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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:

{ "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,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:

memos-api-mcp

Development

  1. Clone the repository:

git clone <repository-url> cd memos-api-mcp
  1. Install dependencies:

pnpm install
  1. Start development server:

pnpm dev
  1. Build the project:

pnpm build

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

-
security - not tested
A
license - permissive license
-
quality - not tested

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/endxxxx/MemOS'

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