GitHub - MemTensor/memos-api-mcp: A Model Context Protocol (MCP) implementation for the Memos API service. This package provides a command-line interface to interact with Memos API using MCP standards. (original) (raw)

MCP Server for MemOS API

A Model Context Protocol (MCP) implementation for the MemOS API service. This package provides a command-line interface to interact with MemOS API using MCP standards.

MCP Configuration

To use this package In MCP Client, use the following configuration: （You may need to install Node.js first）

{ "mcpServers": { "memos-api-mcp": { "command": "npx", "args": ["-y", "@memtensor/memos-api-mcp"], "env": { "MEMOS_API_KEY": "your-api-key", "MEMOS_USER_ID": "your-user-id", "MEMOS_CHANNEL": "the-site-where-you-are-seeing-this-document" } } } }

Configuration Explanation

• command: Uses npx to run the package
• args: Arguments passed to npx to run the package
• env: Environment variables
  • MEMOS_API_KEY: Your Memos API key for authentication (Get your API Key in Dashboard[https://memos-dashboard-pre.openmem.net/cn/quickstart/])
  • MEMOS_USER_ID: Stable per-human identifier. MUST be deterministic and non-PII, and MUST remain the same for the same person across devices/sessions. NEVER reuse across different people. DO NOT use random values, device IDs, or model/chat session IDs. Recommended: SHA-256(lowercase(trim(email))) or your SSO subject/employee ID.
  • MEMOS_CHANNEL: The site where you are seeing this document. Candidate values: MODELSCOPE, MCPSO, MCPMARKETCN, MCPMARKETCOM, GLAMA, PULSEMCP, MCPSERVERS,LOBEHUB,MEMOS(meaning the MemOS official website), GITHUB(meaning this README file)

Available MCP Tools

This package provides the following MCP tools:

1. add_message
   • Adds a new message to a conversation
   • Parameters:
     * conversation_id: Conversation ID to identify which conversation the message belongs to
     * messages: Array of messages containing role and content information
     * role: Role of the message sender, e.g., user, assistant
     * content: Message content
2. search_memory
   • Searches for memories in a conversation
   • Parameters:
     * query: Search query to find relevant content in conversation history
     * conversation_id: Conversation ID to define the search scope
     * memory_limit_number: Maximum number of results to return, defaults to 6
3. get_message
   • Retrieves messages from a conversation
   • Parameters:
     * conversation_id: Conversation ID to identify which conversation's messages to retrieve

All tools use the same configuration and require the MEMOS_API_KEY environment variable.

Features

• MCP-compliant API interface
• Command-line tool for easy interaction
• Built with TypeScript for type safety
• Express.js server implementation
• Zod schema validation

Prerequisites

• Node.js >= 18
• npm or pnpm (recommended)

Installation

You can install the package globally using npm:

npm install -g @memtensor/memos-api-mcp

Or using pnpm:

pnpm add -g @memtensor/memos-api-mcp

Usage

After installation, you can run the CLI tool using:

npx @memtensor/memos-api-mcp

Or if installed globally:

Development

1. Clone the repository:

git clone cd memos-api-mcp

1. Install dependencies:
2. Start development server:
3. Build the project:

Available Scripts

• pnpm build - Build the project
• pnpm dev - Start development server using tsx
• pnpm start - Run the built version
• pnpm inspect - Inspect the MCP implementation using @modelcontextprotocol/inspector

Project Structure

memos-mcp/
├── src/           # Source code
├── build/         # Compiled JavaScript files
├── package.json   # Project configuration
└── tsconfig.json  # TypeScript configuration

Dependencies

• @modelcontextprotocol/sdk: ^1.0.0
• express: ^4.19.2
• zod: ^3.23.8
• ts-md5: ^2.0.0

Version

Current version: 1.0.0-beta.2