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brandomica-mcp-server

Package Registry & SaaS Availability

brandomica_check_saas
Read-onlyIdempotent

Check package name availability across npm, PyPI, crates.io, RubyGems, NuGet, Homebrew, Docker Hub, and ProductHunt to verify brand name availability.

Instructions

Check package name availability across npm, PyPI, crates.io, RubyGems, NuGet, Homebrew, Docker Hub, and ProductHunt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brand_nameYesThe brand name to check

Implementation Reference

  • Registration and handler implementation for the brandomica_check_saas tool.
    server.registerTool(
      "brandomica_check_saas",
      {
        title: "Package Registry & SaaS Availability",
        description:
          "Check package name availability across npm, PyPI, crates.io, RubyGems, NuGet, Homebrew, Docker Hub, and ProductHunt.",
        inputSchema: z.object(brandNameInput).strict(),
        annotations: toolAnnotations,
      },
      async ({ brand_name }) => {
        const data = (await fetchApi("check-saas", brand_name)) as {
          results: SaasResult[];
        };
        return {
          content: [{ type: "text" as const, text: formatSaas(data) }],
        };
      }
    );
  • Helper function to format the SaaS availability check results.
    function formatSaas(data: { results: SaasResult[] }): string {
      const lines: string[] = ["## Package Registries & SaaS"];
      for (const s of data.results) {
        const status =
          s.available === true
            ? "Available"
            : s.available === false
              ? "Taken"
              : "Unknown (check manually)";
        lines.push(`- ${s.platform}: ${status} — ${s.url}`);
      }
      return lines.join("\n");
    }
Behavior4/5

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

Annotations already provide readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, covering safety and idempotency. The description adds context by specifying the exact platforms checked, which helps the agent understand scope beyond what annotations convey. No contradictions with annotations exist.

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

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the core action and lists all relevant platforms without unnecessary words. Every element (verb, resource, platforms) earns its place by directly informing tool selection and use.

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?

Given the tool's low complexity (one parameter, no output schema) and rich annotations covering safety and behavior, the description is reasonably complete. It specifies the platforms checked, which is crucial for contextual understanding. However, it lacks details on output format or potential limitations (e.g., rate limits, error handling), leaving some gaps for the agent.

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%, with the parameter 'brand_name' fully documented in the schema (including type, length constraints, and pattern). The description does not add any additional meaning or details about the parameter beyond what the schema provides, so it meets the baseline for high schema coverage.

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?

The description clearly states the specific action ('Check package name availability') and enumerates the exact resources across which this check is performed (npm, PyPI, crates.io, RubyGems, NuGet, Homebrew, Docker Hub, and ProductHunt). This distinguishes it from sibling tools like 'check_domains' or 'check_social' by specifying the package registry and SaaS platform focus.

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?

The description implies usage context (checking brand name availability across specific platforms) but does not explicitly state when to use this tool versus alternatives like 'check_all' or 'check_appstores'. No exclusions or prerequisites are mentioned, leaving the agent to infer appropriate scenarios based on the enumerated platforms.

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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