by suthio
Brave Deep Research combines Brave Search with advanced web scraper tools to extract and traverse web content for thorou
Combines Brave Search with web scraping to extract full page content and follow links for comprehensive research. Goes beyond search snippets to provide complete webpage text at configurable depths.
Brave Deep Research is a community-built MCP server published by suthio that provides AI assistants with tools and capabilities via the Model Context Protocol. Brave Deep Research combines Brave Search with advanced web scraper tools to extract and traverse web content for thorou It is categorized under search web.
You can install Brave Deep Research in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Brave Deep Research is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Fetch and extract information from websites automatically
Example
Research competitor pricing, scrape product reviews, monitor news mentions
Automate 5-10 hours/week of manual web research
Track website changes, new content, price updates
Example
Monitor competitor blog for new posts, track stock availability, watch for pricing changes
Stay informed without manual checking, never miss important updates
Extract structured data from multiple websites
Example
Compile product listings from 10 e-commerce sites, aggregate job postings, collect real estate data
Build datasets 100x faster than manual copying
Share your MCP server with the developer community
We wired Brave Deep Research into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
Strong directory entry: Brave Deep Research surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Brave Deep Research is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.
Brave Deep Research has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, Brave Deep Research benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Brave Deep Research is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
Strong directory entry: Brave Deep Research surfaces stars and publisher context so we could sanity-check maintenance before adopting.
I recommend Brave Deep Research for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We evaluated Brave Deep Research against two servers with overlapping tools; this profile had the clearer scope statement.
Strong directory entry: Brave Deep Research surfaces stars and publisher context so we could sanity-check maintenance before adopting.
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A Model Context Protocol (MCP) server that combines Brave Search with Puppeteer-powered content extraction for deep research capabilities. This server allows AI assistants to perform comprehensive web searches by not only retrieving search results but also visiting the pages to extract full content and explore linked pages.
For a query like "climate change mitigation technologies":
Standard Brave Search MCP:
Title: "Latest Climate Change Mitigation Technologies - Example Site"
URL: "https://example.com/climate-tech"
Snippet: "Various technologies are being developed to mitigate climate change, including carbon capture..."
(Limited to just these search result snippets)
Brave Deep Research MCP:
# Latest Climate Change Mitigation Technologies - Example Site
URL: https://example.com/climate-tech
## Content
Carbon capture and storage (CCS) technology has advanced significantly in recent years. The latest direct air capture facilities can now remove CO2 at a cost of $250 per ton, down from $600 just five years ago. Implementation challenges remain, including...
[Followed by several pages of detailed content from the original page and linked pages]
# Install from npm
npm install -g @suthio/brave-deep-research-mcp
# Or clone the repository
git clone https://github.com/suthio/brave-deep-research-mcp.git
cd brave-deep-research-mcp
npm install
npm run build
Create a .env file based on the provided .env.example:
# Copy the example env file
cp .env.example .env
# Edit the file to add your Brave API key and other settings
nano .env
BRAVE_API_KEY: Your Brave Search API key (required)PUPPETEER_HEADLESS: Whether to run Puppeteer in headless mode (default: true)PAGE_TIMEOUT: Timeout for page loading in milliseconds (default: 30000)DEBUG_MODE: Enable detailed debug logging (default: false)# If installed globally via npm
brave-deep-research-mcp
# Or run directly from the package
npx @suthio/brave-deep-research-mcp
# Or run locally after cloning
npm start
To use this server with Claude for Desktop:
npm install -g @suthio/brave-deep-research-mcp
Edit the Claude for Desktop configuration file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.jsonAdd the following to the mcpServers section:
{
"mcpServers": {
"brave-deep-research": {
"command": "npx",
"args": ["@suthio/brave-deep-research-mcp"],
"env": {
"BRAVE_API_KEY": "your_brave_api_key_here",
"PUPPETEER_HEADLESS": "true"
}
}
}
}
The deep-search tool accepts the following parameters:
query (required): The search queryresults (optional): Number of search results to process (default: 3, max: 10)depth (optional): Depth of link traversal for each result (default: 1, max: 3)# Clone the repository
git clone https://github.com/suthio/brave-deep-research-mcp.git
cd brave-deep-research-mcp
# Install dependencies
npm install
# Run in development mode
npm run dev
# Build the project
npm run build
MIT
Interact with services that don't offer APIs
Example
Check form submissions, validate website functionality, test user flows
Automate interactions with any website, even without API
Prerequisites
Time Estimate
20-40 minutes including configuration and testing
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
MCP server handles HTTP requests, HTML parsing, JavaScript rendering (if headless browser), and returns structured data to Claude.
Protocols
Compatibility
✓ Use when
Use for research automation, content monitoring, data aggregation from multiple sources, and when official APIs don't exist. Best for read-only information gathering.
✗ Avoid when
Avoid for sites with APIs (use API instead), sites that explicitly forbid scraping, when data is copyrighted, or for login-required content without proper authorization.