Claude Context is an MCP plugin that provides in - depth context of the entire codebase for AI programming assistants through semantic code search. It supports multiple embedding models and vector databases to achieve efficient code retrieval.

An intelligent task management system based on the MCP protocol, providing an efficient programming workflow framework for AI agents, with functions such as task planning, decomposition, execution, and memory.

Provide a programming interface for the IACR Cryptology ePrint Archive, supporting efficient retrieval of cryptographic research papers

Code Index MCP is a code indexing and analysis server based on the Model Context Protocol (MCP), providing functions such as code search, file analysis, and intelligent filtering. It supports multiple programming languages and helps developers efficiently manage codebases.

A YAML declarative API testing framework, optimized for AI programming assistants. It seamlessly integrates with editors such as Claude/Cursor through the MCP server, enabling efficient API test generation and execution.

An intelligent task management system based on the Model Context Protocol (MCP), providing an efficient programming workflow framework for AI agents, with functions such as task planning, decomposition, dependency management, verification, and memory.

The MCP Programming Assistant is a project that provides programming assistance services, aiming to help developers complete programming tasks more efficiently.

A lightweight and efficient MCP server for monitoring and verifying the health status of the development environment, supporting multiple programming languages and tools. It is driven by YAML configuration and can expand new ecosystems without code modification.

VectorCode is a code repository indexing tool designed to optimize the prompt construction of large programming language models (LLMs) by indexing and providing code repository information. It supports multiple embedding engines, provides command - line tools and Neovim plugins to help developers more efficiently use project context to improve the quality of model output.