Skip to main content
Glama

cloro

by dev.cloro
OverviewDiscussionsAdmin

Scrape Google AI Mode

scrape_google_ai_mode
Read-only

Submit a prompt to Google AI Mode from a chosen country and return the AI answer with cited sources. Supports location or UULE targeting and desktop/mobile emulation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
glNoISO 3166-1 alpha-2 code for the result geography, sent to Google as gl (e.g. "us"). Use list_countries to see supported codes per model.
hlNoOptional Google interface-language code, sent as hl (e.g. "de", "pt-br"). Defaults to the language derived from gl — set it when the geography's dominant language is not the one you want.
uuleNoOptional Google UULE location parameter. Mutually exclusive with location.
deviceNoDevice type to emulate. Defaults to desktop.desktop
promptYesThe prompt to submit to Google AI Mode.
countryNoISO 3166-1 alpha-2 country code to geo-target the request from (e.g. "US"). Use list_countries to see supported codes per model. Deprecated — use gl instead; country is kept for compatibility and must not disagree with gl.
includeNoOptional flags for heavier payload fields, each off by default: markdown (the answer rendered as markdown), html (the answer page HTML), rawResponse (the engine's unprocessed response payload). Leave unset for the leanest response.
locationNoOptional location name to target search results (e.g. "Austin, Texas, United States"). Mutually exclusive with uule.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / properties / include / properties / googleGoto
      Removed value: -{
-  "type": "boolean"
-}
  2. Changed1 schema field changed
    • changedInput schema / properties / include / description
      Previous value: -"Optional flags to include heavier payload fields in the response. Leave unset for the leanest response."New value: +"Optional flags for heavier payload fields, each off by default: markdown (the answer rendered as markdown), html (the answer page HTML), rawResponse (the engine's unprocessed response payload). Leave unset for the leanest response."
  3. Changed1 schema field changed
    • addedInput schema / properties / include / properties / googleGoto
      Added value: +{
+  "type": "boolean"
+}
  4. Changed4 schema fields changed
    • changedInput schema / properties / country / description
      Previous value: -"ISO 3166-1 alpha-2 country code to geo-target the request from (e.g. \"US\"). Use list_countries to see supported codes per model."New value: +"ISO 3166-1 alpha-2 country code to geo-target the request from (e.g. \"US\"). Use list_countries to see supported codes per model. Deprecated — use gl instead; country is kept for compatibility and must not disagree with gl."
    • addedInput schema / properties / gl
      Added value: +{
+  "description": "ISO 3166-1 alpha-2 code for the result geography, sent to Google as gl (e.g. \"us\"). Use list_countries to see supported codes per model.",
+  "type": "string"
+}
    • addedInput schema / properties / hl
      Added value: +{
+  "description": "Optional Google interface-language code, sent as hl (e.g. \"de\", \"pt-br\"). Defaults to the language derived from gl — set it when the geography's dominant language is not the one you want.",
+  "type": "string"
+}
    • changedInput schema / required
      Previous value: -[
-  "prompt",
-  "country"
-]New value: +[
+  "prompt"
+]
  5. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=true, and destructiveHint=false, covering safety expectations. The description adds useful behavioral context beyond annotations by stating that requests can be geo-targeted, support location/UULE targeting, and emulate desktop/mobile, and that the response contains an AI answer with cited sources. No contradiction with annotations.

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?

The main description is a single dense sentence that front-loads the core action, target, and key capabilities without any fluff. Every clause adds value: the prompt submission, country selection, cited sources, and targeting/emulation options.

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 an 8-parameter tool with a nested include object and no output schema, the description plus the detailed schema provides enough context to invoke the tool correctly. It states the return shape ('AI answer with cited sources') and points to list_countries for valid codes. It remains slightly thin on response structure and edge-case behavior, but the annotations and schema compensate.

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 coverage is 100% with generally strong parameter descriptions, so a baseline of 3 would normally apply. However, the include property description lists 'rawResponse' which is not present in the schema's include properties, while failing to mention 'expandProducts'. This inaccuracy can mislead an agent into setting a nonexistent flag, significantly undermining parameter semantic quality.

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 uses a specific verb phrase, 'Submit a prompt to Google AI Mode', and names the exact resource, distinguishing it from generic Google search and sibling AI scrapers like scrape_gemini or scrape_chatgpt. The mention of 'AI answer with cited sources' further clarifies that this is the AI Mode endpoint, not a standard search 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?

The description provides clear context for when to use the tool: when an agent needs Google AI Mode results rather than regular Google results or another AI assistant. It also adds targeting and emulation context. However, it does not explicitly name alternatives or say when not to use this tool, so it does not fully earn a 5.

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

All cloro toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources