What types of HackerNews data can I analyze?

You can search and retrieve comprehensive details for posts, analyze user profiles, identify current trending topics, and explore comment engagement patterns directly through your AI assistant.

How does this tool benefit AI assistants and developers?

It provides structured, real-time access to HackerNews for in-depth content research, community intelligence, and tech trend analysis, significantly empowering AI models with rich, contextual data.

Is the data access efficient and reliable?

Yes, it features a smart three-tier caching system that reduces API calls by up to 80%, alongside robust error handling, batch operations, and rate limiting for efficient and respectful API usage.

What is the HackerNews MCP Server?

It's a Model Context Protocol (MCP) server that integrates with the HackerNews API, enabling AI assistants to access, analyze, and understand HackerNews content programmatically via standardized interfaces.

HackerNews

Name: HackerNews
Author: Traves-Theberge

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Integrates with the HackerNews API to enable AI assistants to access, analyze, and understand HackerNews content via standardized Model Context Protocol (MCP) interfaces.

This Model Context Protocol (MCP) server offers deep integration with the HackerNews API, empowering AI assistants and clients to seamlessly access, analyze, and understand a wealth of HackerNews content. It provides a standardized interface for interacting with data, allowing users to execute interactive commands for tasks such as searching posts, retrieving full story details including comments, analyzing user profiles, identifying trending topics, and delving into discussion patterns within comments. With a robust caching system and comprehensive API client features, it enhances performance and data richness for AI-driven insights into the HackerNews community.

主要功能

01Analyze user profiles to understand statistics, top stories, and contribution patterns.

02Retrieve comprehensive post details including metadata, comment trees, and engagement metrics.

03Search and filter HackerNews posts by keywords, author, score, and date range.

04Identify current trending topics through keyword frequency analysis from top stories.

05Analyze comment engagement, statistics, top commenters, and discussion patterns.

062 GitHub stars

使用案例

01Perform trend and sentiment analysis to track current tech focus, identify emerging technologies, and monitor community sentiment.

02Gather community intelligence to identify quality contributors, find domain experts, and understand user contribution patterns.

03Conduct content research and analysis to find breaking tech stories, track controversial topics, and analyze discussion quality.