Plug-and-play Model Context Protocol (MCP) server that exposes Product Huntโs public API as easy-to-call MCP tools.
https://github.com/jaipandya/producthunt-mcp-serverYou're already using Claude Desktop or Cursor for development work. Now imagine asking your AI assistant "What are the top AI launches from Product Hunt this week?" and getting structured data back instantly - no browser tabs, no manual API calls, no context switching.
Every time you need Product Hunt data - whether you're researching competitors, analyzing launch trends, or hunting for inspiration - you're stuck with manual browsing, copy-pasting launch details, and losing context when you switch between tools. Your AI assistant sits there useless while you manually gather data that should flow directly into your workflow.
This MCP server fixes that disconnect.
Connect Product Hunt's entire API to Claude Desktop or Cursor in under 5 minutes. Your AI assistant can now pull launch data, analyze trends, fetch user profiles, and dig into comments - all without you leaving your conversation.
Key capabilities your AI gains:
Competitive Research: "Show me all the productivity tools launched on Product Hunt in the last month with over 100 votes" - instant structured data instead of endless scrolling.
Content Creation: "Get the details on today's #1 Product Hunt launch including maker quotes and top comments" - perfect for social posts, blog content, or newsletters.
Market Analysis: "Compare the launch performance of these 5 AI coding tools" - your assistant pulls the data and creates the analysis in one go.
Due Diligence: "Get the complete launch history and community engagement for this startup" - comprehensive founder and product research without tab juggling.
pip install product-hunt-mcp
Add 4 lines to your Claude Desktop config:
{
"mcpServers": {
"product-hunt": {
"command": "product-hunt-mcp",
"env": {
"PRODUCT_HUNT_TOKEN": "your_token_here"
}
}
}
}
Restart Claude Desktop. That's it.
Your AI assistant now has full Product Hunt API access with 11 different tools - from basic post lookups to complex filtered searches across the entire platform.
This isn't about replacing Product Hunt's interface. It's about eliminating the context switch when Product Hunt data needs to inform your AI-assisted work. Whether you're analyzing markets, researching competitors, or creating content, the data flows directly into your existing AI conversations.
Built on FastMCP for reliable performance and proper error handling. Respects API rate limits. Works with Docker if that's your deployment preference.
Get it running: pip install product-hunt-mcp
The next time you need Product Hunt insights, you'll ask your AI assistant instead of opening another browser tab.