Ubersuggest MCP Server and API by Cotlet

Get rank tracking in Ubersuggest

ubersuggest_get_rank_tracking

Read-onlyIdempotent

Get rank tracking in the user's own Ubersuggest account from ChatGPT, Claude or any AI agent. Returns how to do it in Ubersuggest step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Ubersuggest Cloud Browser. Ubersuggest's official API: Ubersuggest has no public REST API and no webhooks (checked 23 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": "ubersuggest_get_rank_tracking"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 9, 2026

TDQS

A3.7/5.0

Behavior3/5

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

Beyond the readOnly/idempotent annotations, it usefully discloses that the tool 'opens nothing by itself' and returns procedural content rather than data, plus that no REST API or webhooks exist. However it says nothing about how long the returned procedure is, whether it covers all rank-tracking variants, or what the browser step requires (login state, plan tier).

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 workflow is front-loaded and useful, but the sentence about the official API and webhooks 'checked 23 Oct 2026' is dated boilerplate that does nothing to help select or invoke the tool, and 'from ChatGPT, Claude or any AI agent' is marketing 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 no parameters and no output schema, the description correctly carries the burden of saying what comes back (step-by-step screens, buttons, fields) and what to do next. It falls short only on operational prerequisites, such as whether the user must already be logged in before the browser tools can act on the instructions.

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 the baseline is 4 and the description adds the relevant framing that all context comes from the user's own account rather than from inputs. There is nothing more for it to specify.

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 resource (rank tracking in the user's Ubersuggest account) and clarifies what is actually returned: step-by-step instructions with screens, buttons and fields, not rank data. That correction rescues a name that could otherwise be read as a data-fetch, though the phrasing 'Get rank tracking' still front-loads the wrong expectation.

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 an explicit two-step workflow: call this to obtain instructions, then execute them with the cotlet_browser_* tools in the user's Ubersuggest Cloud Browser. What is missing is differentiation from the other ubersuggest_* siblings (e.g. add_tracked_keywords, list_projects), which are never mentioned as alternatives.

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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