Neural memory: MCP server, setup and security

What Neural memory does

According to its repository: “Persistent memory for AI agents — 55 MCP tools, spreading activation recall.”

The Model Context Protocol (MCP) is a standard plug between an AI agent and an outside service: once the server is connected, its tools show up in the agent, which decides when to call them. Neural memory is listed under Memory and knowledge, a category of 250 servers in the directory, where it ranks #46 by stars.

Installing and connecting Neural memory

Distribution modes declared in the official MCP registry:

• npm package (Node.js, usually started with npx)

It works with any MCP-compatible client (Claude Desktop, Claude Code, Cursor, VS Code, Codex and most recent agents). You add one entry to the client's MCP configuration: server name, start command or URL, environment variables. Project language: Python.

Security: what to check

Connecting an MCP server means installing software that talks straight to your agent: it runs with your rights and the model trusts its tool descriptions. The risk therefore depends on what it can touch and how far its code can be trusted.

None of the risk signals we track (system access, secrets, missing licence, abandonment) applies to Neural memory. That does not replace reading the code.

Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.

Project activity and maintenance

Created on February 4, 2026, the nhadaututtheky/neural-memory repository has 242 stars and 69 forks, with 0 open issues. It has more stars than 80% of the servers in the directory. It received changes this month. Version published in the registry: 4.27.2 (April 2, 2026).

Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.