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Index repositories into a persistent graph for fast code search and understanding.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "codebase-memory-mcp" yet — see the docs or source repo.
Using the current repository index, map the call relationships between the authentication and authorization modules. List the key files, core functions, and dependency paths.
A structured overview of the auth modules, key code locations, and summarized call chains.
Based on the indexed codebase, explain how caching is implemented in this project, including entry points, main classes or functions, and cache invalidation logic.
A concise explanation of the caching implementation with references to relevant files and functions.
Create an onboarding guide for a new developer covering the project structure, core services, main tech stack, and recommended files to read first.
An onboarding-oriented codebase guide with a recommended learning path.
Index, search, analyze, and monitor codebases for faster understanding and troubleshooting.
Build local codebase memory for AI agents with search and architecture inspection.
Build persistent, semantically searchable memory for codebases via natural language queries.
Analyze codebases with semantic search, dependency insights, and natural language Q&A.
Index a monorepo into a graph for fast code structure queries.
Index codebases into a searchable graph for structure, calls, and routes.