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Breezeway MCP Server and API by Cotlet

Approve task in Breezeway

breezeway_approve_task
Read-onlyIdempotent

Approve task in the user's own Breezeway account from ChatGPT, Claude or any AI agent. Returns how to do it in Breezeway step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Breezeway Cloud Browser. Breezeway's official API: Breezeway has a REST API for properties, reservations, tasks and people, but you need API keys from a request form, and it has no official MCP server (checked 20 Oct 2026).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "breezeway_approve_task"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior3/5

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

The description adds real behavioral context beyond the annotations: it opens nothing by itself and returns a step-by-step walkthrough, which matches readOnlyHint=true and destructiveHint=false. However, it does not say what happens if the user is not signed in to Breezeway, whether the returned steps are verified against the live UI, or how stale they can be.

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 first two sentences are front-loaded and earn their place. The closing paragraph about Breezeway's REST API, key request forms, and a 'checked 20 Oct 2026' date is tangential metadata that does not help the agent invoke this tool.

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 parameters and no output schema, the description correctly explains the return value (step-by-step instructions) and the handoff to browser tools. That is sufficient for an agent to select and use it, with only minor gaps around preconditions.

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?

The tool takes no parameters, so the baseline is 4. The description could have compensated by explaining how a target task is identified (presumably through the browser session), but it does not need to since the schema is empty.

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 names a specific verb and resource (approve a task in Breezeway) and immediately clarifies the mechanism: it returns step-by-step screens/buttons/fields rather than performing the action. It routes the agent to cotlet_browser_* tools for execution, though it does not differentiate itself from similarly named siblings like breezeway_close_task or breezeway_reopen_task.

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?

Clear usage flow: call this to get instructions, then carry them out with cotlet_browser_* tools. The condition for using this over the REST API route is also implied. What is missing is any guidance on when to choose this over the other breezeway_* task tools.

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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