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Product Hunt
- python
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GitHub Stars
python
Language
4 months ago
First Indexed
3 weeks ago
Catalog Refreshed
Documentation & install
Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.
Installation
Add the following to your MCP client configuration file.
Configuration
View docs{
"mcpServers": {
"jaipandya-producthunt-mcp-server": {
"command": "product-hunt-mcp",
"args": [],
"env": {
"PRODUCT_HUNT_TOKEN": "your_token_here"
}
}
}
}You have a plug-and-play MCP server that connects Product Hunt data to any Model Context Protocol (MCP) client. It lets you fetch posts, collections, topics, users, votes, and comments, enabling AI assistants, chatbots, and automations to query Product Hunt in a structured way.
How to use
Install and run the MCP server, then configure your MCP client to reach it. You can run the server directly or inside Docker. The server authenticates using your Product Hunt API token, which you provide as an environment variable. Once running, you can query posts, comments, topics, users, and more from your MCP-enabled client.
To connect from your MCP client, specify the server as an MCP endpoint with the appropriate command to start the server and ensure the token is available in the environment. For example, you can run the server locally with the token set and then point your client to that local MCP instance.
How to install
Prerequisites: Python 3.10+ and a Product Hunt API token.
pip install uv
Install the MCP server from PyPI or via the offering package manager.
# Preferred: uv (fast, modern Python installer)
pip install uv
# Install the MCP server from PyPI
uv pip install product-hunt-mcp
# or
pip install product-hunt-mcp
Alternative installation from source or GitHub is supported via uvx when you want the 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 if you prefer a local build.
uv pip install .
# or
pip install .
Set the token in your environment and start the server.
export PRODUCT_HUNT_TOKEN=your_token_here
product-hunt-mcp
Docker usage
You can run the MCP server inside Docker and provide the token through the container environment.
# 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
Connecting from MCP clients
Configure your MCP client to start the server and supply the token as an environment variable. Here is a representative configuration for a client that expects an MCP endpoint named product-hunt.
{
"mcpServers": {
"product-hunt": {
"command": "product-hunt-mcp",
"env": {
"PRODUCT_HUNT_TOKEN": "your_token_here"
}
}
}
}
Security and best practices
Your API token is sensitive. Do not share it or commit it to version control. When using Docker, avoid embedding the token directly in code; pass it through the environment as shown above.
Available tools
get_post_details
Get detailed information for a specific post by id or slug, including related data such as comments if requested.
get_posts
Retrieve a list of posts with filters like topic, order, count, and whether to include featured items.
get_comment
Fetch information about a single comment by its id.
get_post_comments
Obtain comments for a specific post, with options for ordering and limiting results.
get_collection
Get information about a specific collection by id or slug.
get_collections
List collections with filters such as featured, user_id, post_id, order, and count.
get_topic
Retrieve information about a topic by id or slug.
search_topics
Search topics by query with optional filters like followed_by_user_id, order, and count.
get_user
Get user information by id or username, with options for posts type and posts count.
get_viewer
Fetch information about the authenticated user.
check_server_status
Check server/API status and authentication state.