In this video, I'll be telling you about Claude Context, an open-source MCP plugin that adds semantic code search to AI coding agents and helps them understand larger codebases much faster.

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Key Takeaways:

🚀 Claude Context adds semantic code search to Claude Code and other MCP-compatible coding agents.  
🔍 It uses hybrid search, combining dense vector search with BM25 keyword search for better retrieval.  
🧩 AST-based chunking and incremental indexing help it understand code more accurately and efficiently.  
💾 You can use it with Zilliz Cloud and OpenAI, or run it fully locally with Milvus and Ollama.  
⚙️ It is especially useful for medium to large repositories where manual context gathering wastes time and tokens.  
🛠️ The tool is simple to use, with just a few MCP commands like index, search, status, and clear.  
👍 Overall, Claude Context is a practical workflow upgrade for anyone using AI coding agents on real-world codebases.

AICodeKing

Claude Context is an open-source MCP plugin that adds semantic code search to AI coding agents like Claude Code, Cursor, and Codex. It indexes a repository into a vector database and uses hybrid search (dense vector + BM25) to retrieve only relevant code chunks, reducing wasted context and token costs. Key features include incremental indexing via Merkle trees, AST-based chunking, support for 14+ languages, and compatibility with most MCP-capable coding clients. Setup requires Node 20-23, a vector database (Zilliz Cloud or local Milvus), and an embedding provider (OpenAI or local Ollama). The project claims ~40% token reduction and has over 6,000 GitHub stars. It is MIT licensed and best suited for developers working on medium-to-large codebases who rely heavily on AI coding agents.

Claude Context: This NEW & SIMPLE PLUGIN is CRAZY!