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search_volume

Read-only

Retrieve monthly search volume, CPC, and competition metrics for up to 1,000 keywords in a specified location, with country-level fallback when local data is unavailable.

Instructions

Use when you have specific keywords and need monthly volume, CPC, and competition data. Accepts up to 1000 keywords. Returns search_volume, cpc, competition, competition_level, and monthly_searches trend. Volumes are locally scoped when the location is a city/state (volume_scope: "local", data_source: "google_ads"); falls back to country-level numbers when local data is unavailable (volume_scope: "country") — check location_used for the actual scope. If location_alternatives is present, the location has sibling entities (e.g. "Hamilton" vs "Hamilton Township", NJ) whose volumes can differ 3-5x — check them before treating one number as the whole market. A null search_volume means no data, not zero searches. Costs 72 credits.

Input Schema

Name	Required	Description
`keywords`	Yes	Array of keywords to analyze
`language`	No	Language as ISO 639-1 code or name (e.g. "fr", "fr-FR", "French"). Defaults to English wherever we hold an English database for that country, and to the largest database that country has otherwise.
`location`	Yes	Geographic location (e.g. "Orchard Park, NY")

Output Schema

Name	Required	Description	Default
`keywords`	Yes
`language`	Yes
`location`	Yes
`data_source`	No
`total_count`	Yes
`volume_scope`	No
`location_used`	No
`location_alternatives`	No
`country_fallback_unavailable`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedv1.1.0Oct 22, 2026

changedInput schema / properties / language / description

Previous value: -"Language code. Default: \"en\""New value: +"Language as ISO 639-1 code or name (e.g. \"fr\", \"fr-FR\", \"French\"). Defaults to English wherever we hold an English database for that country, and to the largest database that country has otherwise."

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "country_fallback_unavailable": {
+      "type": "string"
+    },
+    "data_source": {
+      "enum": [
+        "google_ads",
+        "labs"
+      ],
+      "type": "string"
+    },
+    "keywords": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "competition": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "competition_level": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "cpc": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "keyword": {
+            "type": "string"
+          },
+          "monthly_searches": {
+            "items": {
+              "additionalProperties": true,
+              "properties": {
+                "month": {
+                  "type": [
+                    "number",
+                    "null"
+                  ]
+                },
+                "search_volume": {
+                  "type": [
+                    "number",
+                    "null"
+                  ]
+                },
+                "year": {
+                  "type": [
+                    "number",
+                    "null"
+                  ]
+                }
+              },
+              "required": [
+                "year",
+                "month",
+                "search_volume"
+              ],
+              "type": "object"
+            },
+            "type": "array"
+          },
+          "search_volume": {
+            "type": [
+              "number",
+              "null"
+            ]
+          }
+        },
+        "required": [
+          "keyword",
+          "search_volume",
+          "cpc",
+          "competition",
+          "competition_level",
+          "monthly_searches"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "language": {
+      "type": "string"
+    },
+    "location": {
+      "type": "string"
+    },
+    "location_alternatives": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "code": {
+            "type": "number"
+          },
+          "name": {
+            "type": "string"
+          },
+          "type": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "name",
+          "code",
+          "type"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "location_used": {
+      "type": "string"
+    },
+    "total_count": {
+      "type": "number"
+    },
+    "volume_scope": {
+      "enum": [
+        "local",
+        "country"
+      ],
+      "type": "string"
+    }
+  },
+  "required": [
+    "keywords",
+    "total_count",
+    "location",
+    "language"
+  ],
+  "type": "object"
+}

First observedv0.1.0May 11, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Goes well beyond the readOnly/openWorld annotations: discloses local-vs-country fallback logic with volume_scope values, the location_alternatives trap (3-5x divergence for sibling entities), the null-means-no-data rule, the 1000-keyword ceiling, and the 72-credit cost. That is exactly the caveat material an agent cannot get from structured fields.

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?

Front-loads the trigger, then returns, then scope caveats, then cost — good ordering with no filler. The explicit return-field list partly duplicates the output schema that already exists, which is the only wasted material.

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 an open-world, credit-charging lookup with a complex geo-scoping failure mode, it covers inputs, outputs, fallbacks, cost, and null semantics. Nothing an agent needs in order to call it correctly and interpret results is missing.

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?

Schema coverage is 100%, so baseline is 3; the description adds real semantic depth on `location` by explaining local vs country scoping, location_used, and location_alternatives divergence. It does not touch `language` at all, so it does not fully round out all three parameters.

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?

States a specific verb+resource (keyword search volume) and enumerates exactly which metrics are returned (volume, CPC, competition, trend), which implicitly separates it from discovery siblings like keyword_suggestions or keyword_trends. An agent can tell this is the metrics-lookup tool, not a keyword-generation tool.

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?

Opens with a clear trigger: 'Use when you have specific keywords and need monthly volume, CPC, and competition data,' which sets the precondition (you must already have keywords). It does not name an alternative tool or state when to prefer a sibling instead, so it stops short of the 5 bar.

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