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damientilman

Mailchimp MCP

get_batch_status

Check the progress and completion status of an asynchronous batch operation. Poll repeatedly until the status shows as 'finished'.

Instructions

Check the progress and completion status of an asynchronous batch operation.

Use after create_batch to poll for completion. Call repeatedly until status is 'finished'. Do not use for non-batch operations. Use list_batches to see all recent batch operations.

Authenticated via API key. Subject to Mailchimp API rate limits (max 10 concurrent requests). Read-only, safe to retry.

Args: batch_id: The batch operation ID (e.g. 'batch123abc'). Obtain from create_batch.

Returns: JSON with fields: id, status ('pending' = queued, 'started' = in progress, 'finished' = complete), total_operations (int), finished_operations (int), errored_operations (int), submitted_at (ISO 8601), completed_at (ISO 8601 or null), response_body_url (string, downloadable tar.gz archive with per-operation results, only available when status is 'finished').

Example: get_batch_status(batch_id="batch123") -> {"status": "finished", "total_operations": 100, "finished_operations": 100, "errored_operations": 2, "response_body_url": "https://...", ...}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
batch_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Discloses authentication via API key, rate limits, read-only safe-to-retry nature, and polling behavior. No annotations provided, so description carries full burden and meets it.

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?

Well-structured: purpose sentence, usage guidance, behavioral notes, parameter, return type, and example. Every sentence adds value.

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

Completeness5/5

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

Complete for a simple tool: covers what, when, how, parameters, returns (including example). Output schema exists, but description enhances it with status meanings.

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

Parameters5/5

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

Given 0% schema coverage, description adds meaningful context: explains batch_id as operation ID with example ('batch123abc') and source (create_batch).

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 checks progress and completion status of an asynchronous batch operation, distinguishing it from siblings like create_batch and list_batches.

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

Usage Guidelines5/5

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

Explicitly instructs to use after create_batch, call repeatedly until finished, and mentions do not use for non-batch operations, with alternative list_batches.

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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