Yandex Search

io.github.johnisanerd由 GitHub 账号 johnisanerd 发布v1.0.0更新于 Oct 24, 2026

Yandex search results, images, and SERP data via the Apify Yandex Search Scraper, hosted MCP.

已验证Streamable HTTP可网页运行网页搜索与抓取数据与分析

概览

AI 生成的概览

托管在 Apify 的 MCP 端点,让助手执行 Yandex 搜索并获取结构化 JSON 结果、广告、知识卡片、图片和视频。

可以做什么
  • 在 Yandex 上执行关键词搜索,并以结构化 JSON 返回结果页
  • 可选择要采集的结果块:自然结果、付费广告、知识图谱卡片、内嵌图片和内嵌视频
  • 支持 6 个 Yandex 域名、19 种语言和地区 ID,并提供排序、时效、安全搜索和拼写纠正选项
  • 控制分页和每页结果数,输出中包含每页元数据
适用场景
适合面向俄语及独联体市场的 SEO 研究、竞品情报和品牌监测,或当助手需要 Yandex 而非其他搜索引擎的结果时使用。
运行要求
远程 MCP 端点 mcp.apify.com,并预加载 Scrape-Yandex Actor。需要 Apify 账号并完成认证:浏览器 OAuth,或以 Authorization Bearer 头传入 Apify API 令牌。需要能访问 Apify 的网络。
安装前请注意
按运行次数加处理页数计费,页数上限直接决定花费。Apify API 令牌属于凭据,请勿放入共享配置。搜索查询会发送给 Apify 和 Yandex。

安装

在 SourceWeft 中

  1. 打开 控制台中的 Yandex Search,将其添加到工作区。
  2. 连接 所需的 凭据。它们会被私密存储,绝不会在公开页面上展示。
  3. 为需要使用其工具的对话启用该服务。

Web executable,通过 Streamable HTTP。 远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体,或 SourceWeft 对话中。智能体会读取该服务器的安装指南,先向你展示发布者、端点和登录方式,经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.johnisanerd%2Fyandex-search/install.md,并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前,先告诉我它的发布者、端点和登录方式,等我确认。不要把 API 密钥写进命令或我会提交的文件;问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。 客户端会在首次连接时完成 OAuth 登录。

{
  "mcpServers": {
    "yandex-search": {
      "type": "http",
      "url": "https://mcp.apify.com/?tools=johnvc/Scrape-Yandex"
    }
  }
}

README

English | Русский

🔎 Yandex API: Structured Yandex Search Results in Clean JSON

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

Actor page: apify.com/johnvc/Scrape-Yandex Input schema: apify.com/johnvc/Scrape-Yandex/input-schema

The Yandex API runs a Yandex search for any query and returns clean, structured JSON. Choose the result types you want a la carte (organic listings, paid ads, knowledge graph entity cards, inline image panels, inline video panels); each selected type comes back as its own item tagged with item_type, plus per-page metadata. It supports 6 Yandex domains, 19 languages, and region targeting across 123,000+ locations, with sort/recency filters and fast parallel pagination.

Video Walkthrough

[Watch the walkthrough]

Quick Start

Prerequisites

  1. Clone the repository

    bash
    git clone https://github.com/johnisanerd/Apify-Yandex-Search-Scraper.gitcd Apify-Yandex-Search-Scraper
  2. Install dependencies with UV

    bash
    # 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

    bash
    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

    bash
    uv run python yandex-scraper.py

Alternative: set the API key directly

bash
export APIFY_API_TOKEN="your_api_key_here"uv run python yandex-scraper.py

Why Use This Yandex API?

Full results-page coverage. One call returns the whole Yandex results page as structured data: organic listings, paid ads, knowledge graph entity cards, inline image panels, and inline video panels. You get the entire page, not just the organic links.

Built for Russian-speaking and CIS markets. Target 6 Yandex domains (yandex.com, yandex.ru, yandex.by, yandex.kz, yandex.uz, yandex.com.tr), 19 languages, and any of 123,000+ region IDs. That makes it practical for SEO, competitive intelligence, and brand monitoring across Russia, Eastern Europe, Central Asia, and beyond.

