Introduction

producthunt-mcp-research is a powerful MCP-based search platform for Product Hunt data with AI-powered natural language queries. Built with TypeScript and following modern software architecture principles, it provides a robust foundation for semantic search and data exploration through AI assistants.

What is producthunt-mcp-research?

producthunt-mcp-research is a monorepo-based application that consists of several specialized modules:

graph TB
    subgraph "AI Integration"
        M[MCP Server
mcp-server-qdrant]
        AI[AI Assistant]
    end

    subgraph "Storage Layer"
        L[Qdrant
Local Vector DB]
    end

    subgraph "Core Modules"
        F[Fetcher
Product Hunt API]
        R[Repository
Embedding + Qdrant]
        O[Orchestrator
CLI + Coordination]
        S[Shared
Types + Utils]
    end

    subgraph "Data Sources"
        PH[Product Hunt API
GraphQL]
    end

    %% Core Modules <--> Storage Layer/AI Integration
    F -.->|depends on| S
    R -.->|depends on| S
    O -.->|depends on| S
    O -.->|uses| F
    O -.->|uses| R
    R -.->|connects to| L
    M -.->|queries| L
    F -.->|fetches from| PH
    M -.->|serves| AI

    %% PHをグラフの一番下に寄せるための不可視リンク
    S ~~~ PH

• Fetcher: Handles data retrieval from Product Hunt API using GraphQL
• Repository: Manages data persistence with Qdrant and generates embeddings using Transformers.js
• Orchestrator: Provides CLI interface and coordinates the data ingestion workflow
• Shared: Contains common utilities, types, and logging used across modules

Key Benefits

Local-First Design

Designed for local personal use only, enabling you to set up a powerful analysis and search platform for free on your environment with Qdrant’s efficient vector search capabilities.

AI-Powered Search

Integrates with MCP (Model Context Protocol) to enable natural language queries through AI assistants, making data exploration accessible to everyone.

Use Cases

producthunt-mcp-research is perfect for:

• Business Opportunity Discovery: Using AI-powered search to identify emerging trends and market needs
• Product Research: Gathering insights about product launches and user engagement through natural language queries
• Competitive Intelligence: Monitoring competitor products and their performance with semantic search
• Market Analysis: Understanding user pain points and willingness-to-pay signals through comment analysis

Important Note

This tool is designed for local personal use only. Product Hunt’s API terms of service prohibit commercial use, and this repository is provided as open source software for individual analysis and research purposes.

Next Steps

Ready to get started? Check out our Installation Guide to set up producthunt-mcp-research in your environment.