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Producthunt MCP Server logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 6:47:06 PM

Producthunt MCP Server

User RatingsBe the first to rate and review this MCP server!
View Repository53 GitHub StarsTotal stargazers on GitHub for the source repository (53 stars).Visit Website
product-huntsearchdata-extractionmcp

Connects MCP clients to Product Hunt for querying posts, comments, collections, topics, users, votes, and authentication status.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
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We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "jaipandya-producthunt-mcp-server": {
      "command": "uvx",
      "args": [
        "product-hunt-mcp"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives๐Ÿ’ฌ More in Communication

Overview

The jaipandya/producthunt-mcp-server MCP server exposes Product Hunt data through MCP tools for compatible AI clients. It uses a Product Hunt developer token supplied through PRODUCT_HUNT_TOKEN and provides queries for posts, comments, collections, topics, users, and the authenticated viewer. Filters, pagination, ordering, and date parameters support targeted data retrieval. Reach for the jaipandya/producthunt-mcp-server MCP server when an agent, dashboard, bot, or automation needs Product Hunt data through Claude Desktop, Cursor, or another MCP client.

Use cases

โ€ขQuery trending or filtered Product Hunt posts
โ€ขInspect comments and user activity
โ€ขSearch Product Hunt topics for an agent
โ€ขBuild dashboards or automations from Product Hunt data

Key features

โ€ขRetrieve posts, comments, collections, topics, and users
โ€ขFilter posts by topic, date, votes, and featured status
โ€ขPaginate post comments and related results
โ€ขInspect the authenticated Product Hunt viewer
โ€ขCheck API connectivity and authentication status
โ€ขRun locally with Python or Docker

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Producthunt MCP Server.

Extracted Tool Capabilities
Retrieve posts, comments, collections, topics, and users
Filter posts by topic, date, votes, and featured status
Paginate post comments and related results
Inspect the authenticated Product Hunt viewer
Check API connectivity and authentication status
Run locally with Python or Docker

How Producthunt MCP Server works

What jaipandya/producthunt-mcp-server MCP server does

The jaipandya/producthunt-mcp-server MCP server connects an MCP-compatible client to the Product Hunt API. It makes Product Hunt entities available as callable tools rather than requiring an agent to handle direct API requests. Supported data includes posts, comments, collections, topics, users, votes, and details about the authenticated Product Hunt account.

The server is suitable for assistants that need to answer questions about Product Hunt activity, developers building bots or dashboards around Product Hunt data, and automations that monitor or filter product discovery information. It is not affiliated with Product Hunt, and the Product Hunt API may change over time.

How it works

The server runs locally as a Python command-line application and communicates with an MCP client. Product Hunt authentication uses a developer token placed in the PRODUCT_HUNT_TOKEN environment variable. The token is sent to the Product Hunt API for requests that require authentication.

Queries can retrieve individual resources by ID or slug, or return collections of resources with filters. Posts can be constrained by topic, ordering, count, featured status, and posting dates. Comments support post-based retrieval, ordering, counts, and pagination cursors. Collection and topic tools provide lookup and search behavior, while user tools support account details, post types, and post counts.

Setup and configuration

Python 3.10 or newer is required. Install the published package with pip install product-hunt-mcp, or use the equivalent uv pip install product-hunt-mcp command. The jaipandya/producthunt-mcp-server MCP server starts with the product-hunt-mcp executable after installation.

Create a Product Hunt application and use its Developer Token as the server credential. Set it before starting the process:

server.ts
export PRODUCT_HUNT_TOKEN=your_token_here
product-hunt-mcp

Claude Desktop and Cursor configurations should run product-hunt-mcp and define PRODUCT_HUNT_TOKEN in the configuration's env object. Restart the client after changing its MCP configuration. Docker is also supported: build the included image, then run it interactively with PRODUCT_HUNT_TOKEN passed into the container.

Tools and capabilities

Available tools include:

  • get_post_details for a post and optional comment retrieval.
  • get_posts for filtered post listings.
  • get_comment and get_post_comments for comment data.
  • get_collection and get_collections for collection lookups and listings.
  • get_topic and search_topics for topic retrieval and search.
  • get_user and get_viewer for user and authenticated-account information.
  • check_server_status for API connectivity and authentication status.

The README also refers to get_api_rate_limits when discussing rate-limit status, but it is not included in the listed MCP tools.

Limitations and notes

A valid Product Hunt API token is required, and requests remain subject to Product Hunt rate limits. When limits are reached, the client reports when the limit resets; reducing request frequency may be necessary. Missing credentials, network access problems, or an unavailable Product Hunt API can prevent requests from succeeding.

The jaipandya/producthunt-mcp-server MCP server does not use the OAuth redirect URI for its own operation, although Product Hunt requires a valid redirect URI when creating an application. Store PRODUCT_HUNT_TOKEN outside source control because it is sensitive. On macOS, clients may need the full path to the installed executable if it is not available on the default PATH.

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
53
Stargazers on the source repository.
Last commit
1y ago
Most recent push to the default branch.
Directory activity
4 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Producthunt MCP Server

Install Python 3.10 or newer, then run `pip install product-hunt-mcp` or `uv pip install product-hunt-mcp`.

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Technical Specs & Signals

Category๐Ÿ’ฌCommunication
PricingFree
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
AuthAPI key
LicenseMIT
ClientsClaude Desktop, Cursor
Last updatedSep 4, 2026
10/10 checks healthy over the last 33d
Views4
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars53
GitHub Star CountTotal stargazers on GitHub representing community popularity (53 stars).
Last commit1y ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Apr 19, 2025
41Quality signal: Fair ยท 41/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools17/30
Adoption & activity3/15
Community engagement1/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 17d ago via OSV.dev ยท product-hunt-mcp (PyPI)

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