Deep Search MCP Server

Deep Search MCP Server

Provides comprehensive search capabilities including web search, content extraction, news search, academic search, and AI-powered multi-source research. Enables natural language access to web content and research through a production-ready MCP server.

Category
Visit Server

README

Deep Search MCP Server

A production-ready Model Context Protocol (MCP) server providing comprehensive deep search capabilities including web search, content extraction, and AI-powered research.

Deploy with Vercel

Features

  • Web Search - Search the web for any topic with comprehensive results
  • Content Extraction - Extract clean, readable content from any URL
  • Deep Research - Multi-source research with summaries and key findings
  • News Search - Find recent news articles on any topic
  • Academic Search - Discover academic papers and research content

Quick Start

Connect to Your AI Assistant

Add this configuration to your MCP client (e.g., Cursor, Claude Desktop):

{
  "mcpServers": {
    "deep-search": {
      "url": "https://deep-search-mcp.vercel.app/api/mcp"
    }
  }
}

For Cursor

Add to .cursor/mcp.json:

{
  "mcpServers": {
    "deep-search": {
      "url": "https://deep-search-mcp.vercel.app/api/mcp"
    }
  }
}

Available Tools

Tool Description Parameters
web_search Search the web for information query (required), maxResults (optional, 1-20)
extract_content Extract content from a URL url (required)
deep_research Comprehensive multi-source research query (required), depth (optional, 1-5)
news_search Search for news articles query (required), maxResults (optional, 1-20)
academic_search Search academic/research content query (required), maxResults (optional, 1-20)

Self-Hosting

Prerequisites

  • Node.js 20+
  • npm, yarn, or pnpm

Installation

# Clone the repository
git clone https://github.com/LikhonSheikh404/deep-search-mcp.git
cd deep-search-mcp

# Install dependencies
npm install

# Copy environment file
cp .env.example .env

# Start development server
npm run dev

Deploy to Vercel

  1. Fork this repository
  2. Import to Vercel
  3. Deploy!

Or use the CLI:

# Install Vercel CLI
npm i -g vercel

# Deploy
vercel

Testing with MCP Inspector

npx @modelcontextprotocol/inspector@latest http://localhost:3000

Then open http://127.0.0.1:6274 to test your tools.

API Endpoints

Endpoint Description
GET/POST /api/mcp MCP server endpoint
GET /.well-known/oauth-protected-resource OAuth metadata (for authenticated setups)

Technology Stack

  • Framework: Next.js 15 (App Router)
  • Language: TypeScript
  • MCP SDK: mcp-handler
  • Deployment: Vercel (Serverless + Fluid Compute)
  • Transport: Streamable HTTP (efficient, no persistent connections)

Architecture

src/
├── app/
│   ├── api/
│   │   └── [transport]/
│   │       └── route.ts      # MCP server endpoint
│   ├── .well-known/
│   │   └── oauth-protected-resource/
│   │       └── route.ts      # OAuth metadata
│   ├── page.tsx              # Landing page
│   └── layout.tsx            # Root layout
├── lib/
│   └── search-engine.ts      # Search functionality
└── types/
    └── mcp.ts                # Type definitions

Environment Variables

Variable Description Required
NEXT_PUBLIC_APP_URL Public URL of your deployment No

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - feel free to use this in your own projects.

Author

Built by Matrix Agent


Resources:

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured