Builds a semantic knowledge graph of C++ code and exposes 9 MCP tools for AI assistants to search classes, functions, inheritance, callers, callees, overrides, and more.
Local-first codebase context engine that parses code into a ranked dependency graph and serves it to AI tools via MCP for deep structural understanding.
A local knowledge graph of your codebase for Claude Code on macOS, exposing structural data via MCP tools for querying calls, imports, test coverage, and impact analysis.
Enables AI coding assistants to understand codebase architecture in real time by parsing source code into a relationship graph and exposing call chains, dependencies, class hierarchies, and conventions via MCP tools.
An MCP server and CLI tool that transforms codebases into AI-ready context through semantic search, call graph analysis, and incremental indexing. It enables AI assistants to perform hybrid vector and keyword searches to understand complex repository structures and cross-file relationships.
AI-native code intelligence graph that builds a persistent knowledge graph of your codebase in Neo4j and exposes it to AI assistants via MCP, enabling contextual code analysis, impact analysis, and dependency tracking.