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Build persistent, semantically searchable memory for codebases via natural language queries.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "memory-bank-mcp" yet — see the docs or source repo.
Connect to memory-bank-mcp and find the core modules related to user login, token refresh, and permission checks in this codebase. List the file paths and summarize each module's responsibility.
Returns relevant file paths, semantic matches, and a summary of each module’s role in the auth flow.
Use memory-bank-mcp to analyze the implementation path of the “export reports” feature, from frontend entry points to backend APIs and data processing logic, and summarize it step by step.
Outputs located code segments related to the feature and organizes the implementation path by call relationships.
Using memory-bank-mcp’s code memory capabilities, summarize the project’s main architecture, key services, common naming patterns, and the files worth reading first.
Generates a newcomer-friendly project overview that helps build a quick mental model of the codebase.
Manage remote AI memory banks for persistent context and project knowledge.
Lightweight vector memory for AI agents to store, search, and delete memories.
Index repositories into a persistent graph for fast code search and understanding.
Build local codebase memory for AI agents with search and architecture insights.
Persistent knowledge-graph memory for MCP with semantic search and version tracking.
Give AI coding tools persistent memory across sessions, devices, and workflows.