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domain-search-mcp

by dorukardahan·20·Score 42

A zero-config domain search MCP server with multi-TLD checks, bulk search, premium detection, AI-powered suggestions, and registrar pricing comparison.

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Overview

Domain Search MCP is a comprehensive domain management tool that works through Model Context Protocol. It provides fast, local-first domain availability checks using a fallback chain of RDAP → GoDaddy → WHOIS, with optional pricing integration. The server supports both stdio transport for Claude Desktop and other MCP clients, plus HTTP/SSE transport for ChatGPT Actions and web applications. Features include bulk checking up to 100 domains, AI-powered domain suggestions using a fine-tuned Qwen model, premium/auction detection, and social handle availability checks.

Try asking AI

After installing, here are 8 things you can ask your AI assistant:

you:Developers checking domain availability for new projects
you:Domain investors researching valuable domains with premium detection
you:Branding teams using AI to generate domain name suggestions
you:Businesses comparing registrar pricing before purchasing domains
you:DevOps teams integrating domain checks into CI/CD workflows
you:Does this require API keys to use?
you:Which AI model is used for domain suggestions?
you:Can this be integrated with ChatGPT?

When to choose this

Choose this server when you need to check domain availability without API keys or want AI-powered domain suggestions integrated into your workflow.

When NOT to choose this

Don't choose this if you need real-time pricing without setting up a custom backend, or if you require domain registration functionality directly from the tool.

Tools this server exposes

11 tools extracted from the README
  • search_domain

    Check a domain name across multiple TLDs with premium/auction detection.

  • bulk_search

    Check availability of up to 100 domain names for a single TLD.

  • compare_registrars

    Compare pricing for a domain across different registrars.

  • suggest_domains

    Generate domain name variations with prefixes, suffixes, and hyphens.

  • suggest_domains_smart

    AI-powered generation of brandable domain names using fine-tuned model.

  • analyze_project

    Analyze local project or GitHub repo to suggest matching domain names.

  • hunt_domains

    Find valuable domains for investment by scanning auctions and generating patterns.

  • expiring_domains

    Monitor domains approaching expiration (requires federated negative cache).

  • tld_info

    Get TLD metadata and restrictions.

  • check_socials

    Check username availability across social media platforms.

  • ai_health

    Check status of AI inference services and circuit breakers.

Comparable tools

whois-mcpdomain-searchregistrar-api

Installation

Installation

Using npx (Recommended)

npx -y domain-search-mcp@latest

From Source

git clone https://github.com/dorukardahan/domain-search-mcp.git
cd domain-search-mcp
npm install
npm run build
npm start

Claude Desktop Configuration

Add to claude_desktop_config.json:

{
  "mcpServers": {
    "domain-search": {
      "command": "npx",
      "args": ["-y", "domain-search-mcp@latest"]
    }
  }
}

Claude Code Configuration

Add .mcp.json in your project root:

{
  "mcpServers": {
    "domain-search": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "domain-search-mcp@latest"]
    }
  }
}

FAQ

Does this require API keys to use?
No, basic availability checking works with zero configuration using public RDAP/WHOIS data. Only pricing comparison requires optional API keys from registrars.
Which AI model is used for domain suggestions?
The server uses a fine-tuned Qwen 7B-DPO model for AI-powered domain suggestions, which works out of the box without requiring API keys.
Can this be integrated with ChatGPT?
Yes, the server supports HTTP/SSE transport for ChatGPT Actions. You can start the HTTP server and import the OpenAPI specification to create a Custom GPT.

On Hacker News

Recent discussion from the developer community.

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Last updated · Auto-generated from public README + GitHub signals.