Built a local-first context engine for AI coding agents — symbol graph + semantic search, no cloud

Sharing a project I've been building: Argyph, an MCP server that gives AI coding agents (Claude, or anything that speaks MCP) structured and semantic understanding of a codebase. The problem: agents are good at reasoning but bad at retrieval. They grep, guess, and pull whole files into a limited context window. Most context tools that try to fix this depend on a cloud vector database and a remote embedding API. Argyph runs entirely locally - single binary, embedded vector, bundled embedding model, no API key.