Memory MCP
@drdee
关于 Memory MCP
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.
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"memory-mcp": {
"command": "uv",
"args": [
"pip",
"install",
"memory-mcp"
]
}
}
}工具
5Store 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
概览
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 inspectwith debug mode - Dependency management with
uvfor 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
FAQ from Memory MCP
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.
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