About mcp-omnisearch
mcp-omnisearch is an MCP server that exposes Tavily, Brave, Kagi, Exa, GitHub, Linkup and Firecrawl through four consolidated tools. It suits users who want several search and extraction services behind one interface. It is licensed under MIT.
Key features
- 01Unified web_search tool across several providers
- 02Sourced AI answers via ai_search
- 03GitHub code, repository and user search
- 04Web extraction, crawling and scraping
- 05Providers without keys are skipped
Use cases
- 01Letting an MCP client query several search engines
- 02Getting AI answers with cited sources
- 03Extracting article text or crawling websites
MCP support
This project is an MCP server that exposes four tools, web_search, ai_search, github_search and web_extract, to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEmcp-omnisearch
A Model Context Protocol (MCP) server that provides unified access to Tavily, Brave, Kagi, Exa AI, GitHub, Linkup, and Firecrawl through four consolidated tools.
Quick start
Install the published server with MCPick:
npx mcpick add \
--name mcp-omnisearch \
--command npx \
--args=-y,mcp-omnisearch
MCPick defaults to Claude Code. Use --client and --scope to target
another client or add the server to the current repository:
npx mcpick add \
--name mcp-omnisearch \
--command npx \
--args=-y,mcp-omnisearch \
--client vscode \
--scope project
See Deployment for supported clients and provider credential storage options.
To run from source instead:
pnpm install
pnpm run build
node ./dist/index.js
Providers without keys are skipped and the rest keep working. If your client supports environment-variable expansion, reference keys instead of storing their values in the MCP configuration:
{
"mcpServers": {
"mcp-omnisearch": {
"command": "npx",
"args": ["-y", "mcp-omnisearch"],
"env": {
"TAVILY_API_KEY": "${TAVILY_API_KEY}",
"EXA_API_KEY": "${EXA_API_KEY}"
}
}
}
}
Add only the provider keys you use. Expansion syntax and secret storage are client-specific; see Deployment for secure options and plaintext fallback guidance.
Tools
web_search
Search the web with Tavily, Brave, Kagi, or Exa.
{
"query": "latest SvelteKit releases",
"provider": "tavily",
"limit": 10,
"search_depth": "advanced",
"topic": "news",
"time_range": "month",
"safe_search": true,
"include_raw_content": false,
"auto_parameters": false
}
Search controls apply when supported by the selected provider.
ai_search
Get sourced AI answers with Exa Answer, Linkup, or Tavily Research.
Tavily Research returns a task ID first; pass it back as research_id
to retrieve the report.
{
"query": "Explain the differences between REST and GraphQL",
"provider": "exa_answer"
}
github_search
Search GitHub code, repositories, or users.
{
"query": "filename:remote.ts @sveltejs/kit",
"search_type": "code",
"limit": 5
}
web_extract
Extract, crawl, scrape, or find similar content with Tavily, Firecrawl, or Exa.
{
"url": "https://example.com/long-article",
"provider": "tavily",
"mode": "extract",
"extract_depth": "advanced",
"query": "installation requirements",
"chunks_per_source": 3,
"format": "markdown"
}
Documentation
- Provider selection — choose providers by task, key, mode, and capability.
- Search operators — operator support matrix and tested examples.
- Large results — inline vs file response behavior and remote deployment caveats.
- Deployment — MCP client, WSL, and Firecrawl setup.
- Troubleshooting — keys, access, validation, rate limits, and common failures.
Environment variables
TAVILY_API_KEYKAGI_API_KEYBRAVE_API_KEYGITHUB_API_KEYEXA_API_KEYLINKUP_API_KEYFIRECRAWL_API_KEYFIRECRAWL_BASE_URLoptional, for self-hosted FirecrawlOMNISEARCH_LARGE_RESULT_MODEoptional,filedefault orinline
Development
pnpm install
pnpm run build
pnpm test
Please read CONTRIBUTING.md before opening a PR.
License
MIT License - see LICENSE.
Acknowledgments
Built on Model Context Protocol, Tavily, Kagi, Brave Search, Exa AI, Linkup, and Firecrawl.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.