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AgentX-ai

Mailchimp MCP Server

by AgentX-ai

get_order

Retrieve specific order details from Mailchimp stores using store and order IDs to access comprehensive purchase information for email marketing analysis.

Instructions

Get details of a specific order

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
store_idYesThe store ID
order_idYesThe order ID

Implementation Reference

  • The handler logic for the 'get_order' tool within the handleToolCall switch statement. It invokes the Mailchimp service to fetch the order and returns it as a JSON-formatted text response.
    case "get_order":
      const order = await service.getOrder(args.store_id, args.order_id);
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(order, null, 2),
          },
        ],
      };
  • The input schema and metadata definition for the 'get_order' tool, specifying required store_id and order_id parameters.
    {
      name: "get_order",
      description: "Get details of a specific order",
      inputSchema: {
        type: "object",
        properties: {
          store_id: {
            type: "string",
            description: "The store ID",
          },
          order_id: {
            type: "string",
            description: "The order ID",
          },
        },
        required: ["store_id", "order_id"],
      },
    },
  • src/index.ts:42-46 (registration)
    MCP server registration for listing tools, which includes the 'get_order' tool via getToolDefinitions.
    server.setRequestHandler(ListToolsRequestSchema, async () => {
      return {
        tools: getToolDefinitions(mailchimpService),
      };
    });
  • src/index.ts:52-59 (registration)
    MCP server registration for handling tool calls, dispatching to handleToolCall which processes 'get_order'.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      try {
        return await handleToolCall(
          mailchimpService,
          request.params.name,
          request.params.arguments
        );
      } catch (error: any) {
  • Helper method in MailchimpService that performs the API request to retrieve order details from Mailchimp's e-commerce endpoint.
    async getOrder(storeId: string, orderId: string): Promise<MailchimpOrder> {
      return await this.makeRequest(
        `/ecommerce/stores/${storeId}/orders/${orderId}`
      );
    }
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 this is a retrieval operation ('Get details'), implying it's likely read-only, but doesn't confirm safety aspects, authentication needs, rate limits, error conditions, or what happens if parameters are invalid. For a tool with zero annotation coverage, this is insufficient behavioral 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 front-loads the core purpose without unnecessary words. Every part of the sentence ('Get details of a specific order') directly contributes to understanding the tool's function, making it appropriately concise 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 the tool's simplicity (2 parameters, no output schema, no annotations), the description is minimally adequate but incomplete. It doesn't explain what 'details' include, potential response formats, or error handling. For a retrieval tool in a context with many sibling tools, more differentiation and behavioral context would improve completeness.

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 both parameters clearly documented in the schema. The description adds no additional parameter semantics beyond implying that both store_id and order_id are needed to identify 'a specific order.' This meets the baseline for high schema coverage but doesn't enhance understanding of parameter relationships or constraints.

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 details') and resource ('specific order'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'list_orders' or other 'get_' tools, which would require more specificity about what 'details' means or what distinguishes an order lookup from other entity lookups.

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 'list_orders' or other retrieval tools. It doesn't mention prerequisites, context requirements, or any exclusions, leaving the agent to infer usage based solely on the tool name and basic purpose.

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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