agent-memory-mcp

To persist AI agent memories across projects, you need a dedicated memory store offering APIs to write, read, and search accumulated knowledge. This centralizes scattered data to keep it accessible and reusable.

The best way to search stored AI memories by keywords or tags is using a memory store with a dedicated search API. It allows querying specific memories by text, type, or tags to retrieve relevant project decisions quickly.

To set up a persistent memory server for AI agents in Node.js, start the MCP server using `npm run start-server <project_id> <absolute_path_to_target_workspace>`. This provides a self-contained environment to manage your memories.

Yes, you can use a dedicated dashboard for AI memory and knowledge management to gain analytics and oversight across projects. It centralizes the visualization of patterns and documentation stored by agents across teams.

This AI memory persistence approach works as a self-contained setup without external dependencies. It provides modular API capabilities for storing and retrieving agent decisions directly within your Node.js environment.