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AgentX-ai

Mailchimp MCP Server

by AgentX-ai

get_automation_queue

Retrieve queued emails from a Mailchimp automation workflow to monitor scheduled email delivery status and manage campaign timing.

Instructions

Get the automation email queue

Input Schema

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

Implementation Reference

  • The core handler function in MailchimpService that fetches the automation queue via Mailchimp API using a paginated request to the /automations/{workflowId}/emails/{emailId}/queue endpoint.
    async getAutomationQueue(
      workflowId: string,
      emailId: string
    ): Promise<{ queue: MailchimpAutomationQueue[] }> {
      return await this.makePaginatedRequest(
        `/automations/${workflowId}/emails/${emailId}/queue`,
        "timestamp_signup",
        "DESC"
      );
    }
  • Tool definition and input schema validation specifying required workflow_id and email_id parameters.
    {
      name: "get_automation_queue",
      description: "Get the 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"],
      },
    },
  • Registration and dispatch handler in handleToolCall that invokes the service method and formats the response.
    case "get_automation_queue":
      const queue = await service.getAutomationQueue(
        args.workflow_id,
        args.email_id
      );
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(queue, null, 2),
          },
        ],
      };
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 'Get' which implies a read operation, but doesn't specify if this is safe (e.g., no side effects), what permissions might be required, or how the data is returned (e.g., format, pagination). For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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, efficient sentence with no wasted words. It's front-loaded with the core action and resource, making it easy to scan. However, it could be more structured by including key details like purpose or usage, but given its brevity, it earns a high score for conciseness.

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 complexity of a tool with 2 required parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., queue status, email details), how it differs from siblings, or any behavioral traits. For a tool that likely interacts with automation systems, more context is needed to be fully helpful.

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 meaning beyond what's in the schema, such as explaining how these IDs relate to the queue or providing examples. Since schema coverage is high, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

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

The description 'Get the automation email queue' states a clear verb ('Get') and resource ('automation email queue'), but it's somewhat vague about what exactly is being retrieved. It doesn't specify whether this returns metadata, status information, or the actual queue contents, nor does it distinguish itself from sibling tools like 'get_automation_email' or 'list_automation_emails' which might overlap in functionality.

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. With siblings like 'get_automation_email' and 'list_automation_emails', it's unclear if this tool is for a specific subset of email data (e.g., queued emails only) or a different aspect. No prerequisites, exclusions, or contextual hints are mentioned.

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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