Google Image Search Results & Metadata Scraper: MCP config, n8n workflow and API
One dataset row per image with original/thumbnail provenance, dimensions when stated, source page metadata, stable image ID and a labelled engine. Per-query completeness telemetry is in the SUMMARY key-value record.
Fastest route, in Claude Code:
claude mcp add --transport http google-image-search-results-and-metadata-scraper "https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper" One click, signs in with Apify on first use:
Any other client, one command (writes the config for 25+ agents, including Windsurf, Zed, Cline and Goose):
npx add-mcp "https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper" --name google-image-search-results-and-metadata-scraper Every file on this page is generated from the Actor's published schema: 51 of 51 checks pass (validated, not run)
- MCP configs: 7 of 7 (Uses Apify's hosted MCP endpoint over HTTPS; The tools parameter lists exactly the chosen Actors as owner/name; JSON configs parse and use the client's top-level key and the same URL; Codex TOML has a [mcp_servers.<name>] table with url and bearer_token_env_var; CLI commands quote the same URL and use the streamable HTTP transport; One-click install links decode back to the same URL and carry no token; Only placeholders, no real token)
- n8n workflow: 11 of 11 (It has a nodes array and a connections object; Every node has a name, type, typeVersion, position and parameters; Node names are unique; Every node type is a known n8n core node (or the Apify node); Every node uses a typeVersion that n8n ships; Every connection points at an existing node; At least one trigger starts the workflow; Every working node is reachable from a trigger; Apify calls use POST and a credential for the token; Actor input matches the Actor's published input schema; No token or credential value is embedded)
- long-run workflow: 11 of 11 (It has a nodes array and a connections object; Every node has a name, type, typeVersion, position and parameters; Node names are unique; Every node type is a known n8n core node (or the Apify node); Every node uses a typeVersion that n8n ships; Every connection points at an existing node; At least one trigger starts the workflow; Every working node is reachable from a trigger; Apify calls use POST and a credential for the token; Actor input matches the Actor's published input schema; No token or credential value is embedded)
- example input: 5 of 5 (The schema has no required fields; Every input key exists in the published input schema; Every value has the type the schema declares; Every choice field uses one of its published options; Numbers respect the published minimum and maximum)
- code snippets: 4 of 4 (curl calls the documented run-sync-get-dataset-items endpoint for this Actor; Python (apify-client 3.x typed Run) and JavaScript use the official apify-client call() then read the run's dataset; Multi-line shell commands continue every line with a backslash; Token read from APIFY_TOKEN, none embedded)
- SKILL.md: 13 of 13 (SKILL.md starts with YAML front matter; name is 1-64 lowercase letters, digits and single hyphens; name matches the skill folder name; description is present, at most 1024 characters and has no angle brackets; front matter uses only spec fields; compatibility is at most 500 characters; body has instructions; field descriptions end on whole sentences; no credential values are embedded; the token is read from APIFY_TOKEN; the run command calls this Actor's run-sync endpoint; the example input is valid JSON; the example input matches the published input schema)
What a run costs
Every run pays a start fee plus a price per result. On the Free plan this Actor's start fee is $0.40 (the start event, $0.10 per GB, times its default 4 GB of memory), $0.12 on Business; results cost $0.99 per 1,000 results (pay per event). Checked 2026-11-12.
| Results in one run | Start | Results | Run total |
|---|---|---|---|
| 10 | $0.40 | $0.010 | $0.41 |
| 100 | $0.40 | $0.10 | $0.50 |
| 1,000 | $0.40 | $0.99 | $1.39 |
Plus Apify platform usage for the run, which the caller pays. A smaller memory setting lowers the start fee if the Actor still finishes. Prices can change; the Store pricing tab is the source of truth.
