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Producthunt Mcp Server
What is Producthunt Mcp Server
Product Hunt MCP Server is a plug-and-play server that connects Product Hunt’s API to any LLM or agent using the Model Context Protocol (MCP). It is designed for AI assistants, chatbots, and automation tools.
Use cases
Use cases include integrating Product Hunt data into AI assistants, building bots for data retrieval and analysis, creating dashboards for monitoring trends, and developing custom automation tools.
How to use
To use the Product Hunt MCP Server, install it via pip with ‘pip install product-hunt-mcp’. Set the PRODUCT_HUNT_TOKEN environment variable with your API token and run the server using ‘product-hunt-mcp’.
Key features
Key features include retrieving detailed information on posts, comments, collections, topics, and users, as well as searching and filtering by various criteria. It supports paginated comments and user upvotes and is built with FastMCP for speed and compatibility.
Where to use
Product Hunt MCP Server can be used in various fields including AI development, chatbot creation, and automation of tasks that require access to Product Hunt’s data.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Producthunt Mcp Server
Product Hunt MCP Server is a plug-and-play server that connects Product Hunt’s API to any LLM or agent using the Model Context Protocol (MCP). It is designed for AI assistants, chatbots, and automation tools.
Use cases
Use cases include integrating Product Hunt data into AI assistants, building bots for data retrieval and analysis, creating dashboards for monitoring trends, and developing custom automation tools.
How to use
To use the Product Hunt MCP Server, install it via pip with ‘pip install product-hunt-mcp’. Set the PRODUCT_HUNT_TOKEN environment variable with your API token and run the server using ‘product-hunt-mcp’.
Key features
Key features include retrieving detailed information on posts, comments, collections, topics, and users, as well as searching and filtering by various criteria. It supports paginated comments and user upvotes and is built with FastMCP for speed and compatibility.
Where to use
Product Hunt MCP Server can be used in various fields including AI development, chatbot creation, and automation of tasks that require access to Product Hunt’s data.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
🚀 Product Hunt MCP Server
A plug-and-play MCP server for Product Hunt
📦 Quick Install
pip install product-hunt-mcp
🏃♂️ Quick Start Example
# Run the MCP server (requires PRODUCT_HUNT_TOKEN environment variable)
export PRODUCT_HUNT_TOKEN=your_token_here
product-hunt-mcp
✨ What is this?
Product Hunt MCP Server connects Product Hunt’s API to any LLM or agent that speaks the Model Context Protocol (MCP). Perfect for AI assistants, chatbots, or your own automations!
- 🔍 Get posts, collections, topics, users
- 🗳️ Get votes, comments, and more
- 🛠️ Use with Claude Desktop, Cursor, or any MCP client
🛠️ Features
- Get detailed info on posts, comments, collections, topics, users
- Search/filter by topic, date, votes, etc.
- Paginated comments, user upvotes, and more
- Built with FastMCP for speed and compatibility
🧑💻 Who is this for?
- AI/LLM users: Plug into Claude Desktop, Cursor, or your own agent
- Developers: Build bots, dashboards, or automations with Product Hunt data
- Tinkerers: Explore the MCP ecosystem and build your own tools
🏁 Setup
Prerequisites
- Python 3.10+
- Product Hunt API token (get one here)
- You’ll need to create an account on Product Hunt
- Navigate to the API Dashboard and create a new application
- Use the
Developer Tokenfor the token
Note: When creating a new application on Product Hunt, you will be asked for a
redirect_uri. While the MCP server does not use the redirect URI, it is a required field. You can enter any valid URL, such ashttps://localhost:8424/callback.
Installation
Preferred: uv (fast, modern Python installer)
# Install uv if you don't have it
pip install uv
Install from PyPI (recommended)
uv pip install product-hunt-mcp
# or
pip install product-hunt-mcp
Install from GitHub (latest main branch)
uv pip install 'git+https://github.com/jaipandya/producthunt-mcp-server.git'
# or
pip install 'git+https://github.com/jaipandya/producthunt-mcp-server.git'
Install locally from source
uv pip install .
# or
pip install .
