Nomik – AI agent memory through a structured knowledge graph of your codebase

Summary: Nomik converts your entire codebase into a structured knowledge graph representing functions, call chains, routes, databases, APIs, and events with real relationships. It integrates with AI editors like Cursor, Windsurf, and Claude via MCP to provide precise context queries, improving code understanding and impact analysis.

What it does

Nomik uses deep static analysis with Tree-sitter to extract nodes and typed edges from source code, building a Neo4j knowledge graph that maps dependencies and interactions across files. It supports TypeScript, Python, Rust, SQL, and config files, enabling AI agents to query accurate code relationships instead of raw file dumps.

Who it's for

It is designed for developers and AI coding agents working with large, multi-language codebases who need accurate cross-file context and impact analysis.

Why it matters

Nomik addresses AI agents’ limitations by replacing noisy file dumps with precise code structure, reducing hallucinations and enabling reliable queries like "what breaks if I change this?" and dead code detection.