> !mtpcli
> How do I use infractl?
The first line runs `mtpcli`, which prints instructions teaching the LLM the `--mtp-describe` convention: how to discover tools, how schemas map to CLI invocations, how to compose with pipes. The second line causes the LLM to run `infractl --mtp-describe`, get back the full schema, and understand a tool it has never seen in training data. Now you say: > Write a crontab entry that posts unhealthy pods to the #ops Slack channel every 5 minutes
And it composes your custom CLI with a third-party MCP server it's never touched before: */5 * * * * infractl pods list --cluster prod --unhealthy --json \
| mtpcli wrap --url "https://slack-mcp.example.com/v1/mcp" \
postMessage -- --channel "#ops" --text "$(jq -r '.[] | .name')"
Your tool, a Slack MCP server, and `jq`, in a pipeline the LLM wrote because it could discover every piece. That script can run in CI, or on a Raspberry Pi. No tokens burned, no inference round-trips. The composition primitives have been here for 50 years. Bash is all you need! class EncapsulatedCounter:
def __init__(self, initial_value):
_count = initial_value
def increment():
nonlocal _count
_count += 1
return _count
self.increment = increment
counter = EncapsulatedCounter(100)
new_value = counter.increment()
print(f"New value is: {new_value}")
> Imagine that you want to buy a few B300s to run GLM 5.2 and rent the service out to other people. How could this business be viable and sustainable in the first place?
My understanding is the frontier labs have huge fixed costs and relatively low marginal costs because they have to bear the cost of training the model/R&D, and then amortise that cost over their userbase.
By contrast, if I buy a few B300s and run GLM5.2 and rent the service out to other people, I can be profitable at a comparatively very small scale because I got the model for free.