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AgentX-ai

Mailchimp MCP Server

by AgentX-ai

get_product

Retrieve detailed information about a specific product from a Mailchimp store using store and product IDs.

Instructions

Get details of a specific product

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
store_idYesThe store ID
product_idYesThe product ID

Implementation Reference

  • Core handler function in MailchimpService that fetches the specific product details via the Mailchimp API endpoint.
    async getProduct(
      storeId: string,
      productId: string
    ): Promise<MailchimpProduct> {
      return await this.makeRequest(
        `/ecommerce/stores/${storeId}/products/${productId}`
      );
    }
  • Tool dispatcher handler case that calls the service method and formats the response as MCP content.
    case "get_product":
      const product = await service.getProduct(args.store_id, args.product_id);
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(product, null, 2),
          },
        ],
      };
  • Tool registration definition including name, description, and input schema for get_product.
    {
      name: "get_product",
      description: "Get details of a specific product",
      inputSchema: {
        type: "object",
        properties: {
          store_id: {
            type: "string",
            description: "The store ID",
          },
          product_id: {
            type: "string",
            description: "The product ID",
          },
        },
        required: ["store_id", "product_id"],
      },
    },
  • TypeScript interface defining the structure of the Mailchimp product response (output schema).
    export interface MailchimpProduct {
      id: string;
      title: string;
      handle: string;
      url: string;
      description: string;
      type: string;
      vendor: string;
      image_url?: string;
      variants: Array<{
        id: string;
        title: string;
        url: string;
        sku: string;
        price: number;
        inventory_quantity: number;
        image_url?: string;
        backorders: string;
        visibility: string;
      }>;
      published_at_foreign?: string;
      _links?: Array<{
        rel: string;
        href: string;
        method: string;
        targetSchema?: string;
        schema?: string;
      }>;
    }
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 but only states what the tool does without mentioning whether it's a read-only operation, what permissions might be required, error conditions, or response format. This is inadequate for a tool with no 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 unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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?

For a tool with no annotations and no output schema, the description is insufficient. It doesn't explain what details are returned, error handling, or behavioral traits like idempotency or side effects, leaving significant gaps in understanding how to use the tool effectively.

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 input schema has 100% description coverage, with both parameters clearly documented in the schema itself. The description adds no additional meaning beyond implying that 'product_id' identifies the specific product, which is already covered by the schema. This 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.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('details of a specific product'), making it immediately understandable. However, it doesn't distinguish this tool from its sibling 'list_products', which retrieves multiple products rather than a single one, missing an opportunity for clear 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. It doesn't mention that 'list_products' should be used for retrieving multiple products or that this tool requires specific identifiers, leaving the agent to infer usage from context 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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