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Housecall Pro MCP Server and API by Cotlet

by dev.cotlet
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Run a script on the page

cotlet_browser_evaluate
Destructive

Runs a JavaScript function body on the page and answers what it returns, as JSON. Use it to extract data the page holds (a table, a list, attributes); act with the other tools. It cannot send requests, click, submit, or read cookies or storage; a filled field's value reads [hidden by Cotlet]. Example: return [...document.querySelectorAll('h2')].map(h => h.innerText)

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": {
      "script": "<script>"
    },
    "name": "cotlet_browser_evaluate"
  }
}

Input Schema

NameRequiredDescriptionDefault
scriptYesA function body that returns.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Adds substantial behavior beyond the annotations: sandbox limits (no requests, clicks, submits, cookie or storage access) and the [hidden by Cotlet] redaction on filled fields, which an agent would otherwise only discover by failing. It does not address the destructiveHint=true / readOnlyHint=false profile, i.e. what happens if the script mutates page state, leaving a mild tension with the 'extract, don't act' framing, though nothing is outright contradicted.

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?

Front-loads the capability, then the use case, then the hard limits, then a one-line example — no filler sentences. The 20000-character limit and other mechanical details are correctly left to the schema.

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 carries the return contract and does so adequately by declaring JSON-serialized results. It omits failure behavior such as timeouts, thrown exceptions, or oversized return values, which matter for an arbitrary-script tool, so it falls just short of fully complete.

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 already documents the single 'script' parameter, so the baseline is 3. The description earns an extra point by showing a concrete function-body example and clarifying the return path ('answers what it returns, as JSON'), which the terse schema line 'A function body that returns' does not convey.

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 (runs a JavaScript function body on the page) plus the return contract (JSON), and distinguishes itself from the action-oriented siblings by saying 'act with the other tools.' An agent can tell this apart from cotlet_browser_read or cotlet_browser_click 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 Guidelines4/5

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

Gives an explicit when-to-use case ('extract data the page holds (a table, a list, attributes)') and routes state-changing work to other tools. It stops short of naming the closest alternatives, e.g. when cotlet_browser_read or cotlet_browser_find suffices, which would remove the remaining ambiguity about choosing evaluation over simpler extraction 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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