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Gemini MCP Server

by dakrin

getModelInfo

Retrieve details about the Gemini AI model configuration, including capabilities and settings, for verification and integration purposes.

Instructions

Get information about the Gemini model being used

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • src/index.ts:310-322 (registration)
    Registration of the getModelInfo tool including inline handler function that returns static text about the Gemini model used, referencing the betaModelName constant.
    server.tool(
      "getModelInfo",
      "Get information about the Gemini model being used",
      {},
      async () => {
        return {
          content: [{ 
            type: "text", 
            text: `Using Gemini 2.5 Pro Experimental (${betaModelName})\n\nThis is Google's latest experimental model from the beta API, with:\n- 1,048,576 token input limit\n- 65,536 token output limit\n- Enhanced reasoning capabilities\n- Improved instruction following` 
          }]
        };
      }
    );
  • Inline handler for getModelInfo tool that returns model information as text content.
    async () => {
      return {
        content: [{ 
          type: "text", 
          text: `Using Gemini 2.5 Pro Experimental (${betaModelName})\n\nThis is Google's latest experimental model from the beta API, with:\n- 1,048,576 token input limit\n- 65,536 token output limit\n- Enhanced reasoning capabilities\n- Improved instruction following` 
        }]
      };
    }
  • Constant defining the model name used in the getModelInfo response.
    const betaModelName = 'models/gemini-2.5-pro-exp-03-25';
  • Empty schema (no parameters) for the getModelInfo tool.
    {},
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'Get information' implies a read-only operation, it doesn't specify what kind of information is returned, whether there are rate limits, authentication requirements, or any other behavioral characteristics. The description is minimal and lacks operational context.

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 gets straight to the point with no wasted words. It's appropriately sized for a simple tool with no parameters and effectively communicates the core purpose.

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?

For a zero-parameter tool with no output schema, the description is minimally adequate but lacks important context. It doesn't explain what information about the model is returned, the format of the response, or how this information might be useful to an agent. The absence of annotations means the description should provide more operational guidance.

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 has zero parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, which is correct for this tool configuration.

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 clearly states the action ('Get information') and the target resource ('Gemini model being used'), making the purpose immediately understandable. However, it doesn't distinguish this from its sibling tool 'generateWithGemini' which likely generates content rather than retrieving model metadata.

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. There's no mention of when this information would be needed, what context it applies to, or how it differs from the sibling 'generateWithGemini' tool.

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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