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OneSearch MCP Server

MCP Server

Unified web search, scrape, and crawl via multiple engines

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Updated 17 days ago

About

The OneSearch MCP Server provides a Model Context Protocol interface for web search, scraping, crawling, and content extraction. It supports multiple search engines (Searxng, DuckDuckGo, Bing, Tavily) and scrapers like Firecrawl, enabling developers to integrate versatile web data retrieval into LLM workflows.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

OneSearch MCP Server Overview

The OneSearch MCP Server is a versatile web‑search and scraping backend that plugs directly into AI assistants via the Model Context Protocol. It bridges popular search engines—SearXNG, DuckDuckGo, Bing, Tavily—and web‑scraping services like Firecrawl, allowing an assistant to perform real‑time information retrieval without manual API integration. For developers building AI workflows, this means a single, configurable endpoint that can query multiple search engines, scrape content from arbitrary URLs, or even crawl entire sites—all while staying within the MCP ecosystem.

At its core, the server exposes three key tools: , , and .

  • lets the assistant query any of the supported engines or a local browser search. Developers can switch providers by setting environment variables, and for self‑hosted options like SearXNG or Firecrawl the server can be pointed to local instances, eliminating external dependencies.
  • leverages Firecrawl’s powerful crawler or a lightweight puppeteer‑core scraper to pull structured content from webpages. This is invaluable for pulling up-to-date data, product details, or news articles that the assistant can then summarize or analyze.
  • provides a simple interface for mapping URLs to content, useful in exploratory tasks or when building knowledge graphs.

The server’s flexibility shines in real‑world scenarios: a developer can let an AI assistant search the web for the latest market trends, scrape competitor product pages, and then generate a comparative report—all in one conversation. It also supports local browser search, enabling the assistant to query installed browsers (Chrome, Chromium) without any API keys—perfect for private or internal data that cannot be exposed externally.

Integration is straightforward. Once the MCP server is running, any AI client that supports MCP can invoke the tools via their built‑in prompt templates. Because the server handles provider selection, rate limiting, and error handling internally, developers can focus on higher‑level logic rather than plumbing. The ability to self‑host SearXNG or Firecrawl adds another layer of control: sensitive data never leaves the network, and costs are reduced by avoiding third‑party API calls.

In summary, OneSearch MCP Server offers a unified, extensible interface for web search and scraping that is both developer‑friendly and privacy‑conscious. Its plug‑and‑play nature, support for multiple engines, and seamless MCP integration make it a standout choice for any AI application that needs real‑time, reliable access to the internet.