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MCP Omnisearch

@spences10

代码仓库

基本信息

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许可证

MIT

传输方式

stdio

作者

spences10

关于 MCP Omnisearch

🔍 A Model Context Protocol (MCP) server providing unified access to multiple search engines (Tavily, Brave, Kagi, Exa), AI tools (Kagi FastGPT, Exa, Linkup), and content extraction services (Firecrawl, Tavily, Kagi). Includes GitHub search. All through a single interface.

#search#mcp#brave#kagi#perplexity-ai#tavily#model-context-protocol

MCP Omnisearch 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块，请前往代码仓库查看安装说明。

代码仓库

MCP Omnisearch 工具

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工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is mcp-omnisearch?

mcp-omnisearch is a Model Context Protocol (MCP) server that unifies access to seven providers (Tavily, Brave, Kagi, Exa AI, GitHub, Linkup, and Firecrawl) through four consolidated tools. It is designed for developers using MCP clients who want a single interface for web search, AI answers, GitHub search, and web extraction from multiple backends.

How to use mcp-omnisearch?

Install dependencies with pnpm install, build the project with pnpm run build, and run the server with node ./dist/index.js. Configure the server in your MCP client by setting environment variables for the API keys you have (e.g., TAVILY_API_KEY, BRAVE_API_KEY). Providers without keys are automatically skipped; all others continue to work.

Key features of mcp-omnisearch

  • Four tools: web_search, ai_search, github_search, web_extract
  • Supports Tavily, Brave, Kagi, Exa AI, GitHub, Linkup, and Firecrawl
  • Providers with missing API keys are gracefully skipped
  • Web extraction supports crawling, scraping, summarizing, and similarity search
  • AI search provides sourced answers via Kagi FastGPT, Exa Answer, or Linkup
  • Configurable large‑result mode (file vs inline) via environment variable

Use cases of mcp-omnisearch

  • Search the web using multiple search engines from a single MCP server
  • Get AI‑generated, sourced answers for complex questions
  • Search GitHub code, repositories, or users programmatically
  • Extract, crawl, scrape, or summarize web content from a URL

常见问题

1

What providers does mcp-omnisearch support?

It supports Tavily, Brave, Kagi, Exa AI, GitHub, Linkup, and Firecrawl. You can use any subset by providing the corresponding API keys.

2

How do I configure API keys?

Set environment variables in your MCP client configuration. Keys accepted: `TAVILY_API_KEY`, `KAGI_API_KEY`, `BRAVE_API_KEY`, `GITHUB_API_KEY`, `EXA_API_KEY`, `LINKUP_API_KEY`, `FIRECRAWL_API_KEY`. Optionally, `FIRECRAWL_BASE_URL` for a self‑hosted Firecrawl instance.

3

What tools are available?

The server exposes four tools: `web_search` (web search with Tavily, Brave, Kagi, Exa, or Kagi Enrichment), `ai_search` (sourced AI answers), `github_search` (GitHub code, repos, users), and `web_extract` (extract, crawl, scrape, summarize, or find similar content).

4

How are large results handled?

By default, large results are saved to a file and a file reference is returned. You can change this to inline mode by setting the `OMNISEARCH_LARGE_RESULT_MODE` environment variable to `inline`.

5

What are the runtime requirements?

The server runs on Node.js and is invoked via a MCP client using standard I/O (stdio). It does not require a separate HTTP server.

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