Stop Context-Switching for Tech Stack Research

You're deep in a competitive analysis, due diligence review, or architecture research session when you need to know what technologies a website is running. Instead of breaking your flow to open another tab, authenticate with BuiltWith, and manually query their interface, just ask your AI assistant directly.

The Context-Switching Problem

Every time you need to research a website's technology stack, you're interrupting your primary workflow. Whether you're evaluating competitors, assessing potential acquisitions, or researching implementation approaches, the current process forces you to:

• Switch to BuiltWith's web interface
• Remember login credentials or API endpoints
• Manually query each domain
• Context-switch back to your analysis with the data

This MCP server eliminates that friction entirely.

Direct Integration Benefits

Seamless Research Flow: Ask "What JavaScript frameworks does stripe.com use?" directly in Claude, Cursor, or your preferred AI assistant. No tab switching, no manual API calls.

Comparative Analysis Made Simple: Request side-by-side comparisons like "Compare the hosting infrastructure of netflix.com and hulu.com" and get structured analysis without juggling multiple queries.

Natural Language Queries: Instead of remembering BuiltWith's specific API parameters, ask questions the way you naturally think about them: "Does shopify.com use any Google services?" or "What CMS is running on techcrunch.com?"

Real-World Implementation Scenarios

Competitive Intelligence: When analyzing competitor architecture, you can seamlessly blend technology discovery with strategic analysis. Ask your AI assistant to identify the tech stack and immediately follow up with architectural implications or migration considerations.

Due Diligence Workflows: During acquisition evaluations, query multiple properties rapidly: "What technologies are used across domain1.com, domain2.com, and domain3.com?" Your assistant can synthesize the data into risk assessments or integration complexity estimates.

Architecture Research: While exploring implementation options, ask "What CDN does fastly.com's customers typically use?" or "Show me the analytics stack for media companies like nytimes.com and washingtonpost.com."

Client Discovery: Before sales calls or consulting engagements, quickly research prospects: "What's the current hosting setup for potential-client.com?" and get context without obvious reconnaissance browsing.

Integration Setup

Requires a BuiltWith API key and standard MCP server configuration. Add this to your Claude Desktop or VS Code MCP settings:

{
    "mcpServers": {
        "builtwith": {
            "command": "node",
            "args": ["path/to/bw-mcp-v1.js"],
            "env": {
                "BUILTWITH_API_KEY": "your-api-key"
            }
        }
    }
}

Once configured, the integration is invisible – your AI assistant simply gains the ability to answer technology questions about any website through natural conversation.

Why This Approach Works

Rather than building another dashboard or API wrapper, this server plugs directly into your existing AI-powered workflow. You're already asking your assistant to help with analysis, research, and decision-making. Now it can access real-time technology intelligence without breaking your concentration.

The natural language interface means you can ask follow-up questions, request comparisons, and integrate findings into broader analysis sessions – all within the same conversational context where you're already working.

Repository: github.com/builtwith/mcp