ableton-mcp
Control Ableton Live with any LLM: create tracks, arrange clips & compose music via MCP
Runs with mockssource: GitHubPythonMITcommit 9dddc7bd5b95
Python, MIT licensed. The project labels itself: ableton, ai, claude, daw, generative ai, llm, mcp and model context protocol.
ableton-mcp runs, with stand-ins for the services it depends on. An Argusic agent installed it in 10 minutes and hit no errors on a clean machine with no GPU, and the whole session was recorded.
Ableton MCP v1.4.5 is installed in a Python 3.12 venv, all 49 unit tests pass, and the MCP server starts and responds to MCP protocol messages over stdio transport against a mock Ableton backend.
What the agent ended up with on a clean machine, in its own words. How this is measured
Measured by Argusic on a fresh machine every time. Every number links to its evidence. Argusic Score 92 of 100 (the mean of this project's run scores).
At a glance
Subject data from GitHub, linked at the top of this page, refreshed . Test data by Argusic (CC BY 4.0); every number links to a run page with the full log, the recording, and their sha256 hashes.
What was measured
From the run that decided this verdict. Every line is a recorded value, not an estimate.
- Install time
- 10 minutes
- Cold machine to finish
- 5 minutes
- Errors hit and fixed
- 0 hit, 0 fixed with no human help
- How the result was proved
- pytest tests/ exited 0 with 49 passed; MCP server over stdio responded to initialize, tools/list, and tools/call (get_remote_script_info, get_session_info) against a mock Ableton Remote Script, all returning correct JSON-RPC responses
- Model tokens used
- 57,773
- Exact commit tested
- 9dddc7bd5b95
- Container image
- sha256:cdd920bce783
What was not measured
The other half, so you can see exactly how far this evidence goes. A gap is printed as a gap and never filled in.
- Peak GPU memory
- this ran on a CPU machine, so there was no GPU to sample
- Behaviour over a long run
- each attempt uses the smallest documented settings and a fixed time budget, so this measures whether it runs, not how it holds up under load
- Behaviour against real services
- this run was verified against stand-in services only
The end of the recording
The last lines of the terminal session that decided this verdict, exactly as they were recorded.
- **End-to-end verification**: The real MCP server started over stdio transport, connected to a moc…
- **No fixes needed**: Everything worked out of the box. No errors requiring patches.
**ARGUSIC_RESULT:** {"install_succeeded": true, "launch_succeeded": true, "install_minutes": 10, "e…
tokens used
57,773
All 49 tests pass, the MCP server installs cleanly, and the end-to-end verification against a mock …
Here's the summary:
- **Install**: `pip install -e .` succeeded with all dependencies. `ableton-mcp` and `ableton-mcp-i…
- **Tests**: `pytest tests/` — 49/49 passed in 0.4s.
- **End-to-end verification**: The real MCP server started over stdio transport, connected to a moc…
- **No fixes needed**: Everything worked out of the box. No errors requiring patches.
**ARGUSIC_RESULT:** {"install_succeeded": true, "launch_succeeded": true, "install_minutes": 10, "e…Replay the whole session, every command from a clean machine to this point.
How it was tested
One agent, one container, no human help. It installs the project the way its own documentation says to, runs it, and fixes what breaks. Everything below is recorded as it happened: the terminal session, the log and the exact commit. The full method.
Strengths and limits
Measured facts, not opinions. How this is written.
What went well
- Installed in 10 minutes.
- Nothing broke on the way: zero errors between clone and running.
- Licensed MIT, as reported by its host.
What did not, or is not known
- Only reached a running state against stand-in services, so nothing here proves it works against the real ones.
- Measured once so far. A single attempt shows it can run, not that it runs reliably.
Also tested, in the same area
Every one of these was installed and run by Argusic on a clean machine. Nothing appears here that was not tested.
Run history
| tested by | attempt | outcome | score | cost USD | when |
|---|---|---|---|---|---|
| Argusic Runner | 1/3 | Runs with mocks | 92.00 | 0.03 |
Topics (from GitHub)
abletonaiclaudedawgenerative-aillmmcpmodel-context-protocolmusicpython
Embed the badge
Markdown for the project README. It links back here; terms on the terms page.
[](https://argusic.com/subject/ableton-mcp)Questions
- Does ableton-mcp run?
- ableton-mcp runs, with mocks standing in for external services. Argusic installed and launched it on a clean machine in 10 minutes, hitting 0 errors on the way, and recorded the session.
- How did Argusic test ableton-mcp?
- On a fresh, disposable machine, with every command recorded and the repository pinned at commit 9dddc7bd5b95. One attempt is recorded, and the full method is on the methodology page.
- What did it cost to test ableton-mcp?
- The run that produced this verdict cost $0.03: real compute and model cost, not a list price per million tokens. It is recorded on that run's page.
- How long does ableton-mcp take to install?
- 10 minutes in the run that decided this verdict, from a clean machine to a running state. That is one measured attempt, not an average.
- Does ableton-mcp need a GPU?
- Not to start. Argusic reached a running state on a machine with no GPU.
- What goes wrong when installing ableton-mcp?
- Nothing did, in the recorded run: zero errors between clone and running.
- Where is the evidence for ableton-mcp?
- The recorded run is on this page, each linking to its full log and terminal recording, stored with a sha256 fingerprint so it cannot be quietly altered.