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Valet

by io.github.valetdotdev
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Get a build

get_build
Read-onlyIdempotent

Follow a build publish_app started: its state, the log it has written so far, and, once it succeeds, the release it produced, the URL that serves it, and its deploy: deploy_state and every process with the release it targets and the release it runs. Poll every ten to fifteen seconds until deploy_state is up or crashed, or the build failed; most deploys finish within five minutes. starting means a process is still booting the release. crashed means a process kept failing on it and was stopped: a web process that had a running release keeps serving it, so a working URL does not prove the new release is live, and other crashed processes are down until fixed. Its state_reason says why. When it is the app's own output, usually a start command that exited or a server not listening on $PORT, fix the code and publish again; when it names a platform or configuration failure, fix that or publish again. A failed build's log is where the reason is, usually a missing dependency. Requires connecting a Valet account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
build_idYesRequired. The id publish_app returned.
org_nameNoThe Valet organization the build belongs to. Omit to use the organization the account joined first.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations declare read-only and idempotent; the description adds the critical trap that a working URL does not prove the new release is live, and interprets the starting/crashed deploy states. It also notes the auth requirement (Valet account) and where the failure reason lives.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core follow/poll instruction is front-loaded, but the middle section is a dense run-on covering deploy states, state_reason, and failure remediation. It is informative but overstuffed and hard to parse in one read.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a polling tool with no output schema, it explains state values, deploy states, and failure remediation well. It could say more about log access or how much log is returned, but the operational picture is largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds nothing about build_id or org_name beyond what the schema already states. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: follows a build started by publish_app, and enumerates exactly what it returns (state, log, release, URL, deploy). It is unambiguously distinct from siblings like get_service or get_source.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly names publish_app as the producer of the build_id and gives polling cadence (every 10-15 seconds until up/crashed). It does not rule out alternatives or state when NOT to call it, but the context is clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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