Memory MCP
About
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.
Details
- Author
- drdee
- GitHub stars
- 10
- Downloads
- 306
- Categories
- Knowledge Base
Jump to
- 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
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Memory MCPCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
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.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"memory mcp": {
"memory-mcp": {
"command": "uv",
"args": [
"pip",
"install",
"memory-mcp"
]
}
}
}
}McpServers
{
"memory-mcp": {
"command": "uv",
"args": [
"pip",
"install",
"memory-mcp"
]
}
}Memory MCP
A Model Context Protocol server for storing and retrieving memories using low-level Server implementation and SQLite storage.
Installation
This project uses uv for dependency management instead of pip. uv is a fast, reliable Python package installer and resolver.
Install using uv:
uv pip install memory-mcp
Or install directly from source:
uv pip install .
For development:
uv pip install -e ".[dev]"
If you don't have uv installed, you can install it following the official instructions.
Usage
Running the server
memory-mcp
This will start the MCP server that allows you to store and retrieve memories.
Available Tools
The Memory MCP provides the following tools:
- remember: Store a new memory with a title and content
- get_memory: Retrieve a specific memory by ID or title
- list_memories: List all stored memories
- update_memory: Update an existing memory
- delete_memory: Delete a memory
Debugging with MCP Inspect
MCP provides a handy command-line tool called mcp inspect that allows you to debug and interact with your MCP server directly.
Setup
1. First, make sure the MCP CLI tools are installed:
uv pip install mcp[cli]
2. Start the Memory MCP server in one terminal:
memory-mcp
3. In another terminal, connect to the running server using mcp inspect:
mcp inspect
Using MCP Inspect
Once connected, you can:
List available tools
> tools
This will display all the tools provided by the Memory MCP server.
Call a tool
To call a tool, use the call command followed by the tool name and any required arguments:
> call remember title="Meeting Notes" content="Discussed project timeline and milestones."
> call list_memories
> call get_memory memory_id=1
> call update_memory memory_id=1 title="Updated Title" content="Updated content."
> call delete_memory memory_id=1
Debug Mode
You can enable debug mode to see detailed request and response information:
> debug on
This helps you understand exactly what data is being sent to and received from the server.
Exploring Tool Schemas
To view the schema for a specific tool:
> tool remember
This shows the input schema, required parameters, and description for the tool.
Troubleshooting
If you encounter issues:
1. Check the server logs in the terminal where your server is running for any error messages.
2. In the MCP inspect terminal, enable debug mode with debug on to see raw requests and responses.
3. Ensure the tool parameters match the expected schema (check with the tool command).
4. If the server crashes, check for any uncaught exceptions in the server terminal.
Development
To contribute to the project, install the development dependencies:
uv pip install -e ".[dev]"
Managing Dependencies
This project uses uv.lock file to lock dependencies. To update dependencies:
uv pip compile pyproject.toml -o uv.lock
Running tests
python -m pytest
Code formatting
black memory_mcp tests
Linting
ruff check memory_mcp tests
Type checking
mypy memory_mcp
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