Web Search and Research MCP

This MCP provides comprehensive web browsing, search, and research capabilities for AI agents, including PDF extraction, YouTube transcripts, summarization, and semantic search.

Overview

This MCP implements a full suite of tools for AI agents to interact with the web:

• Google search integration
• Web page content extraction
• Link extraction from pages
• PDF text extraction
• YouTube video transcript retrieval
• Text summarization
• Text embedding and semantic search
• Automated research workflows

Features

• Search: Perform Google searches and get structured results
• Page Extraction: Extract clean text content from web pages
• Link Extraction: Get all links from a webpage
• PDF Processing: Extract text from PDF documents
• YouTube Transcripts: Retrieve transcripts from YouTube videos
• Summarization: Generate concise summaries of text content
• Embeddings: Store and search text using semantic embeddings
• Research: Automated multi-step research workflows

Tools

• search - Google search with results
• open_page - Extract text from web pages
• extract_links - Get links from pages
• extract_pdf - Extract text from PDFs
• youtube_transcript - Get YouTube video transcripts
• summarize - Summarize text content
• embed - Store text embeddings
• semantic_search - Search stored embeddings
• research - Conduct automated research

Installation

npm install

Usage

Run the MCP server:

node index.js <tool_name> <json_input>

Example:

node index.js search '{"query":"artificial intelligence"}'

Dependencies

• axios: HTTP requests
• cheerio: HTML parsing
• natural: Text processing
• pdf-parse: PDF text extraction
• youtube-transcript: YouTube transcript API