MCP config
One URL works in every client: https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper. It exposes this Actor as a tool, plus fetch-actor-details so the agent can read the input schema before calling it. Pick your client:
Claude Code configterminal or .mcp.json
claude mcp add --transport http google-image-search-results-and-metadata-scraper "https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper" Run the command in your project folder. Add --scope user to make it available in every project. Full Claude Code setup
Claude Desktop configclaude_desktop_config.json
{
"mcpServers": {
"google-image-search-results-and-metadata-scraper": {
"command": "npx",
"args": [
"-y",
"@apify/actors-mcp-server",
"--tools",
"fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper"
],
"env": {
"APIFY_TOKEN": "YOUR_APIFY_TOKEN"
}
}
}
} Easiest: open Customize, then Connectors, choose Add custom connector, paste the server URL (the ChatGPT tab shows it on its own) and sign in to Apify. Full Claude Desktop setup
Cursor config~/.cursor/mcp.json
{
"mcpServers": {
"google-image-search-results-and-metadata-scraper": {
"url": "https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper",
"headers": {
"Authorization": "Bearer ${env:APIFY_TOKEN}"
}
}
}
} Save as ~/.cursor/mcp.json for every project, or .cursor/mcp.json for one project. Merge with servers you already have. Full Cursor setup
VS Code config.vscode/mcp.json
{
"inputs": [
{
"type": "promptString",
"id": "apify-token",
"description": "Apify API token",
"password": true
}
],
"servers": {
"google-image-search-results-and-metadata-scraper": {
"type": "http",
"url": "https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper",
"headers": {
"Authorization": "Bearer ${input:apify-token}"
}
}
}
} Save as .vscode/mcp.json in your workspace. Full VS Code setup
ChatGPT configPlugins > Add custom MCP server
https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper In ChatGPT on the web, open Plugins, select + and choose Add custom MCP server. Full ChatGPT setup
Codex CLI config~/.codex/config.toml
[mcp_servers.google-image-search-results-and-metadata-scraper]
url = "https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper"
bearer_token_env_var = "APIFY_TOKEN" Add the block to ~/.codex/config.toml, or .codex/config.toml in a project. Full Codex CLI setup
Gemini CLI configterminal (writes ~/.gemini/settings.json)
gemini mcp add -t http -s user -H "Authorization: Bearer $APIFY_TOKEN" google-image-search-results-and-metadata-scraper "https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper" Export APIFY_TOKEN first: the shell expands it and Gemini CLI saves the header, token included, in plain text in ~/.gemini/settings.json (keep that file private). In PowerShell write $env:APIFY_TOKEN instead of $APIFY_TOKEN. Drop -s user to save it in the project's .gemini/settings.json. Full Gemini CLI setup
n8n AI Agent configMCP Client Tool node
https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper Add an AI Agent node, then attach an MCP Client Tool node to its tool input. Full n8n AI Agent setup
Tools your agent gets
Listed by Apify's MCP server 0.21.5 for this exact URL on 2026-11-11 (a tools/list call; nothing was run).
fetch-actor-detailsreads the input schemaget-actor-runchecks a run's statusget-dataset-itemsreads a run's resultsget-key-value-store-recordreads a stored record such as a file or summaryabort-actor-runstops a run that is still goingnimbryxo-studio--google-image-search-results-and-metadata-s-d762runs the Actor and returns its results
n8n workflow
A manual and a daily trigger call the Actor through the HTTP Request node with your Apify token, then hand each record to the destination you pick. The Actor input sits in the request body, already filled with the example below.
- Run by hand
- Every day
- Run Apify Actor
n8n workflowgoogle-image-search-results-and-metadata-scraper.n8n.json
{
"name": "Google Image Search Results & Metadata Scraper to n8n only",
"nodes": [
{
"id": "08871cda-fadb-4a2a-a46c-a7434bda9293",
"name": "Run by hand",
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
0,
0
],
"parameters": {}
},
{
"id": "eb949eda-0991-4d6c-a7e8-8dc17a0f2ffb",
"name": "Every day",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.2,
"position": [
0,
200
],
"parameters": {
"rule": {
"interval": [
{
"triggerAtHour": 8
}
]
}
},
"notes": "Activate the workflow to run on this schedule."
