LeanKG is a Go-based knowledge graph engine for AI-assisted development. It indexes source code from multi-language repositories into a graph of elements (functions, types, classes) and relationships (calls, imports, implements), stored in SQLite or PostgreSQL with optional vector embeddings for semantic search. The system provides a CLI, REST API, MCP (Model Context Protocol) server, and a React web UI (force-directed graph, file tree, code panel). Core capabilities include incremental indexing with three-signal change detection, a four-tier query ladder (cold/exact/fuzzy/semantic), impact analysis with blast radius, organizational knowledge management (incidents, notes, env reports), ontology matching, federation across servers, and token-budgeted compression for AI tool integration. The architecture is modular: the store backend interface supports SQLite and PostgreSQL with a shared migration ledger; indexing uses regex extractors for 40+ languages with an optional tree-sitter CGO tier; embeddings use a provider abstraction (OpenAI-compatible, llama.cpp sidecar, deterministic). The codebase is well-structured with extensive tests, hermetic test patterns, and deterministic output design. Notable reusability includes the compress package (shell output, git diff), auth token system, store abstraction pattern, and A/B benchmarking harness.