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louis030195

GPTZero MCP Server

by louis030195

gptzero_model_versions

Retrieve available AI detection model versions from GPTZero to select appropriate models for analyzing text authenticity and identifying AI-generated content.

Instructions

Get available GPTZero model versions

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler for the gptzero_model_versions tool. Calls the client's getModelVersions method and returns the list of versions formatted as text content.
    case "gptzero_model_versions": {
      const versions = await client.getModelVersions();
    
      return {
        content: [
          {
            type: "text",
            text: `Available GPTZero model versions:\n\n${versions.join("\n")}`,
          },
        ],
      };
    }
  • Core helper function in GPTZeroClient class that makes the API call to retrieve GPTZero model versions.
    async getModelVersions() {
      const response = await this.api.get("/model-versions/ai-scan");
      return response.data;
    }
  • src/index.ts:88-95 (registration)
    Tool registration in the ListToolsRequestHandler, including name, description, and empty input schema (no parameters required).
    {
      name: "gptzero_model_versions",
      description: "Get available GPTZero model versions",
      inputSchema: {
        type: "object",
        properties: {},
      },
    },
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Get available GPTZero model versions', which implies a read-only operation, but doesn't specify details like authentication needs, rate limits, error handling, or what the return format might be. This leaves significant gaps for a tool with zero annotation coverage.

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 directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.

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

Completeness3/5

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

Given the tool's simplicity (0 parameters, no output schema), the description is minimally adequate but lacks depth. It doesn't explain what 'model versions' entail or provide behavioral context, which is a gap since there are no annotations to compensate. However, for a straightforward read operation, it's passable but not comprehensive.

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 input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description doesn't need to add parameter details, but it implicitly confirms no inputs are required by not mentioning any. This meets the baseline for 0 parameters, though it could slightly enhance clarity by explicitly stating 'no parameters needed'.

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 'Get available GPTZero model versions' clearly states the verb ('Get') and resource ('available GPTZero model versions'), making the purpose understandable. However, it doesn't distinguish this tool from its sibling 'gptzero_detect', which appears to be a different detection function, so it misses full sibling differentiation.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives, such as the sibling 'gptzero_detect'. It lacks any context about prerequisites, timing, or exclusions, leaving usage entirely implicit based on the tool name alone.

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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