imessage-analysis 0.1.0

Extract, query, and analyse your Mac iMessage history

iMessage Analysis

Ask questions about your entire iMessage history — from an AI agent, the terminal, or a Python notebook. Works on Mac.

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What it does

• Ask your AI — connect to Claude, Codex, Cursor, or ChatGPT and ask things like "Who do I text most?" or "What did Alice and I talk about last month?"
• Search and query — run any question against your messages from the terminal
• Python notebooks — load your message data into pandas for custom analysis
• Always current — syncs only new messages each run, so it stays fast
• Real names — reads your Contacts to show names instead of phone numbers

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Quickstart

With Claude Code, Codex, or Cursor

1. Install the skills package:

npx skills add DecisionNerd/imessage-analysis

2. Run the setup command inside your AI tool:

/imessage-analysis-install

This installs the binary, connects it to your AI tool, and walks you through the first sync — including a note about using Apple Terminal the first time so macOS can ask for Contacts permission.

3. Ask anything:

"Who have I texted most this year?" "Give me a deep dive on Alice" "Who's been waiting on a reply from me?"

With Claude Desktop, ChatGPT, or any other AI tool

curl -fsSL https://raw.githubusercontent.com/DecisionNerd/imessage-analysis/main/scripts/install.sh | bash

Detects and connects to Claude Desktop, Cursor, Claude Code, and Codex automatically. See MCP setup for manual steps.

From the terminal only

1. Give Terminal permission to read your messages:

System Settings → Privacy & Security → Full Disk Access → enable Terminal

2. Install:

brew tap DecisionNerd/tap
brew install imessage-analysis

3. Run your first sync from Apple Terminal.app (not iTerm2 or other terminals — macOS needs this to ask for Contacts permission the first time):

imessage-analysis sync

4. Start exploring:

imessage-analysis status
imessage-analysis top-contacts --limit 10
imessage-analysis time-series --year 2024
imessage-analysis reactions --received
imessage-analysis search-contacts alice
imessage-analysis query "SELECT year, COUNT(*) AS n FROM messages GROUP BY year ORDER BY year"

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Use with Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json:

{
  "mcpServers": {
    "imessage": { "command": "imessage-mcp" }
  }
}

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Use with Python

pip install imessage-analysis

import imessage_analysis

df = imessage_analysis.top_contacts().to_pandas()
df = imessage_analysis.query("SELECT * FROM messages WHERE year = 2024").to_pandas()

Note: imessage_analysis.sync() picks up new messages but won't resolve contact names — that requires running imessage-analysis sync from the terminal at least once.

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Installation

Method	Command
Homebrew	brew tap DecisionNerd/tap && brew install imessage-analysis
Cargo	cargo install --git https://github.com/DecisionNerd/imessage-analysis
PyPI	pip install imessage-analysis
Claude Code / Codex / Cursor	npx skills add DecisionNerd/imessage-analysis

Requires macOS. Rust 1.70+ for source builds. Python 3.11+ for the Python package.

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Documentation

Installation	Full Disk Access, Homebrew, source, Python
CLI reference	All commands and flags
AI agent setup	Connecting to Claude, Codex, Cursor, ChatGPT
Python package	API reference, notebook examples
Data model	All 22 output columns
Contact resolution	Contacts.app + TOML overrides
Architecture	How it works under the hood
Releasing	Tagging, Homebrew formula update

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Contributing

1. Fork the repo and create a branch
2. cargo test --all — all tests must pass
3. cargo clippy -- -D warnings and cargo fmt
4. Open a pull request — CI runs automatically

This project uses Conventional Commits.

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Attribution

Inspired by the foundational work of Yorgos Askalidis, who first documented how to access and analyse the macOS iMessage database. See his original Python implementation and write-ups:

• Accessing your iMessage history on Mac
• Fun analysis ideas

This is a separate, ground-up Rust rewrite that extends the concept with a native CLI, AI agent integration, and Python bindings.

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License

Copyright (C) 2026 David Spencer. Released under the GNU General Public License v3.0.