SEO & Web Analysis MCP Server
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Lighthouse audits, PageSpeed analysis, SSL checks, tech stack detection, WHOIS and DNS queries
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🔍 SEO & Web Analysis MCP Server by NexGenData
Connect AI agents to website and domain analysis data through the Model Context Protocol (MCP). This server exposes a focused set of web-intelligence tools that LLM-powered applications like Claude, ChatGPT, Cursor, and Cline can call directly, returning clean JSON.
This MCP server exposes web and domain analysis tools that any MCP-compatible AI client can call. Instead of building API integrations or scraping code, your agent can crawl a website, detect its tech stack, and inspect its DNS, SSL, and WHOIS records through tool calls. The server handles extraction, rate limiting, and response formatting.
- crawl_website— crawl a website and return page content / structure
- detect_tech_stack— identify technologies used by a site
- check_dns— look up DNS records for a domain
- check_ssl— inspect a domain's SSL/TLS certificate
- lookup_whois— retrieve WHOIS registration data for a domain
Each tool accepts structured parameters and returns JSON that AI agents can parse and chain together for multi-step workflows.
- AI developers building agents that need website and domain analysis
- Automation platforms connecting AI agents to structured web data
- Research and ops teams using AI assistants for site and domain checks
This actor runs in standby mode and exposes an MCP endpoint. Configure your MCP client (Claude Desktop, Cursor, Cline, or a custom agent) with the server endpoint URL and your Apify API token. The server auto-discovers the available tools.
Is this compatible with Claude Desktop?Yes. Any MCP-compatible client can connect, including Claude Desktop, Cursor, Cline, and custom LLM agents.
Do I need separate API keys?No. You only need your Apify API token to connect.
Can I use this in production?Yes. The server runs on Apify's scalable infrastructure with built-in monitoring, logging, and error handling.
Browse the full NexGenData catalog at](https://docs.apify.com/llms-full.txt)https://apify.com/nexgendata
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '<YOUR_API_TOKEN>' with your token const client = new ApifyClient({ token: '<YOUR_API_TOKEN>', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/seo-web-analysis-mcp-server").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '<YOUR_API_TOKEN>' with your token. client = ApifyClient("<YOUR_API_TOKEN>") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("nexgendata/seo-web-analysis-mcp-server").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}") for item in client.dataset(run.default_dataset_id).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
echo '{}' | apify call nexgendata/seo-web-analysis-mcp-server --silent --output-dataset
{ "mcpServers": { "apify": { "type": "http", "url": "https://mcp.apify.com/?tools=fetch-actor-details,nexgendata/seo-web-analysis-mcp-server" } } }
The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send anAuthorization: Bearer <APIFY_API_TOKEN>header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).
Download the OpenAPI definition:https://api.apify.com/v2/actors/iS91cqk3mFTWub23X/builds/J6bA3sUnkjmmU14PH/openapi.json
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