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Index local repositories into a queryable graph for AI code understanding.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "CodeGraphContext" yet — see the docs or source repo.
Using the indexed code graph, identify which core services the payment module depends on and explain their call relationships.
A list of related services, dependency paths, and an explanation of call relationships.
Search the code graph for the main implementation entry points of the user login feature, including controllers, service layers, and key data models.
The main entry files, related classes and methods, and key connected objects.
If I modify the order status field, analyze which modules, APIs, and database-related code may be affected based on the code graph.
The likely impact scope, upstream and downstream dependencies, and code areas that need closer review.
Index codebases with AST awareness and retrieve code context via semantic search.
Gives AI coding agents semantic code graphs for faster, more precise answers.
Query, understand, and edit large multilingual codebases with AI knowledge graphs.
Query and understand large codebases with a fast knowledge graph for AI agents.
Index local codebases for fast AI-powered cross-repository code search.
Run local semantic search and call graph analysis across codebases.