Memory MCP Server

@drdee

Basic information

About Memory MCP Server

An mcp server that you can use to store and retrieve ideas, prompt templates, personal preferences to use with you favourite AI tool that supports the modelcontextprovider protocol.

Memory MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "memory-mcp": {
      "command": "uv",
      "args": [
        "pip",
        "install",
        "memory-mcp"
      ]
    }
  }
}

Memory MCP Server tools

Store a new memory with a title and content

Retrieve a specific memory by ID or title

List all stored memories

Update an existing memory

Delete a memory

Overview

What is Memory MCP?

Memory MCP is a Model Context Protocol server for storing and retrieving memories using a low-level server implementation and SQLite storage. It is designed for developers who want to add persistent memory capabilities to MCP-compatible agents or applications.

How to use Memory MCP?

Install the package via uv pip install memory-mcp (or from source with uv pip install .). Run the server by executing the memory-mcp command. For debugging, use the MCP Inspect CLI tool to list, call, and inspect tools.

Key features of Memory MCP

Five CRUD tools: remember, get_memory, list_memories, update_memory, delete_memory
Persistent storage backed by SQLite
Debug and inspect via mcp inspect with debug mode
Dependency management with uv for fast, reliable resolution
Lightweight implementation using the Model Context Protocol

Use cases of Memory MCP

Storing and recalling meeting notes or project updates
Building a personal memory database for chatbot assistants
Prototyping memory-backed AI agents with MCP tool integration
Providing long-term context for conversational applications

Frequently asked questions

How do I install Memory MCP?

Install using `uv pip install memory-mcp`. If you don't have `uv`, follow the official installation instructions at https://github.com/astral-sh/uv#installation.

How do I run the server?

Run `memory-mcp` in your terminal. This starts the MCP server that exposes the five memory tools.

What tools are available?

The server provides `remember`, `get_memory`, `list_memories`, `update_memory`, and `delete_memory`. Each has specific parameters; use `mcp inspect` to see their schemas.

How can I debug the server?

Use the MCP Inspect CLI tool (`mcp inspect`) after installing `mcp[cli]` via `uv pip install mcp[cli]`. Connect to the running server and use commands like `tools`, `call`, and `debug on`.

How do I update dependencies?

This project uses a `uv.lock` file. Run `uv pip compile pyproject.toml -o uv.lock` to regenerate it after changing dependencies.

Comments

More Memory & Knowledge MCP servers

Context7 MCP - Up-to-date Docs For Any Cursor Prompt

upstash

Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors

58.7K

Codebase Memory

DeusData

High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 162 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.

46.7K

The Cloud

Teka

The Cloud is the AI-native workspace that gives every AI — Claude, ChatGPT, Gemini, and other Frontier & Free or Local models — shared memory and real agents. Not cloud computing: thecloud.so is one workspace where your

server-noonien - shared memory MCP

sequico

Shared, serverless, conflict-free memory for AI agents: a multi-machine drop-in for the MCP memory knowledge graph.

ctxfile

Local-first MCP server that snapshots your project's working state into one context object. Open-core, privacy-first.