Hackernews-MCP-Typescript

Traves-Theberge/Hackernews-MCP-Typescript

3.4

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A comprehensive Model Context Protocol (MCP) server that integrates with the HackerNews API, allowing AI assistants to access and analyze HackerNews content through standardized MCP interfaces.

The HackerNews MCP Server is designed to provide seamless integration with the HackerNews API, enabling AI assistants to efficiently access, analyze, and understand content from HackerNews. This server leverages the Model Context Protocol (MCP) to offer a standardized interface for interacting with the API, making it easier for developers to build AI applications that can process and interpret HackerNews data. With features like smart caching, batch operations, and comprehensive API coverage, the server ensures efficient data retrieval and analysis. It supports various interactive commands to search posts, analyze user profiles, and discover trending topics, making it a valuable tool for content research, community analysis, and trend monitoring. The server is built with performance and privacy in mind, offering a robust solution for accessing public data while respecting user privacy and API usage limits.

Features

  • Smart Caching System: Reduces API calls by 80% with a three-tier caching mechanism.
  • Comprehensive API Coverage: Supports all HackerNews API endpoints for extensive data access.
  • Batch Operations: Efficiently loads multiple items, enhancing performance.
  • Enhanced Data Analysis: Provides detailed story metadata, user statistics, and comment analysis.
  • Respectful API Usage: Implements rate limiting and robust error handling.

Tools

  1. search_posts

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

  2. get_post

    Retrieve comprehensive post details including metadata and comment trees.

  3. search_user

    Analyze user profiles and activity, including statistics and contribution patterns.

  4. search_trending

    Identify current trending topics through keyword frequency analysis.

  5. search_comments

    Analyze comment engagement, statistics, and discussion patterns.