This project is a Model Context Protocol (MCP) adapter used to connect large language models (LLMs) with the Lisp development environment, supporting interaction through the lightweight Lisply protocol. The main functions include Lisp code evaluation, HTTP requests, and debugging support, suitable for scenarios such as AI-assisted symbolic programming and CAD design automation.

FastApply MCP Server is an enterprise-level code intelligence platform that provides comprehensive code analysis, search, and refactoring capabilities through local AI models, AST semantic search, security scanning, and intelligent pattern recognition. It supports multi-language development and large codebase processing.

Unity - MCP is a bridge tool that connects large language models (LLMs) and the Unity Editor. By exposing Unity Editor functions to AI clients, it enables an AI - driven automated development process. It supports custom tool extensions and currently provides core functions such as game object management, scene operations, and asset handling. It is mainly suitable for the Unity Editor environment.

The MCP Development Framework is a powerful toolset for interacting with large language models, providing functions such as file processing (PDF/Word/Excel) and web content retrieval. It supports Cursor IDE extension and has technical features such as intelligent file identification, efficient processing, and memory optimization.

CTX is a tool that connects code repositories with large language models (LLMs). By automatically generating structured context files, it solves the problem of low efficiency in code context transfer in AI development. It supports collecting information from various sources such as code files, Git repositories, and web pages, and can directly provide project context for AI assistants through the MCP server.

40ants-lisp-dev-mcp is an MCP server that provides tools for large language models (LLMs) to interact with a running Lisp image. It supports running in stdio or HTTP stream modes, allowing LLMs to call Lisp functions, obtain documentation, evaluate code, etc., facilitating AI-assisted programming in the Lisp development environment.

The MCP development framework is a powerful framework for creating custom tools to interact with large language models. It provides functions such as file processing and web content retrieval, supports multiple formats such as PDF, Word, and Excel, and has technical features such as intelligent recognition, efficient processing, and memory optimization.

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.

An MCP server implementation compatible with the OpenAI DALL - E API, supporting multiple large models and image - generation APIs, and providing convenient development and debugging tools.

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.

Awesome MCP Servers is a carefully curated collection of MCP (Model Context Protocol) servers to extend the capabilities of large language models (LLMs). This project lists various MCP server implementations by function, covering multiple professional domains such as databases, fintech, and knowledge memory, and provides development framework resources.

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.

MCP Assistant Server is an intelligent task analysis and tool recommendation server that integrates large language models, provides functions such as task analysis, tool recommendation, and context management, and supports use in development environments such as Cline and Cursor.

MCP server development guide, introducing how to build a standardized communication protocol server for large language models (LLMs), including core architecture, function implementation, and example code.