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BrewMyTech

Grok MCP Server

by BrewMyTech

get_model

Retrieve detailed information about a specific model using its unique ID from the Grok MCP Server, enabling efficient model management and operations.

Instructions

Get details about a specific model

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_idYesThe ID of the model to retrieve

Implementation Reference

  • The handler function that retrieves a specific model by ID using the Grok API.
    export async function getModel(
      modelId: string
    ): Promise<z.infer<typeof ModelSchema>> {
      const response = await grokRequest(`models/${modelId}`);
      return ModelSchema.parse(response);
    }
  • Zod schema defining the input parameters for the get_model tool.
    export const GetModelSchema = z.object({
      model_id: z.string().describe("The ID of the model to retrieve"),
    });
  • index.ts:83-95 (registration)
    Registration of the "get_model" tool using FastMCP's addTool method.
    server.addTool({
      name: "get_model",
      description: "Get details about a specific model",
      parameters: models.GetModelSchema,
      execute: async (args) => {
        try {
          const result = await models.getModel(args.model_id);
          return JSON.stringify(result, null, 2);
        } catch (err) {
          handleError(err);
        }
      },
    });
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. It states it 'gets details' which implies a read-only operation, but doesn't specify what details are returned, whether authentication is required, if there are rate limits, or how errors are handled. The description is too minimal for a tool with no annotation support.

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 extremely concise at just 5 words with zero wasted language. It's front-loaded with the core purpose and appropriately sized for a simple retrieval tool.

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

Completeness2/5

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

Given no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'details' are returned, the format of the response, or any behavioral aspects. For a tool that presumably returns structured model information, more context about the return value would be helpful.

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?

The schema description coverage is 100% with the single parameter 'model_id' well-documented in the schema. The description adds no additional parameter semantics beyond what's in the schema, but since the schema does the heavy lifting, the baseline score of 3 is appropriate.

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 verb ('Get') and resource ('details about a specific model'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling 'list_models' which retrieves multiple models rather than a specific one, though this distinction is somewhat implied by 'specific model'.

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. It doesn't mention the sibling 'list_models' for retrieving multiple models or explain that this tool is for getting detailed information about a single identified model versus creating completions with other siblings.

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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