Yandex Reverse Image Search Server

The most efficient, reliable, and developer-friendly way to use the Yandex Reverse Image Search API.

Actor page: apify.com/johnvc/yandex-reverse-image-search Input schema: apify.com/johnvc/yandex-reverse-image-search/input-schema

Search by image instead of by keywords. Give this reverse image search API the public URL of any image and it searches Yandex's reverse image engine (the same one behind yandex.com/images) to find every page where the image appears online, visually similar images, other sizes and resolutions of the same image, products that match the image, and descriptive tags. Every result is one JSON row tagged with a result_type field, so you can filter and route the data straight into your own code. Pay per result, with a hard cap you control.

Video Walkthrough

Watch the walkthrough

Quick Start

Prerequisites

• Python 3.11 or higher
• An Apify account and API key (get a free key here)

1. Clone the repository

   git clone https://github.com/johnisanerd/Apify-Yandex-Reverse-Image-Search-API.git
   cd Apify-Yandex-Reverse-Image-Search-API
   

2. Install dependencies with UV

   # Install UV if you do not have it:
   curl -LsSf https://astral.sh/uv/install.sh | sh
   
   # Install project dependencies:
   uv sync
   

3. Configure your API key

   cp .env.example .env
   # Edit .env and add your Apify API key
   # Get your free API key at: https://apify.com?fpr=9n7kx3
   

4. Run the example

   uv run python yandex-reverse-image-search-api-example.py
   

Alternative: set the API key directly

export APIFY_API_TOKEN="your_api_key_here"
uv run python yandex-reverse-image-search-api-example.py

Why Use This Reverse Image Search API?

Search by image, not by keyword. A normal image search takes words and returns pictures. This reverse image search API does the opposite: you hand it a picture and it returns where that picture appears online, what looks similar to it, and what is in it. That is the difference between guessing a caption and asking the web directly.

Yandex coverage as a clean API. Yandex is widely regarded as one of the strongest reverse image engines on the web, especially for faces, places, and content that Western engines miss. This actor gives you that reach as a typed JSON endpoint, no HTML, no tokens, no blocking to manage on your side.

One row per result, tagged and filterable. Every result comes back as a single dataset row with a result_type field, so you can split matching pages from similar images from shopping matches in one pass and send each type where it belongs.

Cost you control. Billing is one charge per result row. You decide which result types to turn on and set a max_results cap, so a first run can be a few cents and a monitoring run can be tightly bounded.

Built for automation and source hunting. Save an image as a task, put it on a schedule, and re-check Yandex for new copies over time. It is a practical base for brand protection, counterfeit detection, image provenance work, and source hunting, tracing a compressed or cropped image back to its original.

Features

Core Capabilities

• Search by any public image URL and get every page where the image appears, with title, link, snippet, and source.
• Retrieve visually similar images from across the web, with thumbnails and full-size links.
• Optional result types: other resolutions of the same image, descriptive image tags, matching shop products with prices, and a knowledge-graph entity card.
• Crop-box targeting: search only part of an image (one face in a group photo, one product on a shelf).
• Six regional Yandex domains (yandex.com, yandex.ru, yandex.by, yandex.kz, yandex.uz, yandex.com.tr).

Data Quality

• Structured JSON with a result_type tag on every row for easy filtering.
• A max_results cap that bounds both the rows returned and the amount billed.
• Consistent fields (title, link, source, original, thumbnail, search timestamp) across matching pages and similar images.

Usage Examples

Basic Example

{
  "image_url": "https://example.com/product.jpg",
  "max_results": 20
}

Advanced Example

{
  "image_url": "https://example.com/group-photo.jpg",
  "crop": "0.1;0.2;0.5;0.8",
  "include_matching_pages": true,
  "include_similar_images": true,
  "include_shopping_results": true,
  "yandex_domain": "yandex.ru",
  "max_results": 100
}

Input Parameters

Parameter	Type	Required	Default	Description
image_url	str	YES	-	Public http(s) URL of the image to search by. Yandex fetches it, so it must be reachable from the internet (direct image link, no login or redirect).
crop	str	no	(none)	Search only part of the image: four ;-separated fractions 0-1 in the order left;top;right;bottom, e.g. 0.1;0.2;0.9;0.8.
include_matching_pages	bool	no	true	Pages where the image appears online (result_type matching_page).
include_similar_images	bool	no	true	Visually similar images (result_type similar_image).
include_image_sizes	bool	no	false	Other resolutions of the same image (result_type image_size).
include_image_tags	bool	no	false	Descriptive tags for the image content (result_type image_tag).
include_shopping_results	bool	no	false	Matching products with prices (result_type shopping_result).
include_knowledge_graph	bool	no	false	Entity card for recognizable subjects (result_type knowledge_graph).
yandex_domain	str	no	yandex.com	Regional domain: yandex.com, yandex.ru, yandex.by, yandex.kz, yandex.uz, yandex.com.tr.
max_results	int	no	0	Hard cap on rows returned and billed. 0 = everything found. Set 20 for a cheap first run.

