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AdsAgent — Google Ads MCP

google_ads_reach_forecast

Read-only

Read bounded native reach_forecast insight. Restricted services require fresh server-verified access and otherwise refuse. No writes or access grants.

Input Schema

NameRequiredDescriptionDefault
bodyYes
customer_idYes10-digit Google Ads customer id.
connection_contextNo

Output Schema

NameRequiredDescriptionDefault
okNo
codeNo
dataNo
kindNo
errorNo
needsNo
reasonNo
sourceNo
retryableNo
error_codeNo
request_idNo
api_versionNo
next_actionNo
observed_atNo
support_refNo
availabilityNo
invalid_fieldsNo
rejected_pathsNo
truncated_fieldsNo
origin_support_refNo
forecast_not_guaranteeNo
smart_campaign_create_supportedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "additionalProperties": true,
      +  "properties": {
      +    "api_version": {
      +      "type": "string"
      +    },
      +    "availability": {
      +      "type": "string"
      +    },
      +    "code": {
      +      "type": "string"
      +    },
      +    "data": {
      +      "additionalProperties": true,
      +      "properties": {},
      +      "type": "object"
      +    },
      +    "error": {
      +      "anyOf": [
      +        {
      +          "anyOf": [
      +            {
      +              "type": "string"
      +            },
      +            {
      +              "additionalProperties": true,
      +              "properties": {
      +                "code": {
      +                  "type": "string"
      +                },
      +                "details": {
      +                  "additionalProperties": true,
      +                  "properties": {},
      +                  "type": "object"
      +                },
      +                "message": {
      +                  "type": "string"
      +                },
      +                "retryable": {
      +                  "type": "boolean"
      +                },
      +                "support_ref": {
      +                  "type": "string"
      +                }
      +              },
      +              "type": "object"
      +            }
      +          ]
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ]
      +    },
      +    "error_code": {
      +      "type": "string"
      +    },
      +    "forecast_not_guarantee": {
      +      "type": "boolean"
      +    },
      +    "invalid_fields": {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    "kind": {
      +      "type": "string"
      +    },
      +    "needs": {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    "next_action": {
      +      "anyOf": [
      +        {
      +          "anyOf": [
      +            {
      +              "type": "string"
      +            },
      +            {
      +              "additionalProperties": true,
      +              "properties": {},
      +              "type": "object"
      +            }
      +          ]
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ]
      +    },
      +    "observed_at": {
      +      "type": "string"
      +    },
      +    "ok": {
      +      "type": "boolean"
      +    },
      +    "origin_support_ref": {
      +      "type": "string"
      +    },
      +    "reason": {
      +      "type": "string"
      +    },
      +    "rejected_paths": {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    },
      +    "request_id": {
      +      "anyOf": [
      +        {
      +          "type": "string"
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ]
      +    },
      +    "retryable": {
      +      "type": "boolean"
      +    },
      +    "smart_campaign_create_supported": {
      +      "anyOf": [
      +        {
      +          "type": "boolean"
      +        },
      +        {
      +          "type": "null"
      +        }
      +      ]
      +    },
      +    "source": {
      +      "type": "string"
      +    },
      +    "support_ref": {
      +      "type": "string"
      +    },
      +    "truncated_fields": {
      +      "items": {
      +        "type": "string"
      +      },
      +      "type": "array"
      +    }
      +  },
      +  "type": "object"
      +}
  2. Changed1 schema field changed
    • addedInput schema / properties / connection_context
      Added value: +{
      +  "pattern": "^mctx_v1_[0-9a-f]{64}$",
      +  "type": "string"
      +}
  3. Added

TDQS

C2.9/5.0
Behavior4/5

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

Annotations already cover readOnly/destructive/openWorld, so the description wisely spends its words elsewhere: it discloses an auth precondition ("restricted services require fresh server-verified access and otherwise refuse") that the agent would otherwise only discover at call time. It does not mention rate limits or failure shapes beyond refusal, keeping it at 4 rather than 5.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three terse sentences with the operation front-loaded and the precondition second; nothing is padded. The terseness borders on cryptic, but it is efficient.

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

Completeness2/5

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

For a tool with a required nested body of four undocumented fields, the description should at minimum map location_id and product_code to their lookup siblings and note that budget_micros is per product. With an output schema present, return values need no explanation, but the input-side gaps remain large.

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

Parameters2/5

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

Schema description coverage is only 33% - just customer_id is documented - and the nested body requires location_id, duration_days, currency_code and products with no semantic hints in either schema or description. The description adds nothing about these fields, so the agent must infer that location_id/product_code values come from the reach_locations/reach_products siblings.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Read bounded native reach_forecast insight" gives a verb and a resource, and the annotation title confirms it is a Google Ads reach forecast. But "bounded native ... insight" is jargon that never says what the forecast actually returns (reach/impressions for a budget, duration and product mix), and it does not distinguish this from the reach_locations / reach_products siblings that likely feed it.

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

Usage Guidelines2/5

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

There is no statement of when to use this versus google_ads_reach_locations, google_ads_reach_products, or the keyword forecast tools. Only a precondition (server-verified access) is mentioned, which is a constraint rather than usage 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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