Skip to main content
Glama
Sign In

rapp-name-finder

by io.github.kody-w
OverviewDiscussionsAdmin

Check business names

check_names
Read-only

Use when someone is naming a business, startup, product, brand, app, side hustle, shop, podcast or project. Brainstorm candidate names first, then check up to 8 at once: for each, which domains (.com, .co, .ai, .io, .app by default) are free with prices, and whether the GitHub name is free. Results are ranked, a free .com counts most. Suggest new candidates and check again if the best ones are taken.

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": {
      "names": "<names>"
    },
    "name": "check_names"
  }
}

Input Schema

NameRequiredDescriptionDefault
namesYesCandidate names, e.g. ["Rise and Crumb", "Northwind Bakery"]
endingsNoOptional domain endings to check, e.g. ["com", "shop"]

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the agent knows this is a safe external read. The description adds useful context about ranking and the default endings (.com, .co, .ai, .io, .app) and the free-.com weighting, but does not disclose latency, rate limits, or how 'GitHub name free' is determined. With annotations carrying the safety profile, this is adequate but not rich.

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 when-to-use condition, then describes the workflow and output. It is information-dense with little waste, though the long enumeration of use cases (side hustle, shop, podcast, project) is slightly padded.

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 two-parameter read-only tool with no output schema, the description covers trigger, input limits, output content, and iteration strategy. It stops short of describing result format or error behavior, but the annotations and schema cover the remaining structured ground.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and both parameters are documented with types and examples, so the schema already does the heavy lifting. The description adds the meaningful constraint that up to 8 names can be checked at once and names the default endings list, which is useful but mostly mirrors the schema's maxItems and examples.

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 (check) and resource (names) and describes the exact output: domain availability with prices plus GitHub name availability, ranked. It distinguishes itself from sibling check_domain by handling up to 8 candidates across multiple endings at once.

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?

Explicit when-to-use trigger (naming a business, startup, product, brand, etc.) and a clear workflow: brainstorm first, check up to 8, then iterate if the best are taken. This tells the agent both when to invoke it and how to sequence it relative to iterating on candidates.

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

All rapp-name-finder toolsInspect
Try in Browser
Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources