Claude Hacker News MCP Server

The MCP Claude Hacker News server bridges the gap between Claude Desktop and the Hacker News ecosystem, allowing developers to query, browse, and interact with the platform’s content directly from an AI assistant. By exposing Hacker News data through the Model Context Protocol, the server eliminates the need for custom API wrappers or manual HTTP requests, giving developers a ready‑to‑use integration that can be invoked with simple prompts or tool calls.

This server solves the common problem of real‑time access to trending tech news and community discussions within AI workflows. Instead of scraping or parsing HTML, developers can request the latest stories, top‑rated posts, detailed story metadata, and threaded comments in a structured format. The output is cleaned for readability, ensuring that the assistant can present concise summaries or deeper dives without clutter. This makes it ideal for knowledge‑base augmentation, content curation, and automated research pipelines.

Key capabilities include:

• Story discovery: Fetch the newest, top, or best‑rated stories with a single call.
• Detail retrieval: Obtain full story information such as author, score, and URL.
• Comment navigation: Read threaded comments for any story, preserving hierarchy.
• Formatting hygiene: The server strips unnecessary markup and normalizes text for easy display in conversational contexts.

Real‑world use cases span from building a news briefing tool that updates users on the latest tech trends, to creating a research assistant that pulls relevant Hacker News discussions into academic literature reviews. In marketing, teams can monitor emerging topics and sentiment in real time; in education, teachers can surface current industry debates for classroom discussion. The server’s clean API makes it straightforward to integrate into existing MCP‑enabled pipelines, whether as a standalone tool or as part of a larger suite of data connectors.

Because it operates over MCP, the Hacker News server benefits from Claude Desktop’s native tool‑calling mechanics: developers can define prompt templates that automatically trigger the appropriate MCP endpoint, and the assistant can handle pagination or filtering without additional code. This tight coupling reduces latency, improves reliability, and keeps the developer’s focus on higher‑level logic rather than low‑level networking. The result is a powerful, plug‑and‑play component that enriches AI assistants with timely, community‑driven insights.