imessage-query
An MCP server that provides safe access to your iMessage database through Model Context Protocol (MCP). This server is built with the FastMCP framework and the imessagedb library, enabling LLMs to query and analyze iMessage conversations with proper phone number validation and attachment handling.
iMessage Query MCP Server
An MCP server that provides safe access to your iMessage database through Model Context Protocol (MCP). This server is built with the FastMCP framework and the imessagedb library, enabling LLMs to query and analyze iMessage conversations with proper phone number validation and attachment handling.
📋 System Requirements
- macOS (required for iMessage database access)
- Python 3.6+
📦 Dependencies
Install all required dependencies:
# Using pip
pip install -r requirements.txt
Required Packages
- fastmcp: Framework for building Model Context Protocol servers
- imessagedb: Python library for accessing and querying the macOS Messages database
- phonenumbers: Google's phone number handling library for proper number validation and formatting
All dependencies are specified in requirements.txt for easy installation.
📑 Table of Contents
- System Requirements
- Dependencies
- MCP Tools
- Getting Started
- Installation Options
- Safety Features
- Development Documentation
- Environment Variables
🛠️ MCP Tools
The server exposes the following tools to LLMs:
get_chat_transcript
Retrieve message history for a specific phone number with optional date filtering. Includes:
- Message text and timestamps
- Attachment information (if any)
- Proper phone number validation
- Date range filtering
🚀 Getting Started
Clone the repository:
git clone https://github.com/hannesrudolph/imessage-query-fastmcp-mcp-server.git
cd imessage-query-fastmcp-mcp-server
📦 Installation Options
You can install this MCP server in either Claude Desktop or the Cline VSCode plugin. Choose the option that best suits your needs.
Option 1: Install for Claude Desktop
Install using FastMCP:
fastmcp install imessage-query-server.py --name "iMessage Query"
Option 2: Install for Cline VSCode Plugin
To use this server with the Cline VSCode plugin:
- In VSCode, click the server icon (☰) in the Cline plugin sidebar
- Click the "Edit MCP Settings" button (✎)
- Add the following configuration to the settings file:
{
"imessage-query": {
"command": "uv",
"args": [
"run",
"--with",
"fastmcp",
"fastmcp",
"run",
"/path/to/repo/imessage-query-server.py"
]
}
}
Replace /path/to/repo with the full path to where you cloned this repository (e.g., /Users/username/Projects/imessage-query-fastmcp-mcp-server)
🔒 Safety Features
- Read-only access to the iMessage database
- Phone number validation using the phonenumbers library
- Safe attachment handling with missing file detection
- Date range validation
- Progress output suppression for clean JSON responses
📚 Development Documentation
The repository includes documentation files for development:
dev_docs/imessagedb-documentation.txt: Contains comprehensive documentation about the iMessage database structure and the imessagedb library's capabilities.
This documentation serves as context when developing features and can be used with LLMs to assist in development.
⚙️ Environment Variables
No environment variables are required as the server automatically locates the iMessage database in the default macOS location.
Recommend MCP Servers 💡
dicom-mcp
Model Context Protocol (MCP) for interacting with dicom servers (PACS etc.)
fuel-mcp-server
MCP server for Fuel Network and Sway Language ecosystem enabling IDE integration with Fuel documentation
agentrpc
AgentRPC is a universal RPC layer for AI agents, enabling them to connect to any function in any language across network boundaries. It wraps your functions in a universal RPC interface and provides a hosted Model Context Protocol (MCP) server, ideal for integrating services deployed in private VPCs, Kubernetes clusters, or multiple cloud environments.
NearbySearch
An MCP server for nearby place searches with IP-based location detection.
Gemini Email Generator
An MCP server that uses Google's Gemini Flash 2 AI to generate email subjects and detailed thinking processes, designed for seamless integration with Claude Desktop.
TAM-MCP-Server
An MCP server for market sizing analysis, TAM/SAM calculations, and industry research, built with TypeScript and Express.js.