Memos MCP Server
Click on "Deploy 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 Server search 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: memos-mcp-server
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.
Available Tools
4 toolscreate_memoB
Create a new memo.
Args: content: The content of the memo (supports Markdown) visibility: Visibility level - PUBLIC, PROTECTED, or PRIVATE (default: PRIVATE)
Returns: JSON string containing the created memo details
Inputs: content (required), visibility. Returns: result
get_memoA
Get a specific memo by its UID.
Args: memo_uid: The UID of the memo to retrieve (e.g., "abc123")
Returns: JSON string containing the memo details
Inputs: memo_uid (required). Returns: result
search_memosA
Search for memos with optional filters.
Args: query: Text to search for in memo content creator_id: Filter by creator user ID tag: Filter by tag name visibility: Filter by visibility (PUBLIC, PROTECTED, PRIVATE) limit: Maximum number of results to return (default: 10) offset: Number of results to skip (default: 0)
Returns: JSON string containing the list of matching memos
Inputs: query, creator_id, tag, visibility, +2 more. Returns: result
update_memoB
Update an existing memo.
Args: memo_uid: The UID of the memo to update (e.g., "abc123") content: New content for the memo (optional) visibility: New visibility level - PUBLIC, PROTECTED, or PRIVATE (optional) pinned: Whether to pin the memo (optional)
Returns: JSON string containing the updated memo details
Inputs: memo_uid (required), content, visibility, pinned. Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose with no overlap: create_memo for creation, get_memo for retrieval by UID, search_memos for filtered searching, and update_memo for modifications. The actions (create, get, search, update) target the same resource (memos) but operate in non-overlapping ways, making misselection unlikely.
All tool names follow a consistent verb_noun pattern with 'memo' as the noun: create_memo, get_memo, search_memos, update_memo. The pattern is uniform throughout, using snake_case and clear action verbs, making the set predictable and easy to understand.
With 4 tools, this server is well-scoped for a memos management system. Each tool earns its place by covering essential CRUD operations (create, get, update) plus search functionality, which is appropriate for the domain without being overly sparse or bloated.
The tool set covers core CRUD operations (create, get, update) and search, but lacks a delete_memo tool for full lifecycle coverage. This minor gap might require workarounds for deletion tasks, though the existing tools support most common workflows effectively.
Maintenance
Related MCP Connectors
Securely search, create, and organize your Mem notes and collections from AI assistants.
Connect AI to your flomo notes. Search, create, edit notes and manage tags via MCP.
Search, read, create and edit your Memol notes from Claude. Team note-taking with AI search.
Persistent cloud memory for AI agents. Store and search key-value memories across sessions.
Related MCP Servers
- AlicenseNot gradedqualityDmaintenanceEnables 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
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to create, read, update, delete, and list memos via the MCP protocol.3MIT
- AlicenseAqualityDmaintenanceConnects to Memos note-taking service to read, write, search, filter, and manage memos, including creating comments and managing users.81MIT
- FlicenseAqualityDmaintenanceEnables to interact with Memos note-taking service, allowing search, creation, retrieval, and updating of notes through natural language.49 npm4-