},
{
"id": "152a66e6-65cb-4b11-aa33-5604993f431b",
"name": "Run Apify Actor",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
260,
100
],
"parameters": {
"method": "POST",
"url": "https://api.apify.com/v2/actors/nimbryxo-studio~google-image-search-results-and-metadata-scraper/run-sync-get-dataset-items",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "{\n \"queries\": [\n \"Alfons Mucha\"\n ],\n \"maxResults\": 3,\n \"minWidth\": 0,\n \"minHeight\": 0,\n \"country\": \"US\",\n \"language\": \"en\",\n \"safeSearch\": \"active\",\n \"googleOnly\": false,\n \"enableFallback\": true\n}",
"options": {
"timeout": 310000
}
},
"notes": "Actor: nimbryxo-studio/google-image-search-results-and-metadata-scraper. Select a Header Auth credential: name Authorization, value Bearer + your Apify token. Edit the JSON body to change the input.",
"notesInFlow": false
},
{
"id": "60616bb2-b7f2-49d8-ab32-88c1545b9b6f",
"name": "Setup",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
0,
-370
],
"parameters": {
"content": "## Google Image Search Results & Metadata Scraper\n\nSource: [nimbryxo-studio/google-image-search-results-and-metadata-scraper](https://apify.com/nimbryxo-studio/google-image-search-results-and-metadata-scraper) on Apify.\n\n1. In **Run Apify Actor**, create a Header Auth credential: name `Authorization`, value `Bearer YOUR_APIFY_TOKEN` with your token.\n2. Click **Execute workflow**. Each record arrives as one n8n item.\n3. Edit the JSON body of **Run Apify Actor** to change the input.\n\nGenerated by recipeforagents.com. Validated, not executed: runs are billed to your Apify account.",
"height": 340,
"width": 460,
"color": 6
}
}
],
"connections": {
"Run by hand": {
"main": [
[
{
"node": "Run Apify Actor",
"type": "main",
"index": 0
}
]
]
},
"Every day": {
"main": [
[
{
"node": "Run Apify Actor",
"type": "main",
"index": 0
}
]
]
}
},
"pinData": {},
"active": false,
"settings": {
"executionOrder": "v1"
},
"meta": {
"templateCredsSetupCompleted": false
},
"tags": []
} Import with Workflows, Import from file, or paste into the canvas. Credentials are not included: you select them after import.
All 7 destination variants pass the same checks at build time. Built-in nodes only, at versions n8n has shipped since 1.80: they import on n8n Cloud and older self-hosted instances without community nodes. Prefer Apify's own node? The verified community node @apify/n8n-nodes-apify runs the same Actor with OAuth sign-in on n8n Cloud.
Runs longer than 5 minutes? The synchronous endpoint answers HTTP 408 after 300 seconds. The long-run variant starts the run, checks it every minute until it ends, then reads its dataset (HTTP Request, If and Stop and Error nodes only).
Download the long-run workflow11 of 11 checks pass, not executed
Call it from code
Run the Actor from a script or your own agent framework with the Apify API. The call waits for the run to finish and returns the records. The input is the example below.
curl
curl -X POST "https://api.apify.com/v2/actors/nimbryxo-studio~google-image-search-results-and-metadata-scraper/run-sync-get-dataset-items" \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"queries":["Alfons Mucha"],"maxResults":3,"minWidth":0,"minHeight":0,"country":"US","language":"en","safeSearch":"active","googleOnly":false,"enableFallback":true}' Install: pip install "apify-client>=3"
Python
import os
from apify_client import ApifyClient
client = ApifyClient(os.environ["APIFY_TOKEN"])
run_input = {
"queries": [
"Alfons Mucha",
],
"maxResults": 3,
"minWidth": 0,
"minHeight": 0,
"country": "US",
"language": "en",
"safeSearch": "active",
"googleOnly": False,
"enableFallback": True,
}
run = client.actor("nimbryxo-studio/google-image-search-results-and-metadata-scraper").call(run_input=run_input)
if run is None:
raise RuntimeError("The Actor run could not be started")
print(run.status, "dataset", run.default_dataset_id)
for item in client.dataset(run.default_dataset_id).iterate_items():
print(item) Install: npm install apify-client
JavaScript
import { ApifyClient } from "apify-client";
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const input = {
"queries": [
"Alfons Mucha"
],
"maxResults": 3,
"minWidth": 0,
"minHeight": 0,
"country": "US",
"language": "en",
"safeSearch": "active",
"googleOnly": false,
"enableFallback": true
};
const run = await client.actor("nimbryxo-studio/google-image-search-results-and-metadata-scraper").call(input);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, items[0]); Example input
These values come from the Actor's Store prefill and required defaults. Change the search, URL or limit before your first run.
