Mencoro

Discover more brand names

discover_brands

Start a background job that finds other names the project's brand and each of its existing competitors go by in AI answers and search results (aliases, product and store names). It does not find new competitors. Poll get_job for the result, show it to the user, and add the chosen names with update_project (the brand) or update_competitor (a competitor, by competitorId), passing the full list including the names already there. shoppingEnabled also looks at Google Shopping; country narrows to one market (ISO 3166-1 alpha-2).

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": {
      "organizationId": "<organizationId>",
      "projectId": "<projectId>"
    },
    "name": "discover_brands"
  }
}

Input Schema

Name	Required	Description
`country`	No
`projectId`	Yes
`requestId`	No	Optional idempotency key, 8-255 printable characters. Reuse it only to retry this same call.
`organizationId`	Yes
`shoppingEnabled`	No

Output Schema

Name	Required	Description
`jobId`	Yes	Pass it to get_job. May name a job started by an earlier, equivalent call.
`nextStep`	Yes
`deduplicated`	Yes	Whether this call joined a job that was already running instead of starting one

Schema Changelog

Changes observed during successful MCP inspections.

AddedSep 28, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations declare readOnlyHint=false, idempotentHint=false, openWorldHint=true, so the mutation and non-idempotency profile is partly covered. The description adds that this is an asynchronous background job requiring polling, which the annotations do not convey, and warns that the full list must be passed on update. It stops short of noting rate limits or what happens to concurrent jobs, but adds real value beyond annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the core action and the 'does not find new competitors' exclusion, then layers the workflow and parameter notes. It is dense but nearly every clause carries actionable information. Slightly long, yet no sentence is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

A background mutation tool with an output schema, non-idempotent and open-world semantics is fully described: what it produces, how to retrieve it (get_job), how to apply it, and the scope flags. Nothing an agent needs to invoke it correctly is 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?

Schema coverage is only 20%, so the description must compensate. It explains shoppingEnabled (looks at Google Shopping) and country (narrows to one market, ISO 3166-1 alpha-2), which the bare schema does not. organizationId and projectId are self-evident and requestId is documented in the schema; the two non-obvious flags are covered.

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: starts a background job that finds aliases/product/store names for the brand and existing competitors. It explicitly distinguishes itself from siblings by ruling out new-competitor discovery ('It does not find new competitors') and by naming suggest_brand_names-adjacent scope. An agent can tell exactly what this produces.

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

Usage Guidelines5/5

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

Gives an explicit end-to-end workflow: poll get_job for the result, show the user, then add chosen names with update_project (brand) or update_competitor (by competitorId), passing the full list including existing names. It also states when each option applies (shoppingEnabled, country). This is unusually complete routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Mencoro tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.