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@hskksk/mem-ai-mcp-server

v0.2.0

Published

MCP server for mem.ai API integration

Readme

mem.ai MCP Server

npm version License: MIT

Model Context Protocol (MCP) server for mem.ai API integration. This server enables AI assistants like Claude to interact with your mem.ai memory through a standardized interface.

Features

  • Complete API Coverage: All 11 mem.ai API endpoints wrapped as MCP tools
  • TypeScript: Fully typed with strict mode enabled
  • Easy Integration: Works seamlessly with Claude Desktop and other MCP clients
  • Error Handling: Comprehensive error handling with detailed messages
  • Validation: Input validation using Zod schemas

Installation

No installation required! You can run the server directly using npx (recommended), or install it globally if you prefer.

Using npx (Recommended)

npx @hskksk/mem-ai-mcp-server

This automatically downloads and runs the latest version without requiring installation.

Global Installation (Optional)

npm install -g @hskksk/mem-ai-mcp-server

Configuration

Get Your API Key

  1. Visit mem.ai settings
  2. Generate a new API key
  3. Copy the key for configuration

Environment Variables

Create a .env file or set environment variables:

MEM_API_KEY=your_api_key_here

Optional configuration:

# Override the default API base URL (default: https://api.mem.ai)
MEM_API_BASE_URL=https://api.mem.ai

Usage

With Claude Desktop (Recommended)

Add the following configuration to your Claude Desktop config file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "mem-ai": {
      "command": "npx",
      "args": ["-y", "@hskksk/mem-ai-mcp-server"],
      "env": {
        "MEM_API_KEY": "your_api_key_here"
      }
    }
  }
}

After restarting Claude Desktop, you'll be able to use mem.ai tools in your conversations.

Alternative: Using Global Installation

If you've installed the package globally:

{
  "mcpServers": {
    "mem-ai": {
      "command": "mem-ai-mcp-server",
      "env": {
        "MEM_API_KEY": "your_api_key_here"
      }
    }
  }
}

Standalone Usage

# Using npx (recommended)
MEM_API_KEY=your_api_key_here npx @hskksk/mem-ai-mcp-server

# Or if installed globally
MEM_API_KEY=your_api_key_here mem-ai-mcp-server

Available Tools

Mem It

  • mem_it - Remember any content intelligently
    • Primary endpoint for saving information to mem.ai
    • Supports context and instructions for better processing
    • Parameters: input (required), instructions, context, timestamp

Notes Management

  • create_note - Create a new note with markdown content

    • Parameters: content (required), id, collection_ids, collection_titles, created_at, updated_at
  • get_note - Retrieve a specific note by ID

    • Parameters: noteId (required)
  • delete_note - Delete a note

    • Parameters: noteId (required)
  • list_notes - List all notes with advanced filtering and pagination

    • Supports cursor-based pagination with page and next_page
    • Parameters:
      • limit - Maximum number of results (default: 50, max: 100)
      • page - Cursor for pagination (from previous next_page)
      • order_by - Sort order: created_at or updated_at (default: updated_at)
      • collection_id - Filter by collection ID
      • contains_open_tasks - Filter notes with open tasks
      • contains_tasks - Filter notes with any tasks
      • contains_images - Filter notes with images
      • contains_files - Filter notes with files/attachments
      • include_note_content - Include full markdown content in response
  • search_notes - Search across notes with advanced filtering

    • Parameters:
      • query - Search query (optional)
      • filter_by_collection_ids - Filter by collection IDs array
      • filter_by_contains_open_tasks - Filter notes with open tasks
      • filter_by_contains_tasks - Filter notes with any tasks
      • filter_by_contains_images - Filter notes with images
      • filter_by_contains_files - Filter notes with files
      • config - Response configuration (include_snippet, include_content)

Collections Management

  • create_collection - Create a new collection

    • Parameters: title (required), description
  • get_collection - Retrieve a specific collection by ID

    • Parameters: collectionId (required)
  • delete_collection - Delete a collection

    • Parameters: collectionId (required)
  • list_collections - List all collections with pagination

    • Supports cursor-based pagination with page and next_page
    • Parameters:
      • limit - Maximum number of results (default: 50, max: 100)
      • page - Cursor for pagination (from previous next_page)
      • order_by - Sort order: created_at or updated_at (default: updated_at)
  • search_collections - Search across collections

    • Parameters:
      • query - Search query (optional)
      • config - Response configuration (include_description)

Development

Prerequisites

  • Node.js >= 20.0.0
  • pnpm (recommended) or npm

Setup

# Clone the repository
git clone https://github.com/hskksk/mem-ai-mcp-server.git
cd mem-ai-mcp-server

# Install dependencies
pnpm install

# Copy environment template
cp .env.example .env

# Edit .env and add your API key

Development Commands

# Run in development mode with auto-reload
pnpm dev

# Build the project
pnpm build

# Run tests
pnpm test

# Type check
pnpm type-check

# Lint
pnpm lint

Project Structure

src/
├── index.ts              # Entry point
├── server.ts             # MCP server setup
├── config/
│   └── env.ts           # Environment configuration
├── client/
│   └── mem-api-client.ts # mem.ai API client
├── tools/               # MCP tool implementations
│   ├── base-tool.ts
│   ├── mem-it.ts
│   ├── notes/
│   └── collections/
├── types/               # TypeScript type definitions
└── utils/               # Utility functions

API Documentation

For detailed information about the mem.ai API, visit the official API documentation.

Error Handling

The server provides detailed error messages for common issues:

  • 401 Unauthorized: Invalid API key
  • 404 Not Found: Resource not found
  • 429 Too Many Requests: Rate limit exceeded
  • 500 Server Error: Internal server error

All errors are returned in a structured format for easy debugging.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Links

Support

If you encounter any issues or have questions:

  1. Check the GitHub Issues
  2. Create a new issue with detailed information
  3. Refer to the mem.ai API documentation

Changelog

See CHANGELOG.md for the full version history.