Parse a repository and build its code graph in Neo4j. Run this once per project, and again after significant changes — unchanged files are skipped by content hash, so re-indexing is cheap. Supports Python, TypeScript, TSX and JavaScript.

Locate the definition of a function, class or method by name. Accepts a bare name (fetch_info) or a qualified one (MarketData.fetch_info), and falls back to substring matching.

Every symbol that reaches this one through the call graph, nearest first. This is the question grep answers badly: it finds the name, not the callers.

Everything this symbol calls, transitively — the downstream surface of a function.

What breaks if this symbol changes. Returns everything transitively upstream, split into production callers and the tests that reach it. An empty test list means the change is unguarded — check this before editing shared code.

How control actually flows from one symbol to another — e.g. from an HTTP handler to a database write.

Symbols with the most distinct callers — the code where a mistake propagates furthest. Ranked by in-degree, which works on Neo4j AuraDB Free (no GDS required).

Import edges aggregated to top-level directories — a quick read on the architecture and on which packages depend on which.

Which repositories are in the graph, and how many files each has.

Delete every node belonging to a repository. Irreversible.