Server is an open - source project based on the Model Context Protocol (MCP), providing cloud browser automation capabilities, supporting web page interaction, data extraction, screenshot taking, and JavaScript execution, etc., to help LLM applications seamlessly integrate with external data sources and tools.

This is an open - source project that includes over 35 pre - built MCP connectors for integrating SaaS tools into AI applications, supporting local development and type - safe configuration.

The Scrapeless MCP Server is an open - source protocol project that seamlessly integrates LLM applications with external data sources and tools (such as Google Search) in a standardized way, providing dynamic context retrieval capabilities.

gbox is an open - source self - hosted sandbox project that provides a secure environment for MCP integration and other AI agent use cases. It includes tools such as a terminal, browser, and file editor, supports local task execution and file processing, and provides Python and Typescript SDKs.

The Zhiyan Platform is an open - source platform for agent communication and development, aiming to help AIGC enthusiasts better understand and develop Agents. The platform provides a variety of default Agent functions, such as email sending, information search, weather query, paper search, express delivery query, and document retrieval, and supports users to customize tools. The project supports quick startup and Docker deployment, and plans to add a tool store and automatic build functions in the future.

EvolveMCP is an open - source project that enables Claude AI to independently build, install, and use tools, expanding the practical capabilities of AI through Python code execution.

Trellis MCP is an interface service that connects AI assistants with Trellis 3D generation models, supporting rapid generation of 3D assets through natural language and importing them into Blender. This project is based on an open - source model and requires self - deployment of the API backend. It is fast and free, but there are stability risks.

MCPXcode is an open - source project that implements the Model Context Protocol (MCP) specification, providing a structured protocol between Xcode and AI assistants for context exchange and tool execution.

ZeroPath MCP Server is an open - source project that allows developers to query security findings such as SAST issues, keys, and patches using natural language and directly integrate them into AI - assisted development tools.

The Voyp MCP server is an open - source project based on the Model Context Protocol, enabling AI systems such as Claude to make and manage phone calls via VOYP.

This is a list containing a large number of open - source AI projects, covering multiple fields from natural language processing, image generation to automated workflows. These projects aim to help developers build various applications using AI technology, including chatbots, code - generation tools, data - processing systems, etc.

Dafty MCP is an independently developed open - source project that interacts with Daft.ie through web crawlers, providing functions for searching and querying details of rental information in Ireland.

The OpenAlex MCP Server is an open - source project that implements the Model Configuration Protocol (MCP) to provide structured access to global academic literature for AI assistants.

Model Context Protocol (MCP) is an open standard that allows developers to establish a secure two-way connection between data sources and AI tools. This project provides a gem package implemented in Ruby, including full development process support and type checking functions.

MCP.science is an open - source project that provides a variety of MCP servers designed specifically for scientific research applications, enabling AI models to interact with scientific data, tools, and resources through a standardized protocol.

Portainer MCP is an open - source project that implements the Model Context Protocol (MCP). It connects AI assistants to the Portainer container management platform through a standardized interface, supporting querying and managing Docker/Kubernetes environments.

An open - source project that integrates Blender with local AI models to control 3D modeling through natural language.

The Orion Vision MCP Server is an open - source project based on the Model Context Protocol (MCP), providing seamless integration with Azure Document Intelligence services and supporting analysis and data extraction functions for multiple document types.

DocuMCP is an intelligent document deployment MCP server that provides a revolutionary document deployment solution for open - source projects through in - depth repository analysis, intelligent static site generator recommendation, and automated GitHub Pages deployment workflow.

mcp - searxng is an MCP server example designed for AI agents, which implements the external information search function through the open - source meta - search engine SearXNG. The project demonstrates how to integrate SearXNG and Microsoft's markdownify tool to convert web page content into Markdown - formatted text and communicate with MCP clients via the SSE protocol.

Createve.AI Nexus is an open - source project that bridges the gap between AI agents and enterprise systems by implementing the Model Context Protocol (MCP) standard. It provides secure, real - time data access and system integration capabilities. It supports multiple AI platforms, has an enterprise - level security architecture, and can connect various business applications, sensor data, and document management systems.

The Model Context Protocol (MCP) is an open-source protocol that provides a series of reference implementations and community-built servers, enabling large language models (LLMs) to access tools and data sources securely and controllably. The project includes implementations of various functional servers, covering areas such as file systems, databases, search, and API integration, and supports development with TypeScript and Python SDKs.