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The Hacker News MCP Server provides comprehensive access to user profile data, allowing you to explore individual contributor information and their complete activity history on the platform. Each Hacker News user maintains a public profile that includes their username, karma score, account creation date, biographical information (if provided), and a complete record of their submissions and comments.
To retrieve a user profile, simply ask your AI assistant for information about a specific Hacker News user by their username. The server will return structured data including the user's total karma points (earned through upvotes on their contributions), when they joined the platform, and any "about" text they've added to describe themselves or share contact information.
One of the most powerful features of user profile retrieval is access to complete activity history. This includes two primary types of content:
Submissions: Every story or Ask HN post that a user has submitted to Hacker News. This history reveals the topics they care about, the sources they value, and their engagement patterns over time.
Comments: All comments the user has posted across various discussions. Comment history often provides the richest insight into a user's expertise, perspectives, and areas of interest.
When you request activity history, the data is organized chronologically, making it easy to track how a user's interests or contributions have evolved. Each item includes relevant metadata such as timestamps, scores, and links to the original content.
Expert Identification: Use profile and activity data to identify domain experts within the Hacker News community. Users with high karma and relevant comment history can provide valuable perspectives on technical topics.
Influence Assessment: Analyze submission and comment patterns to understand which community members consistently contribute high-quality content that resonates with the community.
Research Context: When evaluating the credibility of information or opinions shared on Hacker News, reviewing the contributor's profile and history helps establish their expertise and track record.
Network Analysis: Track interactions between users and identify thought leaders whose contributions frequently spark meaningful discussions.
To retrieve user information, simply ask natural language questions like "What's the profile of user X?" or "Show me recent activity from user Y." The server handles all API interactions and returns clean, structured data ready for analysis. You can request specific aspects of a profile or comprehensive overviews depending on your needs, making user research efficient and straightforward.
The GitLab integration lets you interact with your repositories, issues, merge requests, and pipelines directly through natural language commands. Use it to search code, review MRs, update issue statuses, check CI/CD pipeline results, and manage your GitLab projects without leaving your workflow.
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