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Emenowicz

Hybris MCP Server

by Emenowicz

get_product

Retrieve detailed product information by entering the product code or SKU. This tool fetches specific product data from SAP Commerce Cloud (Hybris) for management and analysis purposes.

Instructions

Get detailed information about a specific product by its code

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productCodeYesThe product code/SKU

Implementation Reference

  • Core handler function that executes the get_product tool logic by making a REST API request to the Hybris OCC endpoint to retrieve product details by code.
    async getProduct(productCode: string): Promise<Product> {
      return this.request<Product>(
        `/rest/v2/${encodeURIComponent(this.config.baseSiteId!)}/products/${encodeURIComponent(productCode)}?fields=FULL`
      );
    }
  • JSON input schema defining the required 'productCode' parameter for the get_product tool.
    inputSchema: {
      type: 'object',
      properties: {
        productCode: {
          type: 'string',
          description: 'The product code/SKU',
        },
      },
      required: ['productCode'],
    },
  • src/index.ts:126-139 (registration)
    Tool registration object added to the tools list returned by listTools, including name, description, and schema.
    {
      name: 'get_product',
      description: 'Get detailed information about a specific product by its code',
      inputSchema: {
        type: 'object',
        properties: {
          productCode: {
            type: 'string',
            description: 'The product code/SKU',
          },
        },
        required: ['productCode'],
      },
    },
  • MCP request handler switch case that validates input arguments and dispatches to the HybrisClient.getProduct method.
    case 'get_product':
      result = await hybrisClient.getProduct(
        validateString(args, 'productCode', true)
      );
      break;
  • TypeScript interface defining the structure of the Product object returned by the get_product tool.
    export interface Product {
      code: string;
      name: string;
      description?: string;
      price?: {
        value: number;
        currencyIso: string;
        formattedValue: string;
      };
      stock?: {
        stockLevel: number;
        stockLevelStatus: string;
      };
      categories?: { code: string; name: string }[];
      images?: { url: string; format: string }[];
    }
Behavior2/5

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

With no annotations provided, the description carries full burden but only states it retrieves 'detailed information' without specifying what that includes, whether it's read-only, requires authentication, has rate limits, or error behaviors. It lacks critical context for a tool that presumably accesses a product database, leaving the agent guessing about operational traits.

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 with zero waste—every word contributes to understanding the tool's purpose. It's front-loaded with the core action and resource, 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?

Given no annotations and no output schema, the description is insufficient for a tool that likely returns complex product data. It doesn't explain what 'detailed information' entails, potential response formats, or error conditions. For a lookup tool in a system with many siblings, more context is needed to guide effective use.

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%, so the schema already documents the 'productCode' parameter as 'The product code/SKU'. The description adds no additional meaning beyond implying it's used to identify a specific product, which is redundant with the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 'detailed information about a specific product', making the purpose unambiguous. It distinguishes from siblings like 'search_products' by specifying retrieval of a single product by code rather than searching. However, it doesn't explicitly contrast with 'get_categories' or 'get_category', which might be similar lookup operations.

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 like 'search_products' or 'get_category'. It mentions retrieving by 'code' but doesn't clarify if this is the only identifier method or when to choose this over other lookup tools. No prerequisites or exclusions are stated.

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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