An MCP memory server gives AI agents tools for storing and retrieving memories through the Model Context Protocol. That gives Claude Code, Codex and other MCP-capable tools one shared memory. What matters is that the server doesn't just store, but recalls on its own and understands connections.
What is MCP?
The Model Context Protocol (MCP) is an open standard for connecting AI applications to tools and data sources. Anthropic introduced it in late 2024, and numerous AI tools now support it, including Claude Code and Codex. Think of MCP as a USB port for AI: build it once, plug it in anywhere.
What is an MCP memory server?
An MCP memory server is a memory service that offers its functions through MCP. The agent gets tools like "store memory" or "search memories" and can use them while it works. The result: knowledge survives the end of the session.
The big advantage of MCP: one memory can be used by several tools at the same time. What Claude Code learns is available to Codex too.
Types of MCP memory servers
- File- and note-based: Memories end up as text in files, much like a memory bank. Simple, but flat.
- Vector-based: Memories are stored as vectors and searched by meaning. Finds what is similar, but not necessarily what belongs together.
- Graph-based: A graph memory stores things and their relationships. That lets the memory understand connections.
The weak spot of many MCP memory solutions
Most MCP memory servers are passive. They wait for the agent to think of querying them. In practice that happens too rarely: the agent is busy with the task, and the decisive memory sits unused in storage. A memory you have to ask first gets forgotten.
What to look for in an MCP memory server
- More than MCP tools? Only an additional integration, for example through hooks, lets the memory recall on its own.
- Ready-made integration? Is there a finished integration for your agents, or just the bare protocol?
- Central access? Can several machines and people share one memory, with permissions per agent?
- Lean on context? How many tokens land per call, and can you measure it?
You'll find the general criteria for any AI memory in the AI memory guide.
Hebby: more than an MCP memory server
Hebby speaks MCP and goes further. For Claude Code and Codex, Hebby is ready-made and runs along automatically in every session. It brings up what matters right now on its own and anticipates what will be needed next. Underneath works a graph memory built in-house that learns by the Hebbian principle. One memory for all your agents, modeled on the human brain.
Hebby Memories: the second brain for Claude Code, Codex & co. Learns as you work, thinks ahead, never forgets what matters. Get Early Access →
Frequently asked questions
What is MCP?
The Model Context Protocol is an open standard that AI applications use to talk to external tools and data sources. An MCP server gives the agent functions it can call while it works.
What does an MCP memory server do?
It gives an AI agent tools to store, search and retrieve memories. That way the agent keeps knowledge beyond a single session.
Does Hebby work with MCP?
Yes. Hebby offers an MCP interface and is also ready-made for Claude Code and Codex, so it runs along automatically in every session.