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AgentX-ai

Mailchimp MCP Server

by AgentX-ai

list_automation_subscribers

Retrieve subscribers currently in an automation email queue to monitor campaign progress and audience engagement.

Instructions

List subscribers in an automation email queue

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workflow_idYesThe workflow ID of the automation
email_idYesThe email ID within the automation

Implementation Reference

  • Core handler function in MailchimpService that fetches subscribers from the automation email queue using paginated Mailchimp API request.
    async listAutomationSubscribers(
      workflowId: string,
      emailId: string
    ): Promise<{ subscribers: MailchimpAutomationSubscriber[] }> {
      return await this.makePaginatedRequest(
        `/automations/${workflowId}/emails/${emailId}/queue`,
        "timestamp_signup",
        "DESC"
      );
    }
  • Tool execution handler in handleToolCall that invokes the service method and formats the subscriber list response as JSON.
    case "list_automation_subscribers":
      const subscribers = await service.listAutomationSubscribers(
        args.workflow_id,
        args.email_id
      );
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(
              subscribers.subscribers.map((s) => ({
                email_address: s.email_address,
                status: s.status,
                merge_fields: s.merge_fields,
              })),
              null,
              2
            ),
          },
        ],
      };
  • Tool registration in getToolDefinitions array, including name, description, and input schema for validation.
    {
      name: "list_automation_subscribers",
      description: "List subscribers in an automation email queue",
      inputSchema: {
        type: "object",
        properties: {
          workflow_id: {
            type: "string",
            description: "The workflow ID of the automation",
          },
          email_id: {
            type: "string",
            description: "The email ID within the automation",
          },
        },
        required: ["workflow_id", "email_id"],
      },
    },
  • Input schema definition specifying required workflow_id and email_id parameters.
    inputSchema: {
      type: "object",
      properties: {
        workflow_id: {
          type: "string",
          description: "The workflow ID of the automation",
        },
        email_id: {
          type: "string",
          description: "The email ID within the automation",
        },
      },
      required: ["workflow_id", "email_id"],
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'List subscribers' but does not clarify if this is a read-only operation, what permissions are required, if there are rate limits, or how results are returned (e.g., pagination). For a tool with no annotations, this is a significant gap in transparency.

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 wasted words. It is front-loaded and appropriately sized for a simple list operation, making it highly concise and well-structured.

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 for a tool with 2 required parameters. It lacks details on behavioral traits (e.g., safety, permissions), return values, or error handling. While the schema covers parameters, the overall context for the agent to use the tool effectively is insufficient.

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 clear documentation for 'workflow_id' and 'email_id'. The description adds no additional parameter semantics beyond implying these are used to identify the automation and email queue. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description does not compensate or add extra value.

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 'List' and the resource 'subscribers in an automation email queue', making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'list_members' or 'get_subscriber_activity', which might also involve subscriber data, so it lacks sibling differentiation for a perfect score.

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 does not mention prerequisites, context, or exclusions, such as how it differs from 'list_members' or 'get_subscriber_activity' in terms of automation-specific filtering. This leaves the agent with minimal usage direction.

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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