Hybris MCP Server

get_orders

Retrieve order details for a specific user from SAP Commerce Cloud using their user ID or email address.

Instructions

Get orders for a specific user

Input Schema

TableJSON Schema

Name	Required	Description	Default
`userId`	Yes	User ID or email

Implementation Reference

src/hybris-client.ts:453-457 (handler)

Actual implementation of the getOrders tool logic in the Hybris client class.

async getOrders(userId: string): Promise<{ orders: Order[] }> {
  return this.request<{ orders: Order[] }>(
    `/occ/v2/${encodeURIComponent(this.config.baseSiteId!)}/users/${encodeURIComponent(userId)}/orders?fields=FULL`
  );
}

src/index.ts:162-175 (registration)

Registration of the get_orders tool with its input schema.

{
  name: 'get_orders',
  description: 'Get orders for a specific user',
  inputSchema: {
    type: 'object',
    properties: {
      userId: {
        type: 'string',
        description: 'User ID or email',
      },
    },
    required: ['userId'],
  },
},

src/index.ts:403-407 (handler)

The handler case in index.ts that calls the hybrisClient for the get_orders tool.

case 'get_orders':
  result = await hybrisClient.getOrders(
    validateString(args, 'userId', true)
  );
  break;

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Mar 18, 2026

TDQS

C2.9/5.0

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 the tool retrieves orders, implying a read-only operation, but lacks details on permissions, rate limits, pagination, error handling, or what 'orders' entails (e.g., status, format). This is inadequate for a tool with potential complexity in data retrieval.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that efficiently conveys the core purpose without unnecessary words. It is front-loaded and easy to parse, though it could be slightly more informative without sacrificing brevity.

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 incomplete. It fails to address key contextual aspects like return format (e.g., list of orders, error cases), behavioral traits (e.g., authentication needs, data scope), or how it integrates with sibling tools. For a data retrieval tool, this leaves significant gaps for an AI agent.

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%, with the parameter 'userId' documented as 'User ID or email'. The description adds no additional meaning beyond this, such as examples or constraints. Since the schema fully covers the parameter, the baseline score of 3 is appropriate, as the description doesn't enhance but also doesn't detract from the schema.

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') and resource ('orders'), and specifies the scope ('for a specific user'). It distinguishes from sibling tools like 'get_order' (singular) by implying it returns multiple orders. However, it doesn't explicitly differentiate from potential filtering alternatives or clarify if it returns all orders or a subset.

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 minimal guidance—it indicates the tool is for retrieving orders for a user, but offers no context on when to use it versus alternatives like 'search_products' or 'get_order'. There are no prerequisites, exclusions, or comparisons to sibling tools mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server