imsg — fast, local iMessage for your terminal & MCP

Package brand: imsg-mcp · CLI/MCP: imsg / imsg-mcp · PyPI today: pip install mac-imsg (target PyPI: imsg-mcp).

Read, search, and send iMessage from your terminal — or expose it to Claude, Cursor, VS Code, or any MCP client. Everything runs locally on your Mac: no cloud, no login, no account. Reads open ~/Library/Messages/chat.db read-only; sends go through Messages.app.

Why another one? The hot path — decoding tens of thousands of attributedBody typedstream blobs — is written in Rust (PyO3 + rusqlite), so reads and searches over a large history are several times faster than the pure-Python equivalent that other Messages servers use. Pure Python still ships as a zero-dependency fallback, so it works even where the wheel doesn't.

<!-- BENCH -->

Benchmark

Full-history search over a synthetic 50,000-message database (70% stored as attributedBody blobs), best-of-5, Apple Silicon (16 cores):

operation	pure-Python	Rust core	speedup
full-history search (decodes every message)	120.9 ms	35.7 ms	3.4×
batched blob decode (allocation-bound)	19.1 ms	19.6 ms	1.0×

Two honest caveats, stated up front:

• Raw blob decoding is ~a wash — it's bound by allocating result strings, not CPU, so native code doesn't help. The win is in search, where Rust decodes and filters across all cores and returns only the matches.
• It's 3.4×, not 16×, because the SQLite read and result marshalling are serial on both sides; only the decode+match parallelizes. The gap widens on larger histories.

Reproduce: python bench/benchmark.py. Bonus: this search also finds messages whose text lives in an attributedBody blob — which a plain text LIKE query (used by Python-only Messages servers) silently misses. <!-- /BENCH -->

Install

# with uv (recommended) — provisions Python + the prebuilt wheel
# PyPI package name is mac-imsg (imsg was too similar to an existing project);
# the installed CLIs are still `imsg` and `imsg-mcp`.
uv tool install mac-imsg

# or pip
pip install mac-imsg

# or Homebrew
brew install ml-lubich/tap/imsg

Requirements

• macOS (reads the local Messages database; sends via Messages.app).
• Full Disk Access for the app that runs imsg — Terminal/iTerm/Ghostty for the CLI, or your MCP client (Claude Desktop, Cursor, VS Code…) for the server. System Settings → Privacy & Security → Full Disk Access → add it, then fully quit and reopen it.
• Messages.app signed in and able to send a normal message.

Run imsg doctor to check access and see which engine (Rust or Python) is live.

Specs live under docs/ (overview, architecture, design, API, testing).

CLI

imsg -h                           # commands (also: imsg <cmd> -h)
imsg doctor                       # check Full Disk Access + engine
imsg chats                        # recent conversations + their ids
imsg contacts                     # handles (numbers / emails) seen
imsg contacts -q 415              # filter handles by substring
imsg read -c +14155551234         # recent messages with a contact
imsg read --chat 42 --limit 100   # a specific conversation
imsg search "dinner"              # search message text
imsg send +14155551234 "on my way"

Every command accepts -h / --help with options, arguments, and examples (agent-friendly).

MCP server

The imsg-mcp entry point speaks MCP over stdio. Add it to any client:

Claude Code

claude mcp add --transport stdio --scope user imsg -- imsg-mcp

Claude Desktop / Cursor (mcpServers) · VS Code (servers):

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

Tools exposed: check_access, get_recent_messages, search_messages, list_chats, list_contacts, send_message (the only one with a side effect).

How it works

There is no official iMessage API. Every tool in this space does the same two local things; imsg just does the heavy half in Rust:

Operation	Mechanism	Engine
read / search / list	chat.db (SQLite, read-only) + typedstream decode	Rust (imsgcore), Python fallback
send	AppleScript → Messages.app	Python (osascript)

SQLite is the same C library everywhere, so the read speedup comes from doing the per-message attributedBody decode and row marshalling natively instead of in a Python loop. See bench/benchmark.py for the methodology — both engines run identical queries over an identical synthetic database, and the pure-Python column is the same algorithm Python-only servers use.

Privacy & security

• All database connections are opened read-only (mode=ro).
• Nothing is uploaded, mirrored, or indexed off-device.
• Sending is isolated in one function, escapes its AppleScript inputs, and is the only operation that writes anything anywhere.
• Full Disk Access is broad — grant it only to apps you trust.

Development

git clone https://github.com/ml-lubich/imsg.git && cd imsg
uv venv && source .venv/bin/activate
uv pip install maturin
maturin develop            # builds the Rust core + installs the package
uv pip install -e ".[dev]"
pytest                     # tests run on the pure-Python path (and Rust if built)
python bench/benchmark.py  # regenerate the benchmark

License

MIT © ml-lubich. Not affiliated with Apple. Use responsibly and only with accounts and conversations you own.