Actor inputinput.json
{
"queries": [
"Alfons Mucha"
],
"maxResults": 3,
"minWidth": 0,
"minHeight": 0,
"country": "US",
"language": "en",
"safeSearch": "active",
"googleOnly": false,
"enableFallback": true
} | Field | Type | What it does |
|---|---|---|
queries | array | One or more image search queries. Each query is searched independently. Google operators such as site:, quoted phrases and -exclusions are passed through. The legacy single query key is still accepted by the actor… |
maxResults | integer | Maximum number of image rows to return for each query. Google Images usually runs out around 300-400 results for a query; this is a ceiling, not a guarantee. |
minWidth | integer | Drop images narrower than this many pixels. Rows without published dimensions are dropped when this is set. 0 disables the filter. |
minHeight | integer | Drop images shorter than this many pixels. Rows without published dimensions are dropped when this is set. 0 disables the filter. |
country | string (264 options) | Two-letter country used for Google's gl parameter (and Bing's cc parameter). Local sites rank higher in local results. |
language | string (187 options) | Interface and result language used for Google's hl parameter (and Bing's setlang parameter). |
safeSearch | string (2 options) | Google SafeSearch level. 'active' filters explicit images; 'off' does not. |
imageSize | string (11 options) | Google Images size filter. The MP values are minimum megapixels. Bing fallback applies the nearest size category and enforces the exact MP floor locally when dimensions are known. |
imageColor | string (16 options) | Google Images color filter. 'black_and_white' is grayscale; 'transparent' looks for a transparent background. |
imageType | string (6 options) | Google Images type filter: photographs, faces, clip art, line drawings or animated images. |
fileType | string (8 options) | Only images in this format. Google applies this server-side; Bing fallback applies it to the image URL extension locally. |
timeRange | string (6 options) | Only images Google found within this period. Bing fallback maps 'hour' to its 24-hour window. |
usageRights | string (5 options) | Google's usage-rights labels. These are Google's labels, not a legal guarantee; check the licence on the source page before reuse. |
googleOnly | boolean | When true, a failed or empty Google search fails that query with a clear status instead of using another engine. The default is false so legacy saved tasks keep working; set this true for a strict Google-only contract. |
enableFallback | boolean | When googleOnly is false, allow labelled Bing Images and then DuckDuckGo Images. Every fallback row carries engine, isFallback=true and fallbackReason. |
What your agent receives
Each run returns a list of records. The Actor publishes 29 fields, starting with page, engine, retrievalMethod, isFallback.
| Field | What it holds | Format |
|---|---|---|
query | Query | text |
position | Position | number |
page | Page | number |
engine | Engine | text |
retrievalMethod | Method | text |
isFallback | Fallback | boolean |
fallbackReason | Fallback reason | text |
searchUrl | Search URL | text |
fetchedAt | Fetched at | text |
imageId | Image ID | text |
19 more fields
| Field | What it holds | Format |
|---|---|---|
imageUrl | Image URL | text |
imageUrlType | URL type | text |
isCrawlerOnly | Crawler only | boolean |
hasOriginal | Has original | boolean |
imageWidth | Width | number |
imageHeight | Height | number |
aspectRatio | width divided by height, rounded to three decimals | number |
orientation | landscape, portrait or square, derived from the stated dimensions | string |
fileFormat | Image format derived from the URL extension, when known | string |
thumbnailUrl | URL of the engine's cached thumbnail | string |
thumbnailWidth | Thumbnail width in pixels, when the engine states it | integer |
thumbnailHeight | Thumbnail height in pixels, when the engine states it | integer |
title | Title | text |
sourcePageTitle | Title of the source page containing the image | string |
origin | Legacy field: domain of the source page, or of the image host when no page is known | string |
sourceDomain | Source domain | text |
siteName | Site name the engine displays, or the source domain when no display name is available | string |
contentUrl | URL of the web page containing the image | string |
googleUrl | Google imgres reference URL, when the row came from Google | string |
Agent skill
A SKILL.md in the open Agent Skills format. It teaches Claude Code, Codex and other skill-aware agents when to call this Actor, how to build the input and how to read the result, using the API directly.
