Claude Context
Provides semantic code search and indexing using vector embeddings and AST-based code splitting, enabling natural language queries across codebases with automatic file filtering and support for multiple embedding providers and vector databases.
About
Claude Context MCP server by Zilliz provides AI assistants with semantic code search and indexing capabilities using vector embeddings and AST-based code splitting. The implementation integrates with multiple embedding providers (OpenAI, VoyageAI, Gemini, Ollama) and vector databases (Zilliz Cloud, local Milvus) to create searchable code indexes that enable natural language queries across codebases, with automatic file filtering based on extensions and ignore patterns. Built with TypeScript and supporting both VSCode extension and standalone MCP modes, it includes comprehensive evaluation framework showing 39% token usage reduction compared to grep-only approaches while maintaining equivalent retrieval quality, making it valuable for developers working with large codebases who need efficient semantic code discovery and AI-assisted code understanding workflows.
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