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MoonEyes

google-ecommerce-mcp

Meta campaigns

meta_campaigns
Read-onlyIdempotent

List and filter Meta ad account campaigns by status, showing IDs, objective, budgets, and dates; use IDs for pause or budget planning.

Instructions

List the campaigns of a Meta ad account: id, name, status, effective_status, objective, daily and lifetime budget (minor units and currency units), special_ad_categories, dates. Read-only.

Use the ids with meta_plan_pause / meta_plan_budget_change, or meta_adsets(campaign_id=...).

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum rows returned (1 to 500, at most 5 pages read)
statusesNoOptional effective_status filter (ACTIVE, PAUSED, ARCHIVED, CAMPAIGN_PAUSED, ADSET_PAUSED, WITH_ISSUES...); empty = Meta's default (not deleted)
client_idNoClient id from clients_list; empty uses the only client
account_idNoAd account id (digits or act_<digits>); empty means the client's account

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the description's 'Read-only' is redundant. It adds the returned field list but omits behavioral details such as pagination, rate limits, or authentication requirements.

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?

Two tightly written sentences, front-loaded with the list operation and its returned fields. The downstream usage sentence is compact and no clause is wasted.

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?

With no output schema, the description appropriately names the returned fields. Annotations cover the safety profile, and the input schema is fully documented, so the remaining gaps are minor behavioral details rather than blockers.

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 description coverage is 100%, so all four parameters are already documented in the schema. The description adds no parameter-specific meaning such as filtering behavior, account selection, or status semantics beyond what the 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?

It gives a precise verb and resource: 'List the campaigns of a Meta ad account', and enumerates the returned fields. It also distinguishes itself from sibling resources by naming meta_adsets(campaign_id=...) as the child-listing alternative.

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 tells the agent how to use the returned ids with meta_plan_pause and meta_plan_budget_change, but does not explicitly say when to choose this tool over other listing tools such as meta_ad_accounts, meta_insights, or openai_ads_campaigns. Usage is therefore implied rather than fully scoped.

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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