SKILL.mdgoogle-image-search-results-and-metadata-scraper/SKILL.md
---
name: google-image-search-results-and-metadata-scraper
description: "One dataset row per image with original/thumbnail provenance, dimensions when stated, source page metadata, stable image ID and a labelled engine. Per-query completeness telemetry is in the SUMMARY key-value record. Runs the Apify Actor nimbryxo-studio/google-image-search-results-and-metadata-scraper. Use when the user needs Google Search data with fields such as query, position, page, engine, retrievalMethod, isFallback and an Apify token is available."
compatibility: "Needs network access, curl, and an APIFY_TOKEN environment variable. Runs are billed to the token owner's Apify account."
metadata:
actor: "nimbryxo-studio/google-image-search-results-and-metadata-scraper"
store-url: "https://apify.com/nimbryxo-studio/google-image-search-results-and-metadata-scraper"
---
# Google Image Search Results & Metadata Scraper
Use this skill to fetch Google Search data with the Apify Actor `nimbryxo-studio/google-image-search-results-and-metadata-scraper` and work with the returned rows.
## Before running
1. Check that `APIFY_TOKEN` is set in the environment. Never print it or write it to a file.
2. Build `input.json` from the user's request using the fields below. Keep limits small for a first run.
3. Confirm the search terms or URLs with the user if the request is ambiguous.
## Input fields
| Field | Type | Meaning |
| --- | --- | --- |
| `queries` | array | One or more image search queries. Each query is searched independently. Google operators such as site:, quoted phrases and -exclusions are passed through. The legacy single `query` key is still accepted by the actor code. |
| `maxResults` | integer | Maximum number of image rows to return for each query. Google Images usually runs out around 300-400 results for a query; this is a ceiling, not a guarantee. |
| `minWidth` | integer | Drop images narrower than this many pixels. Rows without published dimensions are dropped when this is set. 0 disables the filter. |
| `minHeight` | integer | Drop images shorter than this many pixels. Rows without published dimensions are dropped when this is set. 0 disables the filter. |
| `country` | string | Two-letter country used for Google's gl parameter (and Bing's cc parameter). Local sites rank higher in local results. |
| `language` | string | Interface and result language used for Google's hl parameter (and Bing's setlang parameter). |
| `safeSearch` | one of `active`, `off` | Google SafeSearch level. 'active' filters explicit images; 'off' does not. |
| `imageSize` | string | Google Images size filter. The MP values are minimum megapixels. Bing fallback applies the nearest size category and enforces the exact MP floor locally when dimensions are known. |
| `imageColor` | string | Google Images color filter. 'black_and_white' is grayscale; 'transparent' looks for a transparent background. |
| `imageType` | one of `photo`, `face`, `clipart`, `lineart`, `animated` | Google Images type filter: photographs, faces, clip art, line drawings or animated images. |
| `fileType` | one of `jpg`, `png`, `gif`, `bmp`, `svg`, `webp`, `ico` | Only images in this format. Google applies this server-side; Bing fallback applies it to the image URL extension locally. |
| `timeRange` | one of `hour`, `day`, `week`, `month`, `year` | Only images Google found within this period. Bing fallback maps 'hour' to its 24-hour window. |
| `usageRights` | one of `free_to_use_or_share`, `free_to_use_or_share_commercially`, `free_to_use_share_or_modify`, `free_to_use_share_or_modify_commercially` | Google's usage-rights labels. These are Google's labels, not a legal guarantee; check the licence on the source page before reuse. |
| `googleOnly` | boolean | When true, a failed or empty Google search fails that query with a clear status instead of using another engine. The default is false so legacy saved tasks keep working; set this true for a strict Google-only contract. |
Example `input.json` (the Actor's published prefill):
```json
{
"queries": [
"Alfons Mucha"
],
"maxResults": 3,
"minWidth": 0,
"minHeight": 0,
"country": "US",
"language": "en",
"safeSearch": "active",
"googleOnly": false,
"enableFallback": true
}
```
## Run
```bash
curl -sS -X POST "https://api.apify.com/v2/acts/nimbryxo-studio~google-image-search-results-and-metadata-scraper/run-sync-get-dataset-items" \
-H "Authorization: Bearer $APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d @input.json > results.json
```
The call waits for the run to finish and returns the dataset items as a JSON array. If the run needs more than 300 seconds the API answers with HTTP 408; then start the run with `POST /v2/acts/nimbryxo-studio~google-image-search-results-and-metadata-scraper/runs`, poll `GET /v2/actor-runs/{runId}` until `SUCCEEDED`, and read `GET /v2/datasets/{defaultDatasetId}/items`.
