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ping

Validate Mailchimp API credentials and retrieve account details including name, email, and subscriber count.

Instructions

Validate your Mailchimp API key and get account info (name, email, total subscribers).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The 'ping' tool is defined as an asynchronous function decorated with @mcp.tool(). It validates the Mailchimp API key by making a request to the '/ping' endpoint and returns formatted account information.
    @mcp.tool()
    async def ping() -> str:
        """Validate your Mailchimp API key and get account info (name, email, total subscribers)."""
        mc = get_client()
        try:
            await mc.get("/ping")
            root = await mc.get("/")
            return _fmt({
                "status": "connected",
                "account_name": root.get("account_name", ""),
                "email": root.get("email", ""),
                "account_id": root.get("account_id", ""),
                "total_subscribers": root.get("total_subscribers", 0),
                "data_center": mc.dc,
            })
        except MailchimpError as e:
            return f"Connection failed: {e}"
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the tool's behavior (validation and info retrieval) but lacks details on rate limits, error responses, or authentication requirements beyond the API key mention. It doesn't contradict any annotations.

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, front-loaded sentence with zero waste—it directly states the tool's function and output without unnecessary elaboration. Every word contributes to understanding.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, output schema exists), the description is complete enough for a validation/info tool. It covers the core purpose and output types, though it could benefit from more behavioral context like error handling or usage timing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has 0 parameters with 100% schema coverage, so no parameter documentation is needed. The description appropriately focuses on the tool's purpose without redundant parameter details, earning a baseline score above 3 for efficient handling of a parameterless tool.

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

Purpose5/5

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

The description clearly states the tool's purpose with specific verbs ('validate', 'get') and resources ('Mailchimp API key', 'account info'), and it distinguishes itself from sibling tools by focusing on authentication and basic account data rather than audience/campaign management operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for API key validation and retrieving account metadata, but it doesn't explicitly state when to use this tool versus alternatives (e.g., for testing connectivity vs. actual operations). No exclusions or prerequisites 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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