Memos MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Memos MCP Serversearch for memos tagged 'meeting' from last week"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Memos MCP Server
An MCP (Model Context Protocol) server that provides tools for interacting with a Memos instance. This server allows AI assistants to search, create, and update memos through the Memos API.
Features
Search Memos: Search for memos with filters like creator, tags, visibility, and content
Create Memos: Create new memos with markdown support
Update Memos: Update existing memos (content, visibility, pinned status)
Get Memo: Retrieve a specific memo by UID
Related MCP server: MCP Server for Mem.ai
Installation
Clone this repository:
git clone <repository-url>
cd memos_mcpInstall dependencies:
Using uv (recommended)
uv syncUsing pip
pip install -r requirements.txtConfiguration
Set the following environment variables:
MEMOS_BASE_URL: The base URL of your Memos instance (default:http://localhost:5230)MEMOS_API_TOKEN: Your Memos API authentication token (optional for public instances)
Getting an API Token
Log into your Memos instance
Go to Settings → Access Tokens
Create a new access token
Copy the token and set it as the
MEMOS_API_TOKENenvironment variable
Example:
export MEMOS_BASE_URL="https://memos.example.com"
export MEMOS_API_TOKEN="your-token-here"Usage
Running the Server
Using uvx (no installation required)
# Run directly with uvx
uvx --from . memos-mcpUsing uv after installation
# After running 'uv sync'
uv run memos-mcpUsing FastMCP directly
fastmcp run server.pyProgrammatic usage
from server import mcp
# The server is ready to useAvailable Tools
1. search_memos
Search for memos with optional filters.
Parameters:
query(optional): Text to search for in memo contentcreator_id(optional): Filter by creator user IDtag(optional): Filter by tag namevisibility(optional): Filter by visibility (PUBLIC, PROTECTED, PRIVATE)limit(default: 10): Maximum number of resultsoffset(default: 0): Number of results to skip
Example:
result = await search_memos(query="meeting notes", limit=5)2. create_memo
Create a new memo.
Parameters:
content: The content of the memo (supports Markdown)visibility(default: PRIVATE): Visibility level (PUBLIC, PROTECTED, PRIVATE)
Example:
result = await create_memo(
content="# Meeting Notes\n\n- Discuss project timeline\n- Review budget",
visibility="PRIVATE"
)3. update_memo
Update an existing memo.
Parameters:
memo_uid: The UID of the memo to updatecontent(optional): New content for the memovisibility(optional): New visibility levelpinned(optional): Whether to pin the memo
Example:
result = await update_memo(
memo_uid="abc123",
content="Updated content",
pinned=True
)4. get_memo
Get a specific memo by its UID.
Parameters:
memo_uid: The UID of the memo to retrieve
Example:
result = await get_memo(memo_uid="abc123")Integration with MCP Clients
Claude Desktop
Add to your Claude Desktop configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Using uvx (recommended - no installation needed)
{
"mcpServers": {
"memos": {
"command": "uvx",
"args": ["--from", "/path/to/memos_mcp", "memos-mcp"],
"env": {
"MEMOS_BASE_URL": "http://localhost:5230",
"MEMOS_API_TOKEN": "your-token-here"
}
}
}
}Using uv (after installation)
{
"mcpServers": {
"memos": {
"command": "uv",
"args": ["run", "--directory", "/path/to/memos_mcp", "memos-mcp"],
"env": {
"MEMOS_BASE_URL": "http://localhost:5230",
"MEMOS_API_TOKEN": "your-token-here"
}
}
}
}Using Python directly
{
"mcpServers": {
"memos": {
"command": "python",
"args": ["-m", "fastmcp", "run", "/path/to/memos_mcp/server.py"],
"env": {
"MEMOS_BASE_URL": "http://localhost:5230",
"MEMOS_API_TOKEN": "your-token-here"
}
}
}
}API Reference
This server is built on the Memos API v1. The API follows Google's API Improvement Proposals (AIPs) design guidelines.
API Endpoints Used
GET /api/v1/memos- List/search memosPOST /api/v1/memos- Create a memoGET /api/v1/memos/{uid}- Get a specific memoPATCH /api/v1/memos/{uid}- Update a memo
Authentication
The server supports Bearer token authentication. Include your access token in the Authorization header:
Authorization: Bearer your-token-hereDevelopment
Running Tests
pytestCode Structure
server.py: Main MCP server implementation with all toolsrequirements.txt: Python dependencies
About Memos
Memos is a lightweight, self-hosted memo hub with knowledge management and social networking features. Learn more at:
Website: https://www.usememos.com/
License
MIT License - see LICENSE file for details
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- Alicense-qualityDmaintenanceEnables AI agents to interact with Memos instances for personal note-taking and knowledge management. Supports creating, searching, updating, and organizing memos with tags, dates, and visibility settings through natural language.MIT
- Alicense-qualityDmaintenanceEnables AI assistants to intelligently save, organize, and retrieve content through Mem.ai's knowledge management platform. Supports creating notes, collections, and AI-powered content processing with automatic organization.4MIT
- Alicense-qualityDmaintenanceEnables AI assistants to create, read, update, delete, and list memos via the MCP protocol.3MIT
- FlicenseAqualityDmaintenanceConnects to Memos note-taking service to read, write, search, filter, and manage memos, including creating comments and managing users.81
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