Predictable, pay-per-use pricing. Billing is per run plus per page processed, with no monthly rental. You pay for the searches you actually make, and you control cost directly with the page limit.

Clean, consistent JSON. Every page is a structured dataset item with the same shape, so you parse results once and reuse the code across queries, domains, and languages.

Easy to automate. Call it from Python in a few lines, or load it as an MCP tool so assistants like Claude and Cursor can run Yandex searches for you on demand.

Features

Core Capabilities

  • Keyword search across Yandex with full results-page extraction
  • A la carte result types: toggle organic results, ads, knowledge graph, inline images, and inline videos independently; each selected type is returned as its own item tagged with item_type
  • Domain localization across 6 Yandex domains
  • Language targeting with 19 supported languages
  • Region targeting with 123,000+ location IDs (the lr parameter)
  • Sort and recency filters: sort_mode (relevance or date) and period (all, day, last_two_weeks, month)
  • Safe search and typo correction controls, plus fast parallel multi-page pagination

Data Quality

  • Structured organic results with title, link, snippet, position, displayed link, date, and sitelinks
  • Rich result blocks: ads, knowledge graph, inline images, inline videos, each with a result_count
  • Per-page metadata with domain, language, location, and pagination details
  • Consistent JSON shape across every query
  • Per-page billing so larger searches stay transparent

Usage Examples

Basic Example

A single-page search for one keyword. This is the cheapest way to try the API.

json
{  "text": "machine learning",  "yandex_domain": "yandex.com",  "max_pages": 1}

Advanced Example

A Russian-domain search with Russian language, a region ID, more results per page, and two pages.

json
{  "text": "машинное обучение",  "yandex_domain": "yandex.ru",  "lang": "ru",  "lr": 225,  "groups_on_page": 20,  "family_mode": 1,  "max_pages": 2}

A la carte: collect ads and the knowledge graph

Enable just the result types you want. Here organic is off and only ads plus the knowledge graph are returned, each as its own item.

json
{  "text": "best running shoes",  "include_organic_results": false,  "include_ads": true,  "include_knowledge_graph": true,  "max_pages": 1}

Fresh results: sort by date, last two weeks

Use sort_mode and period to focus on recent content. They apply to every selected result type.

json
{  "text": "ai news",  "yandex_domain": "yandex.ru",  "lang": "ru",  "sort_mode": "date",  "period": "last_two_weeks",  "max_pages": 1}

Input Parameters

ParameterTypeRequiredDefaultDescription
textstringYes-The search query. Supports Yandex operators such as site:wikipedia.org python.
include_organic_resultsbooleanNotrueReturn organic results (item_type organic).
include_adsbooleanNofalseReturn paid ads when present (item_type ads).
include_knowledge_graphbooleanNofalseReturn the knowledge graph card when present (item_type knowledge_graph).
include_inline_imagesbooleanNofalseReturn the inline image strip (item_type inline_images).
include_inline_videosbooleanNofalseReturn the inline video carousel (item_type inline_videos).
yandex_domainstringNoyandex.comYandex domain, e.g. yandex.ru, yandex.com.tr, yandex.kz (6 supported).
langstringNoenLanguage code, e.g. ru, en, tr, de (19 supported); null for unspecified.
lrintegerNo(domain default)Region ID, e.g. 225 = Russia, 84 = United States, 149 = Belarus. 123,000+ IDs; see the Actor page for the full table.
max_pagesintegerNo2Maximum pages to fetch (0 = no limit). Applies to every selected result type.
sort_modestringNorelevanceResult ordering: relevance or date (newest first).
periodstringNoallRecency window: all, day, last_two_weeks, month.
groups_on_pageintegerNo10Results per page (1 to 20).
family_modeintegerNo1Safe search: 0 = off, 1 = moderate, 2 = strict.
fix_typobooleanNotrueAuto-correct spelling errors in the query.
output_filestringNo(none)Optional filename to save results; auto-generated if omitted.

