What permissions are required to use imessage-gateway?

The terminal running Claude Code must be granted 'Full Disk Access' in macOS System Settings to read the iMessage database.

Does this skill work on Windows or Linux?

No, this skill requires macOS as it interacts directly with the native Messages.app database and local storage.

Is there a performance difference compared to standard MCP servers?

Yes, imessage-gateway is optimized for speed and is up to 19 times faster than traditional MCP implementations for listing contacts and finding messages.

Can I message people who are not in my contact list?

Yes, you can use the 'send-by-phone' command to send iMessages directly to any phone number.

How does the semantic search feature work?

It uses Retrieval-Augmented Generation (RAG) to index your messages locally, allowing you to ask natural language questions about your chat history.

iMessage Gateway

Name: iMessage Gateway
Author: wolfiesch

bywolfiesch

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协作工具

Manages iMessage communication directly from the terminal with high-performance retrieval and semantic search capabilities.

关于

The imessage-gateway skill provides a powerful command-line interface for iMessage on macOS, enabling users to send, read, and analyze messages without leaving their development environment. It features advanced semantic search (RAG) capabilities to query conversation history, perform analytics on contact interactions, and manage group chats. Engineered for speed, it operates significantly faster than traditional MCP implementations, making it an essential tool for developers who want to integrate their personal or professional communication workflows into their AI coding assistant.

主要功能

Lightning-fast message retrieval and contact management optimized for CLI
Automated analytics for follow-ups, handle discovery, and interaction stats
Fuzzy-matching for contact names and group message management
Full support for attachments, voice notes, and shared links
1 GitHub stars
Semantic search (RAG) to find specific information across conversation history

使用场景

Identifying contacts that require follow-ups based on communication gaps
Asking AI to find specific details or summarize long conversation threads
Responding to messages or checking thread history without switching away from your IDE

关于

主要功能

Lightning-fast message retrieval and contact management optimized for CLI
Automated analytics for follow-ups, handle discovery, and interaction stats
Fuzzy-matching for contact names and group message management
Full support for attachments, voice notes, and shared links
1 GitHub stars
Semantic search (RAG) to find specific information across conversation history

使用场景

Identifying contacts that require follow-ups based on communication gaps
Asking AI to find specific details or summarize long conversation threads
Responding to messages or checking thread history without switching away from your IDE