Self-hosted semantic code search for AI coding agents. Indexes many repositories at once with tree-sitter AST chunking, local llama.cpp embeddings and Qdrant, so Claude Code, Cursor, Codex and any MCP client can find code by meaning, trace usages and callers, and read the git history behind each chunk. No API keys, and your code never leaves your machine.
Enables AI coding agents to build and query local repository memory, returning ranked files, context packs, relationship maps, semantic recall, and feedback-tuned search without uploading code.
Architectural memory layer for AI coding.
Automatically extracts decisions, detects
security gaps, and analyzes git history
from your codebase in one command.
Provides AI coding agents with durable architecture memory for repositories by generating structured project maps of responsibilities, relationships, and risks.
Enables AI coding agents to understand unfamiliar codebases through project summaries, file explanations, feature tracing, change planning, test discovery, guided walkthroughs, and token-efficient repository digests.