Output Format

Each result is one dataset row tagged with a result_type. A matching_page row looks like this:

{
  "result_type": "matching_page",
  "position": 27,
  "title": "Central Illustration Agency Illustration portfolio: Matt Taylor",
  "link": "https://tr.pinterest.com/pin/matt-taylor-digital-illustration-illustrator-graphic-poster-art-car-scenery-bold--826762444071832079/",
  "thumbnail": "https://avatars.mds.yandex.net/i?id=592d913ed53e1f78fdd0804bd7064417b709bafb-5437458-images-thumbs&n=13&w=296&h=180",
  "original": "https://i.pinimg.com/736x/9e/b1/f7/9eb1f76ee45eb01706be89b8748a911b.jpg",
  "source": "tr.pinterest.com",
  "snippet": "After graduating from Buckinghamshire University he rolled straight into a successful ten year illustration career.",
  "image_url": "https://substack-post-media.s3.amazonaws.com/public/images/edbfb2cd-ebcb-4527-bec7-5315c182278f_445x445.png",
  "yandex_domain": "yandex.com",
  "crop": "",
  "search_timestamp": "2026-07-05T12:00:00"
}

Every row also carries the query image URL, the Yandex domain used, the crop box (if any), and a search timestamp.

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Install in Claude Cowork Desktop

Cowork is the desktop app's automation mode. To give it the Yandex Reverse Image Search API as a tool, add the Apify MCP server as a connector.

1. Open the Claude desktop app and go to Settings → Connectors (or Settings → Developer → Edit Config to edit claude_desktop_config.json directly).
   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%\Claude\claude_desktop_config.json
2. Add the Apify MCP server, preloaded with only this Actor:

{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote",
        "https://mcp.apify.com/?tools=actors,docs,johnvc/yandex-reverse-image-search"
      ]
    }
  }
}

3. Restart the app. When Cowork first calls the tool, complete the OAuth prompt in your browser, or add your Apify API token in the connector settings to skip OAuth.
4. In a Cowork chat, confirm the tool is available and ask it to run the Yandex Reverse Image Search API.

Download the desktop app and start a free trial: https://claude.ai/referral/uIlpa7nPLg More help: https://docs.apify.com/platform/integrations/claude-desktop

Install in Claude Code

Claude Code is the command-line tool. Add the Actor's MCP server with one command:

claude mcp add --transport http apify \
  "https://mcp.apify.com/?tools=actors,docs,johnvc/yandex-reverse-image-search"

To use a token instead of browser OAuth:

claude mcp add --transport http apify \
  "https://mcp.apify.com/?tools=actors,docs,johnvc/yandex-reverse-image-search" \
  --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Then verify with claude mcp list, or run /mcp inside a session. Ask Claude Code to call the Yandex Reverse Image Search API.

Try Claude Code free: https://claude.ai/referral/uIlpa7nPLg Claude Code MCP docs: https://code.claude.com/docs/en/mcp

Install in Claude (website)

On claude.ai you add Apify as a connector, then enable just this Actor's tool.

1. Go to Settings → Connectors → Browse connectors and search for Apify MCP server. Install it (enable or update if prompted).
2. When connecting, authenticate with your Apify API token, and enable the tool johnvc/yandex-reverse-image-search.
3. In any chat, open + → Connectors and turn on Apify.
4. Alternatively, choose Add custom connector and paste the full MCP URL https://mcp.apify.com/?tools=actors,docs,johnvc/yandex-reverse-image-search, using OAuth when prompted.
5. Ask Claude to run the Yandex Reverse Image Search API.

Open Claude on the web: https://claude.ai

Install in Cursor

Cursor reads MCP servers from a project file at .cursor/mcp.json.

1. In your project, create .cursor/mcp.json:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/yandex-reverse-image-search"
    }
  }
}

2. If you prefer token auth over browser OAuth, add a header:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/yandex-reverse-image-search",
      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }
    }
  }
}

3. Open Cursor → Settings → MCP and confirm the apify server is connected (green dot).
4. In Composer or Chat, ask Cursor to call the Yandex Reverse Image Search API.

New to Cursor? Get it here: https://cursor.com/referral?code=XQP4VBLI3NNX

Install in ChatGPT

ChatGPT connects to the Apify MCP server through Developer mode (available on ChatGPT Pro, Plus, Business, Enterprise, and Education plans).

1. Click your profile icon, then go to Settings > Apps. If you do not see a Create app button, open Advanced settings and enable Developer mode.
2. Click Create app and fill out the form:
   • Name: Apify
   • MCP Server URL: https://mcp.apify.com/?tools=actors,docs,johnvc/yandex-reverse-image-search
   • Authentication: OAuth
3. Click Create and authorize the connection with Apify.
4. To use the app in a conversation, click + in the chat, choose Developer mode, and select Apify.

More help: https://docs.apify.com/platform/integrations/mcp

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Made with care

Use the Yandex Reverse Image Search API to power your image monitoring, brand protection, and source hunting workflows with reliable, structured results.

Last Updated: 2026.07.11