Output Format

Each selected result type present on a page is returned as its own dataset item, tagged with item_type (organic, ads, knowledge_graph, inline_images, or inline_videos) and a result_count. A representative organic item for the query Apple is shown below; arrays and some fields are trimmed here for readability.

json
{  "item_type": "organic",  "result_count": 10,  "text": "Apple",  "yandex_domain": "yandex.com",  "lang": "en",  "lr": "84",  "page_number": 1,  "search_domain": "yandex.com",  "search_domain_description": "United States",  "search_language": "en",  "search_language_description": "English",  "search_location": "84",  "total_results_found": 10,  "pages_processed": 1,  "total_pages": 1,  "max_pages_set": 1,  "results_per_page": 10,  "pagination_limit_reached": true,  "pagination_stopped_by_limit": true,  "organic_results": [    {      "position": 1,      "title": "Apple",      "link": "https://www.apple.com/",      "displayed_link": "apple.com",      "snippet": "Apple Payments Services LLC, a subsidiary of Apple Inc., is a service provider of Goldman Sachs Bank USA for Apple Card and Savings accounts."    },    {      "position": 3,      "title": "Apple Inc. - Wikipedia",      "link": "https://en.m.wikipedia.org/wiki/Apple_Inc.",      "displayed_link": "en.m.wikipedia.org",      "snippet": "Apple Inc. is an American multinational corporation and technology company headquartered in Cupertino, California, in Silicon Valley."    }  ],  "ads_results": [],  "knowledge_graph": [    {      "title": "Apple Inc.",      "description": "American multinational technology company headquartered in Cupertino, California.",      "source": { "name": "en.wikipedia.org" }    }  ],  "inline_images": [],  "inline_videos": []}

Use as an MCP tool

You can load the Yandex API as an MCP tool so assistants call it for you. The MCP server URL preloads just this one Actor:

https://mcp.apify.com/?tools=actors,docs,johnvc/Scrape-Yandex

Authenticate with OAuth in the browser when offered, or with your Apify API token (the same APIFY_API_TOKEN used by the Python example). Get a token at https://console.apify.com/settings/integrations and a free Apify account at https://apify.com?fpr=9n7kx3 .

Install in Claude Cowork Desktop

[Install in Claude Cowork Desktop]

Cowork is the desktop app's automation mode. To give it the Yandex 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:
json
{  "mcpServers": {    "apify": {      "command": "npx",      "args": [        "-y",        "mcp-remote",        "https://mcp.apify.com/?tools=actors,docs,johnvc/Scrape-Yandex"      ]    }  }}
  1. 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.
  2. In a Cowork chat, confirm the tool is available and ask it to run the Yandex 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

[Install in Claude Code]

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

bash
claude mcp add --transport http apify \  "https://mcp.apify.com/?tools=actors,docs,johnvc/Scrape-Yandex"

To use a token instead of browser OAuth:

bash
claude mcp add --transport http apify \  "https://mcp.apify.com/?tools=actors,docs,johnvc/Scrape-Yandex" \  --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 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)

[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/Scrape-Yandex.
  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/Scrape-Yandex, using OAuth when prompted.
  5. Ask Claude to run the Yandex API.

Open Claude on the web: https://claude.ai/referral/uIlpa7nPLg

Install in Cursor

[Install in Cursor]

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

  1. In your project, create .cursor/mcp.json:
json
{  "mcpServers": {    "apify": {      "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/Scrape-Yandex"    }  }}
  1. If you prefer token auth over browser OAuth, add a header:
json
{  "mcpServers": {    "apify": {      "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/Scrape-Yandex",      "headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }    }  }}
  1. Open Cursor → Settings → MCP and confirm the apify server is connected (green dot).
  2. In Composer or Chat, ask Cursor to call the Yandex API.

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

Install in ChatGPT

[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/Scrape-Yandex
    • 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


Made with care

Use the Yandex API to power your search and SEO workflows with reliable, structured results.

🤖 Ask an AI assistant about this Actor

Open a ready-to-send prompt about the Yandex Search API in the AI of your choice:

Last Updated: 2026.10.27

来源:README.md,提交 7bf330a

工具

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版本历史

1
  1. v1.0.0最新Sep 16, 2026

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