Mac Messages MCP Server

What does “Mac Messages” MCP Server do?

Mac Messages MCP Server is an MCP (Model Context Protocol) server designed to securely interface with your iMessage database on macOS. It enables AI assistants and LLMs to query, analyze, and interact with iMessage conversations, providing a bridge between conversational AI and your personal or organizational messaging history. The server offers functionalities such as robust phone number validation, attachment processing, contact management, group chat handling, and supports both sending and receiving messages. By leveraging these capabilities, developers can build advanced workflows, automate message-based tasks, or surface rich message data to enhance productivity tools and other AI-powered applications.

List of Prompts

No prompt templates are explicitly mentioned in the repository or documentation.

List of Resources

No explicit resources (as defined by MCP: server-exposed data/content for LLM context) are documented in the repository.

List of Tools

No explicit list of tools is documented in the repository or in a server.py file. The repo mentions functionalities like querying iMessage conversations, phone number validation, attachment processing, contact management, group chat handling, and sending/receiving messages, which may be exposed as tools, but they are not specifically enumerated as MCP tools in the available documentation.

Use Cases of this MCP Server

• iMessage Database Querying
  Enables AI assistants to search and analyze historical iMessage conversations, making it easier to find specific information, trends, or communication patterns.
• Attachment and Media Processing
  Facilitates the extraction and handling of message attachments (images, files) for downstream processing or summarization by AI models.
• Contact and Group Chat Analysis
  Allows for the organization, management, and querying of contacts and group chats, supporting richer context-aware assistant features.
• Automated Messaging Workflows
  Supports sending and receiving iMessages programmatically, enabling notification bots, reminders, or workflow automation via AI.
• Phone Number Validation and Normalization
  Ensures phone numbers are validated and normalized when interacting with contacts, improving accuracy and reducing errors in communication workflows.

How to set it up

Windsurf

1. Ensure you have Python and Node.js installed on your system.
2. Locate your Windsurf configuration file (typically windsurf.config.json).
3. Add the Mac Messages MCP Server using the following JSON snippet in the mcpServers section:

   {
     "mac-messages-mcp": {
       "command": "mac-messages-mcp",
       "args": []
     }
   }
   

4. Save the configuration file and restart Windsurf.
5. Verify the setup by ensuring the MCP server connects and is available in your Windsurf dashboard.

Claude

1. Ensure Python and Node.js are installed.
2. Open the Claude configuration interface.
3. Add the Mac Messages MCP Server in the MCP servers section:

   {
     "mac-messages-mcp": {
       "command": "mac-messages-mcp",
       "args": []
     }
   }
   

4. Save and restart Claude.
5. Confirm connectivity to the MCP server.

Cursor

1. Install Python and Node.js if not already present.
2. Open your Cursor application settings or configuration file.
3. Insert the following under the MCP servers configuration:

   {
     "mac-messages-mcp": {
       "command": "mac-messages-mcp",
       "args": []
     }
   }
   

4. Save your changes and restart Cursor.
5. Check that the server is available and running.

Cline

1. Make sure Python and Node.js are installed.
2. Access your Cline configuration file.
3. Add the MCP server configuration:

   {
     "mac-messages-mcp": {
       "command": "mac-messages-mcp",
       "args": []
     }
   }
   

4. Save and restart Cline.
5. Validate that the Mac Messages MCP Server is connected.

Securing API Keys

To secure sensitive keys or tokens, use environment variables. In your configuration, reference them like this:

{
  "mac-messages-mcp": {
    "command": "mac-messages-mcp",
    "args": [],
    "env": {
      "IMESSAGE_DB_PATH": "/Users/youruser/Library/Messages/chat.db"
    },
    "inputs": {
      "api_key": "${IMESSAGE_API_KEY}"
    }
  }
}

Replace IMESSAGE_DB_PATH and IMESSAGE_API_KEY with your actual environment variable names.

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "mac-messages-mcp": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change "mac-messages-mcp" to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on these tables, the Mac Messages MCP Server provides a valuable bridge for iMessage data, but lacks detailed documentation about MCP tools, resources, prompts, or agentic sampling/roots support. Usability is high for its main feature, but extensibility and standardization are less well documented.

MCP Score