Provides token-efficient code retrieval for coding agents by indexing repositories and enabling ranked snippet search, symbol outlines, and surgical line reads.
An MCP server for efficient code indexing and symbol retrieval using tree-sitter AST parsing to fetch specific functions or classes without loading entire files. It significantly reduces AI token costs by providing O(1) byte-offset access to code components across multiple programming languages.
Enables AI coding agents to intelligently index and search codebases with sub-20ms retrieval, 8x memory compression, and cross-encoder reranking via MCP stdio.
Provides a local-first code indexing and search engine for coding agents via MCP, enabling precise codebase queries, symbol lookup, and freshness-aware retrieval.
A fully local RAG MCP server for semantic code search and code intelligence, using AST-level chunking and hybrid search to pinpoint functions, classes, and APIs. No cloud, no API keys, zero setup.
A precision code-retrieval MCP server for coding agents working in large, legacy, and air-gapped codebases. It returns exact file and line range citations from natural-language queries without requiring the agent to perform blind searches.