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organic_serp

Read-only

Retrieves the full Google results page for a keyword and location, including organic listings, local pack, ads, People Also Ask, AI overview, and knowledge panel, to audit overall search presence.

Instructions

Use when you need the complete Google search results page in one call: organic listings, local pack, ads, People Also Ask, AI overview, LSA ads, and knowledge panel. Best for auditing overall search presence. Costs 2 credits.

Input Schema

Name	Required	Description	Default
`keyword`	Yes	Search keyword (e.g. "best plumber near me")
`location`	Yes	City and state (e.g. "Orchard Park, NY")

Output Schema

Name	Required	Description	Default
`ads`	Yes
`lsa_ads`	Yes
`local_pack`	Yes
`ai_overview`	Yes
`location_used`	No
`knowledge_panel`	Yes
`organic_results`	Yes
`people_also_ask`	Yes
`location_alternatives`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv1.1.0Oct 22, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": true,
+  "properties": {
+    "ads": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "description": {
+            "type": "string"
+          },
+          "position": {
+            "type": "string"
+          },
+          "title": {
+            "type": "string"
+          },
+          "url": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "position",
+          "title",
+          "url",
+          "description"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "ai_overview": {
+      "type": [
+        "string",
+        "null"
+      ]
+    },
+    "knowledge_panel": {
+      "anyOf": [
+        {
+          "additionalProperties": true,
+          "properties": {
+            "description": {
+              "type": "string"
+            },
+            "image_url": {
+              "type": [
+                "string",
+                "null"
+              ]
+            },
+            "subtitle": {
+              "type": "string"
+            },
+            "title": {
+              "type": "string"
+            },
+            "url": {
+              "type": [
+                "string",
+                "null"
+              ]
+            }
+          },
+          "required": [
+            "title",
+            "subtitle",
+            "description",
+            "url",
+            "image_url"
+          ],
+          "type": "object"
+        },
+        {
+          "type": "null"
+        }
+      ]
+    },
+    "local_pack": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "cid": {
+            "type": "string"
+          },
+          "name": {
+            "type": "string"
+          },
+          "rank": {
+            "type": "number"
+          },
+          "rating": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "reviews_count": {
+            "type": "number"
+          }
+        },
+        "required": [
+          "rank",
+          "name",
+          "cid",
+          "rating",
+          "reviews_count"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "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"
+    },
+    "lsa_ads": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "business_name": {
+            "type": "string"
+          },
+          "rank": {
+            "type": "number"
+          },
+          "rating": {
+            "type": [
+              "number",
+              "null"
+            ]
+          },
+          "reviews_count": {
+            "type": "number"
+          }
+        },
+        "required": [
+          "rank",
+          "business_name",
+          "rating",
+          "reviews_count"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "organic_results": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "organic_position": {
+            "type": "number"
+          },
+          "rank": {
+            "type": "number"
+          },
+          "snippet": {
+            "type": [
+              "string",
+              "null"
+            ]
+          },
+          "title": {
+            "type": "string"
+          },
+          "url": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "rank",
+          "title",
+          "url",
+          "snippet"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "people_also_ask": {
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "organic_results",
+    "local_pack",
+    "ads",
+    "people_also_ask",
+    "ai_overview",
+    "lsa_ads",
+    "knowledge_panel"
+  ],
+  "type": "object"
+}

First observedv0.1.0May 11, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already establish readOnly/openWorld/non-destructive, so the description doesn't need to restate safety. It adds genuinely useful operational context the annotations lack: credit cost (2 credits) and the breadth of returned sections. It doesn't cover pricing edge cases (e.g. whether credits are consumed on empty results), keeping it just under a 5.

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 sentences plus a cost note; the use condition leads, the component list follows, and the practical cost detail comes last. Nothing is redundant or padded.

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 annotations covering safety, an output schema present, and full parameter documentation, the remaining burden on the description is selection context and cost — both supplied. Minor gaps (per-result credit behavior, geography variability) are low-impact for a read-only SERP tool.

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%, with keyword and location documented with examples in the schema itself. The description adds no additional semantics about parameter formats or constraints, so the baseline 3 applies.

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 description names a specific verb-and-resource pairing ('complete Google search results page in one call') and enumerates exactly what comes back (organic listings, local pack, ads, PAA, AI overview, LSA ads, knowledge panel). That enumeration also implicitly distinguishes it from single-component siblings such as local_pack, ai_overview, and local_services_ads.

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?

'Use when you need the complete ... in one call' and 'Best for auditing overall search presence' give a clear selection context. It stops short of explicitly naming the alternative single-surface tools or saying when not to use it (e.g. when only a local pack is needed, use local_pack), so it's clear but not fully routing-guiding.

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