OpenDia is an open - source browser extension tool that allows AI models to directly control the user's browser, perform automated operations using existing login status, bookmarks and other data, support multiple browsers and AI models, and focus on privacy protection.

The Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers. It aims to provide large language models (LLMs) with secure and controllable access to tools and data sources. These servers demonstrate the diversity and scalability of MCP, covering various functions from file system operations to database integration, from web search to AI image generation.

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.

openai - tool2mcp is an open - source bridging tool that encapsulates OpenAI's built - in high - quality tools (such as web search and code interpreter) into an MCP protocol server, enabling MCP - compatible models like Claude to use these powerful functions.

SEC EDGAR MCP is an open - source MCP server that connects AI models to the EDGAR database of the U.S. Securities and Exchange Commission (SEC) and provides corporate financial data query tools.

The Model Context Protocol (MCP) is an open - source protocol released by Anthropic, aiming to solve the standardization problem of connecting large language models (LLMs) with external data sources and systems. It provides a structured framework that enables models to integrate and utilize external context, thereby expanding their capabilities and improving response accuracy. MCP supports functions such as knowledge expansion, external tool calls, and pre - written prompts.

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.

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

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.

The Model Context Protocol (MCP) is an open-source protocol designed to enable Large Language Models (LLMs) to seamlessly interact with external tools, services, and data sources through a standardized interface, simplifying the integration process and expanding AI capabilities.

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. This project includes various types of server implementations, covering multiple domains such as file systems, databases, Git, and Slack, and supports TypeScript and Python SDKs.

This project is an experimental Aider MCP server used to offload AI programming tasks to the Aider open - source assistant to improve development efficiency and flexibility. It supports multiple AI models, provides code modification and model list functions, and integrates with Claude Code through the MCP protocol.

MCP - OpenLLM is a LangChain wrapper tool for seamless integration of different MCP servers and open - source large language models (LLMs), supporting the use of LangChain community models.

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

Awesome MCP Servers is a curated list of Model Context Protocol (MCP) servers and tools. MCP is an open standard introduced by Anthropic that enables AI models to connect to external data sources and tools through standardized interfaces, enhancing their capabilities.

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers, enabling large language models (LLMs) to securely and controllably access tools and data sources. The project includes server implementations with various functions, such as file system operations, database access, Git management, Slack integration, etc., and supports TypeScript and Python SDKs.

The SCANOSS MCP Server is a service integrating SCANOSS open - source scanning technology. It provides code snippet scanning, open - source license compliance checking, and component analysis functions for language models through the Model Context Protocol.

The Storm MCP server is an open protocol that enables seamless integration of LLM applications with RAG data sources and tools, supports custom embedded models and vector database connections, and provides functions such as context sharing, tool systems, and file management.

This is a list of multiple open - source AI projects, covering multiple fields such as automated agents, large - language models, image generation, and AI development frameworks. These projects aim to help developers make money using AI technology, including building intelligent assistants, automating workflows, and content generation applications.

Model Context Protocol (MCP) is an open - source protocol that provides a series of reference implementations and community - developed servers for providing large language models (LLMs) with secure and controlled access to tools and data sources. The project includes various functional servers, such as file system operations, Git integration, database access, etc., and supports rapid development of new services through TypeScript and Python SDKs.