Skip to main content
Glama
Pauesome

Ads Analytics MCP

by Pauesome
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

get_google_ads_campaign_performance

Fetches Google Ads campaign performance metrics like spend, clicks, and conversions. Supports daily or campaign-level aggregation and filtering by date, campaign, or status.

Instructions

Retrieves Google Ads campaign performance metrics for a client. Returns normalized metrics: spend, impressions, clicks, CTR, CPC, CPM, conversions, CPA, conversion value, ROAS, plus bidding_strategy_type and channel_type. Default aggregation = 'campaign' (one row per campaign over the full period). Pass aggregation='campaign_day' for trend analysis or 'day' for account-level timeseries. Supports filtering by date range, campaign IDs, and campaign status. Use list_clients to see available client IDs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusesNoFilter by campaign status. Returns all statuses if omitted.
client_idNoClient identifier. Required when multiple clients are configured. Use list_clients to see available IDs.
aggregationNoRow granularity. 'campaign' (default) = one row per campaign, totals over the full period. 'campaign_day' = one row per campaign × day (trend analysis). 'day' = one row per day rolled up across campaigns.
campaign_idsNoFilter to specific campaign IDs. Returns all campaigns if omitted.
customer_idsNoOverride the client's default Google Ads account IDs. Useful for clients with multiple sub-accounts.
date_range_endNoEnd date in YYYY-MM-DD format. Defaults to today.
date_range_startNoStart date in YYYY-MM-DD format. Defaults to 30 days ago.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior3/5

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

No annotations, so the description carries the burden. It discloses the row-granularity behavior of aggregation modes and that client_id is required when multiple clients exist, which is useful. But it doesn't state default date range behavior (the schema does), pagination, rate limits, or how many rows could be returned for high-cardinality 'day' queries.

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?

Front-loaded with purpose and metric list, then aggregation options, then filtering, then client lookup pointer. Every sentence earns its place and none repeat structured data verbatim.

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?

For a read tool with rich schema and no output schema, the description covers metrics returned, granularity, filtering, and dependency on list_clients. The absence of an output schema means the metric list in the description does useful work. Minor gap: no mention of date defaults or that customer_ids overrides default accounts (both in schema, so acceptable).

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 the schema already documents all 7 parameters including the enum. The description's mention of aggregation semantics and filtering matches the schema rather than extending it. Baseline 3 is appropriate.

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?

Specific verb (retrieves) + resource (Google Ads campaign performance metrics) + the platform differentiator against the many sibling get_*_campaign_performance tools (Meta, TikTok). An agent can immediately distinguish this from get_meta_campaign_performance or get_tiktok_campaign_performance.

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?

Explicitly states when to use each aggregation ('campaign' default for totals, 'campaign_day' for trend analysis, 'day' for account-level timeseries) and points to list_clients for client IDs. However, it does not name when-not-to-use or point to sibling metric tools (search_terms, keywords, impression_share) that cover non-performance dimension analysis.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools