Codegraph is a local codebase indexer and static analysis graph database that serves as a context provider for AI agents. It parses multiple programming languages into a searchable knowledge graph of symbols and dependencies, exposing these relationships to AI tools through the Model Context Protocol.
The project distinguishes itself by aggregating relevant code snippets and symbol flows to reduce token usage for large language models. It automates the configuration of server settings and steering instructions across various AI agent platforms and command line editors to enable automatic codebase navigation.
The system covers broad capability areas including transitive dependency impact analysis, execution flow tracing, and framework route mapping. It utilizes a background daemon for incremental parsing and filesystem synchronization, ensuring the local symbol database remains current across multi-repo workspaces.
The application is delivered as a self-contained bundle to ensure environment consistency on host systems.
