agent-memory-mcp

Persistent memory for AI agents is provided through an MCP-based server with read, write, and search APIs. It captures and retrieves knowledge across projects, enabling memory-based reasoning and continuity over time.

An MCP memory server stores and retrieves knowledge for AI agents using APIs like memory_search, memory_write, memory_read, and memory_stats. It acts as a persistent memory bank that syncs with project documentation for long-term context.

Yes, persistent agent memory supports task tracking and knowledge reuse. It allows AI agents to recall architectural decisions and patterns across sessions, informing new tasks and maintaining long-term project context.

Yes, Node.js v18 or higher is required to run this MCP memory server. You clone the repository into your workspace, install dependencies, and start the server to enable read/write/search operations for your agents.

The best way to search captured memories is using the memory_search API provided by the MCP server. This allows AI agents to query the persistent knowledge store and retrieve relevant historical context across projects.

The persistent memory bank is designed for teams building agents requiring long-term context. It provides a simple dashboard and core APIs, but scalability depends on your Node.js environment and project documentation sync requirements.