Local-first code indexer that provides deep code understanding for Claude and other LLMs with symbol/text search across 48+ languages, semantic search capabilities, and real-time index updates through the Model Context Protocol.
Enables AI agents to locally search, query, and understand codebases with token-efficient context, dependency graphs, history, architecture diagrams, and metrics through MCP.
Provides AI assistants with a structured, token-efficient map of a codebase's symbols, dependencies, and relationships via MCP tools like overview, query, and impact analysis.
A local-first codebase intelligence tool that enables AI assistants to research codebases using semantic search, multi-hop relationship discovery, and structural parsing. It allows users to extract architectural patterns and institutional knowledge across 30+ programming languages through an MCP-compatible interface.
An MCP server that extracts complete knowledge from any codebase — architecture, patterns, dependencies, API surface. Combines static analysis with AI-powered deep interpretation.