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Build local codebase memory for AI agents with search and architecture inspection.
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.
Connect to codebase-memory-mcp, index the current repository, and summarize the main modules, key entry files, core dependencies, and the role of each directory.
A structured architecture overview that helps quickly understand how the codebase is organized.
Use codebase-memory-mcp to search the repository for code related to user authentication and authorization, then list the relevant files, main functions, and their call relationships.
A list of relevant files and call-chain explanations for easier modification or debugging.
Using codebase-memory-mcp, analyze the repository for tightly coupled modules, identify potentially duplicated implementations, and suggest refactoring priorities.
A refactoring-focused analysis report with risk areas, duplicated logic, and priority recommendations.
Index repositories into a persistent graph for fast code search and understanding.
Build persistent, semantically searchable memory for codebases via natural language queries.
Provide local-first memory and retrieval for coding agents using SQLite embeddings.
Search and navigate multiple code repositories with natural language understanding.
Give AI coding agents long-term memory, search, and organization across sessions.
Give AI coding assistants local long-term memory with searchable lessons and patterns.