🚀 Usage with Claude Desktop & Cursor
Once installed, the product-hunt-mcp command will be available. Add it to your Claude Desktop or Cursor configuration:
{
"mcpServers": {
"product-hunt": {
"command": "product-hunt-mcp",
"env": {
"PRODUCT_HUNT_TOKEN": "your_token_here"
}
}
}
}
- Replace
your_token_herewith your actual Product Hunt API token. - The token must be set as an environment variable in your Claude Desktop or Cursor config for the server to authenticate.
- Always restart your client (Claude Desktop/Cursor) after editing the config file.
Tip: On macOS, Claude Desktop may not always find the
product-hunt-mcpcommand if it’s not in the default PATH. If you encounter issues, you can provide the full path to the executable. After installing, run:which product-hunt-mcpUse the output path in your Claude Desktop config, replacing
"command": "product-hunt-mcp"with the full path (e.g.,"command": "/Users/youruser/.local/bin/product-hunt-mcp").
Finding your configuration file
-
Claude Desktop:
- Windows:
%APPDATA%\claude-desktop\config.json - macOS:
~/Library/Application Support/claude-desktop/config.json - Linux:
~/.config/claude-desktop/config.json
- Windows:
-
Cursor:
- Windows:
%APPDATA%\Cursor\User\settings.json - macOS:
~/Library/Application Support/Cursor/User/settings.json - Linux:
~/.config/Cursor/User/settings.json
- Windows:
Docker
You can also run the server using Docker:
# Build the Docker image
docker build -t product-hunt-mcp .
# Run the Docker container (interactive for MCP)
docker run -i --rm -e PRODUCT_HUNT_TOKEN=your_token_here product-hunt-mcp
For Claude Desktop/Cursor integration with Docker, use this configuration:
{
"mcpServers": {
"product-hunt": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"PRODUCT_HUNT_TOKEN=your_token_here",
"product-hunt-mcp"
],
"env": {}
}
}
}
Security Note: Your
PRODUCT_HUNT_TOKENis sensitive. Do not share it or commit it to version control.
🛠️ MCP Tools
| Tool | Description | Key Parameters |
|---|---|---|
| get_post_details | Get info about a specific post | id or slug, comments_count, comments_after |
| get_posts | Get posts with filters | topic, order, count, featured, posted_before, posted_after |
| get_comment | Get info about a specific comment | id (required) |
| get_post_comments | Get comments for a post | post_id or slug, order, count, after |
| get_collection | Get info about a collection | id or slug |
| get_collections | Get collections with filters | featured, user_id, post_id, order, count |
| get_topic | Get info about a topic | id or slug |
| search_topics | Search topics | query, followed_by_user_id, order, count |
| get_user | Get info about a user | id or username, posts_type, posts_count |
| get_viewer | Get info about the authenticated user | None |
| check_server_status | Check server/API status & authentication | None |
🏗️ Project Structure
product-hunt-mcp/ ├── src/ │ └── product_hunt_mcp/ # Main package directory │ ├── __init__.py │ ├── cli.py # Command-line entry point │ ├── api/ # API clients & queries │ ├── schemas/ # Data validation schemas │ ├── tools/ # MCP tool definitions │ └── utils/ # Utility functions ├── pyproject.toml # Project metadata, dependencies, build config ├── README.md ├── CONTRIBUTING.md ├── CHANGELOG.md ├── Dockerfile └── ... (config files, etc.)
🔄 Rate Limiting
The Product Hunt API has rate limits that this client respects. If you encounter rate limit errors, the client will inform you when the rate limit resets. You can check your current rate limit status using the get_api_rate_limits or check_server_status tools.
🐛 Troubleshooting
- Missing token: Ensure your
PRODUCT_HUNT_TOKENis correctly set as an environment variable. - Connection issues: Verify your internet connection and that the Product Hunt API is accessible.
- Rate limiting: If you hit rate limits, wait until the reset time or reduce your query frequency.
- Claude Desktop/Cursor not finding the server: Verify the path to your Python executable and restart the client.
🤝 Contributing
- PRs and issues welcome!
- Please follow PEP8 and use ruff for linting.
- See
pyproject.tomlfor dev dependencies.
🌐 Links
📝 Notes
- This project is not affiliated with Product Hunt.
- The Product Hunt API is subject to change.
📜 License
MIT
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










