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damientilman

Mailchimp MCP

update_store_product_variant

Update an existing product variant by modifying specific attributes like price, SKU, or inventory quantity. Only supplied fields are changed.

Instructions

Update an existing product variant's price, SKU, inventory, or other attributes.

Only fields supplied in additional_fields are changed. Many stores sync variants automatically via Shopify or WooCommerce integrations; these manual writes suit custom or headless storefronts.

Authenticated via API key. Max 10 concurrent requests. Respects read-only and dry-run modes.

Args: store_id: E-commerce store ID. product_id: Product ID that owns the variant. variant_id: Existing variant ID. additional_fields: Dict of documented fields to update (e.g. title, url, sku, price, inventory_quantity, image_url) merged into the request body. account: Optional account name (e.g. 'marketing') configured via MAILCHIMP_API_KEY_. Omit to use the default account. See list_accounts.

Returns: JSON with the updated variant object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accountNo
store_idYes
product_idYes
variant_idYes
additional_fieldsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations indicate readOnlyHint=false (mutation) and destructiveHint=false. The description adds behavioral details: authentication via API key, max 10 concurrent requests, and respect for read-only/dry-run modes. This supplements the annotations well.

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 concise and well-structured: it front-loads the purpose, then usage context, then auth/limits, then parameter explanations. Every sentence adds value with no redundancy.

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 output schema existence, the description covers the main aspects: purpose, when to use, auth constraints, parameter details. Minor omission of error handling but acceptable for a complete tool definition.

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?

With schema coverage at 0%, the description compensates by explaining each parameter: store_id, product_id, variant_id, additional_fields (with example fields like title, sku, price), and account (with optional usage and reference to list_accounts). This adds significant meaning beyond the schema names.

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 'Update an existing product variant's price, SKU, inventory, or other attributes', using a specific verb and resource. It distinguishes from sibling tools like 'create_store_product_variant' and 'delete_store_product_variant' by focusing on updates.

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

Usage Guidelines4/5

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

The description provides context: 'Only fields supplied in additional_fields are changed' and notes that automatic sync via Shopify/WooCommerce is common, so this manual write suits custom or headless storefronts. This implies when to use and when not to, though it doesn't explicitly name alternatives.

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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