Lean KG

What it is

An indexer that builds a graph of a codebase in Postgres and serves it over MCP. Beyond symbols and dependencies it holds documentation, requirements and workflow concepts, so a question can cross from a written requirement to the code that implements it.

What you get

• Find a file, locate a function definition, and search code elements by name or type
• Call graphs, direct dependencies and dependents, and an impact radius bounded by hop count
• A focused review context - a subgraph plus a structured prompt - for a change you are about to make
• Concept and semantic search over the graph, with a compressed context read when the full context is too large
• Documentation indexed alongside the code, so a requirement ID joins to the files that implement it and back again
• Environment-aware filtering, conflict detection across environments, dead-code and diff-impact analysis
• An agent diary written and read back across sessions, and graph snapshots you can export

Requirements

Postgres with pgvector is the only storage engine and has to be up first; the bundled compose file puts it on port 5433 and LEANKG_PG_URL overrides the connection string. Then init, migrate and index the project. Docker serves MCP on port 9699; installing from source is cargo install leankg. In production the project splits into two binaries - a read-only MCP server that rejects mutating tools, and a worker that owns indexing, watching and embedding.

Setup effort

One command — cargo install leankg

Tools you get

76 tools named in the project's documentation.

Requires

• cargo on PATH
• Postgres with pgvector, running before you index — the bundled compose file serves it on :5433 and LEANKG_PG_URL points at your own