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Python
Hybrid

meta_ads_products_add

Add a single product to a Meta Product Catalog and get its product ID. Adding an existing retailer_id updates that product rather than creating a duplicate.

Instructions

Adds a single product to a Meta Product Catalog. Returns the new product_id. Mutating — not automatically reversible; record before-state with mureo_state_action_log_append if you may need to roll back. For bulk ingestion prefer a scheduled feed (meta_ads_feeds_create) — Meta rate-limits single-product adds aggressively. Meta requires a stable retailer_id per product; adding a second product with the same retailer_id updates the existing record rather than creating a duplicate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesProduct landing page URL. Must be HTTPS and reachable — Meta periodically probes URLs and marks broken ones.
nameYesProduct display name shown in DPA / Collection ads.
brandNoBrand name. Optional but improves match quality for broad-intent DPA shoppers.
priceYesPrice as a string with currency code, e.g. '1000 JPY', '9.99 USD'. Meta parses the string into amount + ISO currency. Must match the catalog's supported currencies.
reasonNoWhy this change is being made: one or two sentences naming the evidence and the expected effect. Stored in the journal and on the action_log entry this call produces, for the operator and the next session.
categoryNoCategory path using Google Product Taxonomy format (e.g. 'Apparel & Accessories > Clothing > Tops'). Optional but strongly recommended for multi-category catalogs.
conditionYesProduct condition. Required by Meta for catalog eligibility in most verticals.
image_urlYesPrimary product image URL. HTTPS, publicly fetchable. Meta recommends at least 500×500px.
account_idNoMeta Ads account ID in the format 'act_XXXXXXXXXX' (e.g. 'act_1234567890'). Optional — falls back to META_ADS_ACCOUNT_ID from the configured credentials. The leading 'act_' prefix is required.
catalog_idYesCatalog to add the product into.
descriptionNoProduct description. Shown on some placements and surfaces; Meta also uses it as a weak targeting signal.
retailer_idYesAdvertiser's stable SKU / product identifier. Used as the upsert key — a second add with the same retailer_id updates the existing product.
availabilityYesInventory status. Meta suppresses 'out of stock' and 'discontinued' items from DPA delivery.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.20.0
    • addedInput schema / properties / reason
      Added value: +{
+  "description": "Why this change is being made: one or two sentences naming the evidence and the expected effect. Stored in the journal and on the action_log entry this call produces, for the operator and the next session.",
+  "maxLength": 500,
+  "type": "string"
+}
  2. Changed1 schema field changedv0.10.37
    • addedInput schema / additionalProperties
      Added value: +false
  3. Changed1 schema field changedv1.0.7
    • changedInput schema / required
      Previous value: -[
-  "account_id",
-  "catalog_id",
-  "retailer_id",
-  "name",
-  "availability",
-  "condition",
-  "price",
-  "url",
-  "image_url"
-]New value: +[
+  "catalog_id",
+  "retailer_id",
+  "name",
+  "availability",
+  "condition",
+  "price",
+  "url",
+  "image_url"
+]
  4. Addedv0.9.12
  5. Removedv0.9.6
  6. Addedv0.9.2
  7. Removedv0.9.1
  8. Addedv1.0.5

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and delivers: it states the operation is mutating, not automatically reversible, suggests recording before-state for rollback, warns about aggressive rate limits, and explains retailer_id upsert behavior. These are substantive behavioral disclosures beyond the schema.

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?

Four dense sentences, no filler, and the most important facts (purpose, return value, mutation, rollback, bulk alternative, upsert caveat) are front-loaded. Every sentence contributes.

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?

For a 13-parameter mutating tool with no annotations or output schema, this description covers purpose, output, side effects, rollback path, rate-limit constraints, and upsert behavior. Paired with the 100% schema coverage, an agent has sufficient context to select and invoke the tool correctly.

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?

Schema coverage is 100%, so the baseline is 3. The description mainly repeats the retailer_id upsert behavior already documented in the schema and adds no new parameter-level meaning; it does not enrich any individual parameter beyond what the input schema provides.

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 opening sentence states a specific action and resource: 'Adds a single product to a Meta Product Catalog' and identifies the return value. It distinguishes itself from the bulk sibling meta_ads_feeds_create and clarifies its upsert semantics versus creating duplicates.

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 warns against bulk ingestion ('For bulk ingestion prefer a scheduled feed (meta_ads_feeds_create)') and explains the rate-limit rationale. It also provides a conditional rollback instruction, giving the agent clear when-to-use and when-not-to-use guidance.

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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