antideploy-mcp

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by antideploy

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JavaScript

Local

Set environment variables

set_env

Destructive

Store or replace application environment variables as name/value pairs, excluding platform-managed database, storage, sign-in, and email settings.

Instructions

Store or replace environment variables for this application. Write-only. Do not pass DATABASE_URL, PG*, storage, sign-in or email variables: the platform sets those itself. To take values from a local .env without them passing through this conversation, use set_env_from_file.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "env": "<env>"
    },
    "name": "set_env"
  }
}

Input Schema

Name	Required	Description	Default
`env`	Yes	Variables to store, as name/value pairs.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Oct 23, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare destructiveHint=true; the description reinforces this by clarifying the tool is 'write-only' and that it replaces existing values, plus discloses the platform-reserved variable namespace and the secret-hygiene rationale for set_env_from_file. It stops short of stating whether changes take effect immediately or require a redeploy, which matters given the sibling redeploy tool.

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?

Three short sentences, each carrying distinct information: action, mutability profile, key restrictions, and alternative routing. The core action is front-loaded and there is no filler.

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 one-parameter write tool with no output schema, the description covers the destructive semantics, reserved keys, and the sibling escape hatch. The only material omission is whether a redeploy is needed for new values to take effect.

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?

With a single, fully schema-documented parameter the baseline is 3; the description earns more by constraining which keys are legal (no DATABASE_URL, PG*, storage, sign-in or email names), a rule the permissive name/value schema does not encode. It does not discuss value typing or size limits, but the schema already fixes values as strings.

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?

Uses a specific verb pair (store or replace) against a specific resource (environment variables for this application), and explicitly names the sibling alternative set_env_from_file. An agent can distinguish it from list_env, remove_env, and set_env_from_file without opening any schema.

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

Usage Guidelines5/5

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

Gives explicit exclusions ('Do not pass DATABASE_URL, PG*, storage, sign-in or email variables') with the reason (the platform sets those itself), and routes to the alternative when values come from a local file. Both when-to-use and when-not-to-use are covered.

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