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Gladly MCP Server and API by Cotlet

Search customers in Gladly

gladly_search_customers
Read-onlyIdempotent

Search customers in the user's own Gladly account from ChatGPT, Claude or any AI agent. Returns how to do it in Gladly step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Gladly Cloud Browser. Gladly's official API: Gladly has a full REST API (version 1.0), 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": "gladly_search_customers"
  }
}

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?

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds real value by disclosing that the tool returns procedural instructions and performs no action in the user's account. It does not describe the shape or length of the returned steps beyond "screens, buttons, fields".

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 critical information (returns steps, opens nothing, then use cotlet_browser_*) is front-loaded and useful. However, the closing sentence about Gladly's REST API version and MCP server availability is extraneous to invoking the tool, and the "from ChatGPT, Claude or any AI agent" clause is promotional 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?

With zero parameters, no output schema, and full annotation coverage, this description carries the remaining burden well by explaining the return content and the follow-up workflow. The only gap is that it does not indicate how granular or structured the returned steps are, which matters for an agent deciding how to chain into browser actions.

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. Baseline 4 applies.

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 verb and resource ("Search customers" in Gladly) and then clarifies the actual mechanic: it returns step-by-step instructions rather than performing the search itself. It also differentiates from the browser siblings by naming cotlet_browser_*. It stops short of distinguishing this from other Gladly read tools like gladly_list_conversations, but the resource scope is clear.

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 explicitly states the usage pattern: call this first to get screens/buttons/fields, then execute with the cotlet_browser_* tools. The "opens nothing by itself" clause tells the agent this call has no side effect on the user's account. No explicit when-not guidance is given, but the two-step workflow is unambiguous.

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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