Claude Context is an MCP (Model Context Protocol) plugin developed by Zilliztech, designed to provide deep code context to Claude Code and other AI coding assistants. It leverages semantic search to efficiently retrieve relevant code snippets from entire codebases, injecting them directly into the AI's context. This approach addresses the limitations of context windows and high costs associated with large codebases by storing the codebase in a vector database for efficient management and cost-effectiveness.
An AST-based semantic code search tool powered by the high-performance CocoIndex Rust engine. It provides precise code retrieval by understanding code structure rather than text snippets, reducing token usage by 70%. It integrates seamlessly as a Skill or MCP server for agents like Claude Code and Cursor. Featuring zero-config setup and support for both local and cloud embeddings, it enables efficient semantic search within CLI and modern AI coding environments.
Semble is a fast, CPU-only code search library by MinishLab designed specifically for AI agents. It efficiently retrieves relevant code snippets via natural language queries, reducing token usage by ~98% compared to traditional grep-and-read methods. Requiring no API keys, GPUs, or external services, it indexes and queries codebases locally in milliseconds, achieving near-transformer retrieval accuracy. It functions seamlessly as an MCP server for instant integration with Claude Code, Cursor, and other agent workflows.