autooptm

Measured GPU speedups for your training and inference code, from the terminal, an agent, or Python. Diagnosis and measurement are free; credits move only when you unlock the patch.

pip install autooptm
autooptm login                 # email code, no browser needed
autooptm run https://github.com/you/repo --entrypoint train.py
autooptm unlock <jobId>        # asks before spending credits
git apply autooptm.patch

Python:

from autooptm import AutoOptm
ao = AutoOptm()
job = ao.submit(".", entrypoint="bench.py", workload="inference")
done = ao.wait(job["jobId"])
print(done["speedup"], done["unlock_credits"])

MCP (Claude Code, Cursor, any MCP client), pip install 'autooptm[mcp]':

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

Tools: optimize_submit, optimize_status, optimize_wait, unlock_patch (requires explicit user confirmation), download_patch, account_balance.

API keys (CI and scripts)

autooptm login saves a 14-day token that slides on use, which is the right credential for a laptop and the wrong one for a build machine: it expires while the pipeline is idle, it needs a mailbox to renew, and it can spend credits. A key fixes all three.

autooptm login                      # a key is minted from a session
autooptm keys create "CI pipeline"  # printed once, never again
autooptm keys list
autooptm keys revoke aok_1a2b3c4d5e6f

Put it in CI as AUTOOPTM_TOKEN and it works everywhere a login token does.

Keys carry scopes, and the default is read,submit. unlock is opt-in, so a build machine can submit work and read the result without being able to spend a credit, whatever the build does. Add --scopes read,submit,unlock only if you mean it, and --expires-in-days N to make it die on its own.