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Run local semantic search and call graph analysis across codebases.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "grepai" yet — see the docs or source repo.
Run a semantic search in this repository for the user login retry flow, then identify the core modules, entry functions, and call chain, ranked by importance.
A list of relevant code locations, key functions, and a call graph overview from entry points to critical logic.
Analyze the call relationships between the payment and order modules, map the main function call paths, and highlight highly coupled nodes.
A cross-module call graph, notes on key dependency nodes, and areas that may need refactoring or review.
Build a semantic retrieval context from the local codebase to help the AI answer, "How does the configuration loading flow work?" Include relevant files and call chains.
A structured explanation of the configuration loading flow with traceable files, functions, and call paths.
Gives AI coding agents semantic code graphs for faster, more precise answers.
Query JavaScript and TypeScript codebases in natural language for function insights.
Access public GitHub code and docs for AI-powered development research.
Query and understand large codebases with a fast knowledge graph for AI agents.
Search code quickly and accurately while using far fewer tokens.
Query, understand, and edit large multilingual codebases with AI knowledge graphs.