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Trengo MCP Server and API by Cotlet

Add label in Trengo

trengo_add_label
Read-onlyIdempotent

Add label in the user's own Trengo account from ChatGPT, Claude or any AI agent. Returns how to do it in Trengo step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Trengo Cloud Browser. Trengo's official API: Trengo has a REST API for conversations, messages, contacts, labels, WhatsApp templates and reporting, but 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": "trengo_add_label"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

With readOnlyHint=true already declared, the description adds the key context explaining why a tool named 'add_label' is read-only: it returns instructions and 'opens nothing by itself,' leaving the write to cotlet_browser_* calls. That resolves an otherwise serious name/annotation tension. It doesn't describe the shape or length of the returned guide, so it is not fully transparent, but the important behavioral contract is disclosed.

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 two sentences are efficient and front-load the key constraint that the tool opens nothing by itself. The trailing sentence about Trengo's REST API and the absence of an official MCP server (with a 'checked 20 Oct 2026' date) is background justification that does not help an agent select or invoke the tool, and it dilutes an otherwise tight definition.

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 zero-parameter, read-only guide tool with no output schema, the definition covers what matters: what it returns, that it mutates nothing, and which tools complete the action. The remaining gap is that it never says how the specific label is determined when no parameter carries one, leaving the agent to infer that it comes from conversation context.

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 zero parameters, so there is nothing for the description to disambiguate beyond what the empty schema already shows; baseline 4 applies. The description implicitly explains why no parameters exist — the guide is generated from conversation context rather than a label-name argument.

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 states a specific resource (label) and, crucially, clarifies the actual output: 'Returns how to do it in Trengo step by step (screens, buttons, fields) and opens nothing by itself.' This corrects the misleading implication of the name 'add_label'. However, the opening clause still reads as if the tool performs the add, and only the second sentence reveals it is a guide generator, so an agent must read past the first clause to understand it.

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 gives explicit sequencing: call this first to get the steps, 'then do it with the cotlet_browser_* tools in the user's Trengo Cloud Browser.' That routes the agent to the correct sibling family for the actual mutation. It stops short of stating when-not to use it (e.g., if labels could be set another way), but the workflow guidance is clear and actionable.

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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