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Trengo MCP Server and API by Cotlet

List conversations in Trengo

trengo_list_conversations
Read-onlyIdempotent

List conversations 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_list_conversations"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, but the description adds a genuinely important trait not in the structured data: 'opens nothing by itself' — i.e. invoking it has no side effect on the Trengo account and only produces instructions. It also explains the underlying constraint (Trengo has a REST API but no official MCP server), which justifies why a browser-driving workflow is needed.

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 message (returns a step-by-step guide, then drive with cotlet_browser_*) is front-loaded and useful, but the trailing API paragraph is background justification that consumes roughly a third of the text without guiding invocation. The description also takes two sentences to reach the real behavior, delaying the key disclosure.

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 input parameters and no output schema, the description carries the burden of explaining what comes back, and it does so ('how to do it in Trengo step by step (screens, buttons, fields)'). It also names the tools that perform the actual work, so an agent knows the full workflow; only the hand-off criteria versus the sibling search/guide tools are missing.

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 no parameter semantics for the description to add; baseline 4 applies. The empty schema is consistent with a guide-style tool that needs no arguments.

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

Purpose3/5

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

The first sentence claims it will 'List conversations in the user's own Trengo account', but the second sentence reveals it actually 'Returns how to do it in Trengo step by step (screens, buttons, fields) and opens nothing by itself'. The real verb (returns instructions, not data) only emerges on careful reading, and there is no differentiation from the sibling trengo_search_conversations or cotlet_app_guide.

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

Usage Guidelines3/5

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

It does give a concrete follow-up path: 'then do it with the cotlet_browser_* tools in the user's Trengo Cloud Browser', which tells the agent how to complete the task. However, it never states when to pick this over trengo_search_conversations or why one would need this guide at all versus calling a Trengo tool directly.

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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