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Documentation Index

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SearchAPI is a lightweight, self-hostable REST API that wraps DuckDuckGo’s meta-search engine (DDGS) and the Crossref academic index to deliver structured search results over HTTP. It was built to solve a specific problem: collecting large volumes of relevant URLs across different content types (web pages, PDFs, research papers, books, news articles, GitHub repositories) for building LLM fine-tuning datasets — without hitting paywalls or rate limits from proprietary search APIs.

Quickstart

Make your first API call in under 5 minutes

API Reference

Browse all endpoints with parameters and examples

MCP Server

Connect SearchAPI to Claude, Cursor, and other AI assistants

Dataset Generation

Strategies for building LLM training datasets

What SearchAPI provides

SearchAPI exposes a set of focused endpoints, each targeting a different content type. All endpoints return arrays of URLs (or DOIs for papers) as JSON, making them easy to integrate into data pipelines, scripts, or AI agent workflows.

Web search

General-purpose meta-search across multiple engines

Engine-specific search

Target Bing, Google, DuckDuckGo, Brave, Yandex, and more

Research papers

Academic paper search via Crossref, returns DOIs

Books

Book search returning direct URLs

News

Current news articles by topic

PDFs & filetypes

Search for PDFs, DOCX, PPTX, and any filetype

Repositories

Find GitHub and GitLab repositories

Wikipedia & Wikimedia

Aggregated results from Wikipedia and related Wikimedia sites

Key characteristics

  • No API key required — SearchAPI uses DuckDuckGo’s DDGS library under the hood. No account, no billing, no quota management on your end.
  • MCP server built in — The same endpoints are also available as MCP tools, letting AI assistants like Claude call them directly.
  • Docker and Podman ready — A single podman-compose up -d starts the service. A prebuilt Docker image is available on Docker Hub.
  • One-click Render deploy — The included render.yaml configures automatic deployment on Render’s free tier.
  • CORS open by default — All origins, methods, and headers are permitted out of the box, so you can call the API from any frontend or script.

Getting started

1

Deploy or run locally

Pull and start the container, or clone the repo and run with uv fastapi run. See the deployment guide for all options.
2

Make your first search call

Call GET /search/?query=machine+learning&limit=10 to get a list of URLs. See the quickstart for a full walkthrough.
3

Automate your data collection

Use the endpoint that matches your content type — papers, PDFs, news, books, or repositories — and pipe the results into your dataset pipeline.
4

Optionally connect to an AI assistant

Mount the MCP server and give Claude or Cursor direct access to all search tools. See the MCP server guide.
SearchAPI is intended for educational and research use. You are responsible for complying with the terms of service of any upstream search engine and applicable laws in your jurisdiction.

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