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antideploy

antideploy-mcp

Official
by antideploy

Deploy again without sending the code

redeploy
Destructive

Rebuild and release an already uploaded app with its current environment variables, or deploy the newest GitHub commit. Returns a taskId to poll with deployment_status.

Instructions

Build and release the application again without uploading it. By default that is the version last sent, with the current environment variables: this is how a changed variable or a new AI key reaches the running app. For an application built from GitHub, latest deploys the newest commit on its default branch instead. Returns a taskId to poll with deployment_status.

Input Schema

NameRequiredDescriptionDefault
latestNoGitHub applications only: deploy the branch's newest commit.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already declare destructiveHint=true and openWorldHint=false, and the description adds useful context (default = last-sent version + current env vars, `latest` pulls newest commit, returns a taskId). But it never discloses what is destructive about it – app restart/downtime or interruption of the running release – which is exactly the behavior the destructiveHint implies. Adds value, but leaves a meaningful behavioral gap.

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

Conciseness5/5

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

Four short sentences, front-loaded with the core action and the default behavior, then the exception, then the return value. Every sentence carries information an agent needs and none repeats the schema verbatim.

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?

With no output schema, the description correctly supplies the return contract ('a taskId to poll with `deployment_status`'), which is essential. It is almost complete for a one-parameter mutation, missing only the restart/downtime implication and any permission prerequisite.

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

Parameters4/5

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

Schema coverage is 100% and the single `latest` parameter is documented, so the baseline is 3. The description goes slightly beyond by explaining the contrast: default is the last-sent version, while `latest` (GitHub apps only) deploys the newest default-branch commit.

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

Purpose4/5

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

The description gives a specific verb and resource ('Build and release the application again without uploading it'), which clearly separates it from the sibling `deploy` that would upload code. However, it doesn't explicitly name `deploy` as the alternative, so the differentiation is inferable rather than stated.

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?

It states a concrete trigger condition: 'this is how a changed variable or a new AI key reaches the running app', which tells an agent when to pick this over other deployment tools. It also explains the `latest` branch case. It stops short of explicit when-not-to-use guidance or naming the sibling it replaces.

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