Duckduckgo

io.github.johnisanerdPublished by GitHub account johnisanerdv1.1.0Updated Nov 7, 2026

DuckDuckGo web search results, news and related searches. Paid, on Apify's hosted MCP.

VerifiedStreamable HTTPWeb executableWeb Search & ScrapingData & Analytics

Overview

Duckduckgo's hosted MCP server (mcp.apify.com); OAuth sign-in required; Streamable HTTP.

No AI overview yet: these facts come from the registry entry and the server itself.

Endpoint
mcp.apify.com
Last checked

Installation

In SourceWeft

  1. Open Duckduckgo in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.johnisanerd%2Fduckduckgo/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "mcpServers": {
    "duckduckgo": {
      "type": "http",
      "url": "https://mcp.apify.com/?tools=johnvc/DuckDuckGo-Scraper-for-serp-rankings"
    }
  }
}

README

🦆 DuckDuckGo API: Structured DuckDuckGo Search Results in Clean JSON

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

Actor page: apify.com/johnvc/DuckDuckGo-Scraper-for-serp-rankings Input schema: apify.com/johnvc/DuckDuckGo-Scraper-for-serp-rankings/input-schema

The DuckDuckGo API runs a DuckDuckGo search for any query and returns clean, structured JSON. Each page of results comes back as one item with organic listings (title, link, snippet, position, sitelinks), ads, knowledge graph panels, news results, inline images, inline videos, and related searches, plus per-page metadata. It supports 40+ region and language combinations, safe-search levels, date filtering, and automatic pagination. Because DuckDuckGo does not personalize results, the output is consistent across runs.

Video Walkthrough

[Watch the walkthrough]

Quick Start

Prerequisites

  1. Clone the repository

    bash
    git clone https://github.com/johnisanerd/Apify-DuckDuckGo-Search-Scraper.gitcd Apify-DuckDuckGo-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 duckduckgo-search-scraper.py

Alternative: set the API key directly

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

Why Use This DuckDuckGo API?

Full results-page coverage. One call returns the whole DuckDuckGo results page as structured data: organic listings, ads, knowledge graph panels, news, inline images, inline videos, and related searches. You get the entire page, not just the organic links.

Consistent, non-personalized snapshots. DuckDuckGo does not personalize results, so repeated runs return comparable SERPs, which is ideal for ranking analysis and monitoring over time.

Localized and filterable. Target 40+ region and language combinations, set the safe-search level, and filter by date (past day, week, month, year, or a custom range).

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

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 DuckDuckGo searches for you on demand.

Features

Core Capabilities

  • Keyword search across DuckDuckGo with full results-page extraction
  • Localization across 40+ region and language combinations
  • Safe-search control (strict, moderate, or off)
  • Date filtering with relative periods or a custom date range
  • Multi-page pagination with a configurable page cap

Data Quality

  • Structured organic results with title, link, snippet, position, displayed link, date, and sitelinks
  • Rich result blocks: ads, knowledge graph, news, inline images, inline videos, related searches
  • Per-page metadata with result counts 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
{  "query": "machine learning",  "max_pages": 1}

Advanced Example

A UK-localized search with strict safe-search, results from the past week, and two pages.

json
{  "query": "machine learning",  "localization": "uk-en",  "safe": "strict",  "date_filter": "w",  "max_pages": 2}

Input Parameters

ParameterTypeRequiredDefaultDescription
querystringYes-The search query.
localizationstringNous-enRegion and language code, e.g. uk-en, fr-fr, de-de, ja-jp (40+ supported).
safestringNomoderateSafe-search level: strict, moderate, or off.
date_filterstringNo(none)d (past day), w (week), m (month), y (year), or a custom range YYYY-MM-DD..YYYY-MM-DD.
max_pagesintegerNo2Maximum pages to fetch (0 = no limit).
output_filestringNo(none)Optional filename to save results; auto-generated if omitted.

Output Format

A real dataset item for the query machine learning. Each page of results is one item; the first result's sitelinks are trimmed here for readability.

json
{  "query": "machine learning",  "localization": "us-en",  "safe_search": -1,  "max_pages": 1,  "search_timestamp": "2026-05-29T09:56:11.848097",  "total_results_found": 11,  "pages_processed": 1,  "page_number": 1,  "search_metadata": {    "localization": "us-en",    "localization_name": "United States (English)",    "safe_search": -1,    "safe_search_description": "Moderate",    "max_pages": 1,    "pagination_limit_reached": true  },  "pagination_info": {    "total_pages": 1,    "max_pages_set": 1,    "pagination_stopped_by_limit": true,    "results_per_page": { "first_page": 11, "subsequent_pages": 50 }  },  "organic_results": [    {      "position": 1,      "title": "Machine Learning Tutorial - GeeksforGeeks",      "link": "https://www.geeksforgeeks.org/machine-learning/machine-learning/",      "date": "Apr 15, 2026",      "snippet": "Machine learning is a branch of Artificial Intelligence that focuses on developing models and algorithms that let computers learn from data without being explicitly programmed for every task.",      "favicon": "https://external-content.duckduckgo.com/ip3/www.geeksforgeeks.org.ico",      "sitelinks": [        {          "title": "Gradient Descent in Linear Regression",          "link": "https://www.geeksforgeeks.org/machine-learning/gradient-descent-in-linear-regression/"        }      ]    },    {      "position": 2,      "title": "Machine learning - Wikipedia",      "link": "https://en.wikipedia.org/wiki/Machine_learning",      "snippet": "Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data.",      "favicon": "https://external-content.duckduckgo.com/ip3/en.wikipedia.org.ico"    }  ],  "ads": [],  "knowledge_graph": [],  "news_results": [],  "inline_images": [],  "inline_videos": [],  "related_searches": []}

Use as an MCP tool

You can load the DuckDuckGo 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/DuckDuckGo-Scraper-for-serp-rankings

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 DuckDuckGo 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/DuckDuckGo-Scraper-for-serp-rankings"      ]    }  }}
  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 DuckDuckGo 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/DuckDuckGo-Scraper-for-serp-rankings"

To use a token instead of browser OAuth:

bash
claude mcp add --transport http apify \  "https://mcp.apify.com/?tools=actors,docs,johnvc/DuckDuckGo-Scraper-for-serp-rankings" \  --header "Authorization: Bearer YOUR_APIFY_TOKEN"

Then verify with claude mcp list, or run /mcp inside a session. Ask Claude Code to call the DuckDuckGo 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/DuckDuckGo-Scraper-for-serp-rankings.
  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/DuckDuckGo-Scraper-for-serp-rankings, using OAuth when prompted.
  5. Ask Claude to run the DuckDuckGo 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/DuckDuckGo-Scraper-for-serp-rankings"    }  }}
  1. If you prefer token auth over browser OAuth, add a header:
json
{  "mcpServers": {    "apify": {      "url": "https://mcp.apify.com/?tools=actors,docs,johnvc/DuckDuckGo-Scraper-for-serp-rankings",      "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 DuckDuckGo 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/DuckDuckGo-Scraper-for-serp-rankings
    • 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 DuckDuckGo 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 DuckDuckGo Scraper in the AI of your choice:

Last Updated: 2026.10.27

Source: README.md at commit b1561c7

Tools

0
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Version history

1
  1. v1.0.0Nov 3, 2026

Score

75% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.