## Output
Each item is one record. Published fields include: `query`, `position`, `page`, `engine`, `retrievalMethod`, `isFallback`, `fallbackReason`, `searchUrl`, `fetchedAt`, `imageId`, `imageUrl`, `imageUrlType`, `isCrawlerOnly`, `hasOriginal`, `imageWidth`, `imageHeight`, `aspectRatio`, `orientation`, `fileFormat`, `thumbnailUrl`.
Summarise what was found, cite the record URLs when present, and say how many items came back. Do not invent values for empty fields.
- Claude Code: save it as
~/.claude/skills/google-image-search-results-and-metadata-scraper/SKILL.md, or.claude/skills/google-image-search-results-and-metadata-scraper/SKILL.mdin a project. - Codex and other agents:
~/.agents/skills/google-image-search-results-and-metadata-scraper/SKILL.md, or.agents/skills/google-image-search-results-and-metadata-scraper/in a project. - Or let the skills CLI place it for your agent:
npx skills add https://recipeforagents.com --skill google-image-search-results-and-metadata-scraper - Set
APIFY_TOKENin the agent's environment.
Troubleshooting
Why does the client say Unauthorized or invalid token?
Every Apify Actor tool needs a signed-in Apify account. Reconnect the server so the OAuth sign-in runs again, or switch to the token variant: an Authorization: Bearer header with an API token from Apify Console, Settings, API and integrations. For a local server the token must be in the server's own env block, not only in your shell.
Source: Apify MCP server README
Why did my agent's tool list change after an update?
Without a tools parameter Apify's server loads its default tool set, which changes between releases. The URLs on this site pin the tools with ?tools=, so the agent always gets the same Actor tool plus fetch-actor-details. Apify's README gives the same advice for production.
Source: Apify MCP server README
What happens when the agent sends input the Actor rejects?
The server answers with the Actor's input schema, so the agent can fix the arguments and call again. The fetch-actor-details tool in every scoped URL lets it read that schema before the first call.
Source: Apify MCP server README
Questions
How do I connect Google Image Search Results & Metadata Scraper to Claude?
In Claude Code run: claude mcp add --transport http google-image-search-results-and-metadata-scraper "https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper". In Claude Desktop or claude.ai add a custom connector with the URL https://mcp.apify.com/?tools=fetch-actor-details,nimbryxo-studio/google-image-search-results-and-metadata-scraper and sign in to Apify. The agent then gets one tool for this Actor plus a tool that reads its input schema.
What input does Google Image Search Results & Metadata Scraper need?
No field is required by the published input schema. The example on this page uses the Actor's own Store prefill, so it is a sensible first run.
What does Google Image Search Results & Metadata Scraper cost to run?
The Apify Store lists $0.99 per 1,000 results (pay per event) for this Actor, checked 2026-11-12. Runs are billed to the Apify account whose token or sign-in the agent uses; Apify platform usage can add to that.
Which tools does the MCP config give my agent?
6 tools: fetch-actor-details, get-actor-run, get-dataset-items, get-key-value-store-record, abort-actor-run, nimbryxo-studio--google-image-search-results-and-metadata-s-d762. Apify's MCP server listed them for this exact URL on 2026-11-11.
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