Understanding User Profiles

The Hacker News MCP Server provides comprehensive access to user profile information, allowing you to explore individual contributor data and activity histories. Each Hacker News user maintains a public profile that includes their username, karma score (a measure of community contribution), account creation date, biographical information (if provided), and links to all 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 fetch the profile data and present it in a structured format, making it easy to understand the user's standing in the community and their areas of interest.

Accessing User Activity

Beyond basic profile information, you can dive deeper into what users have posted and discussed over time. User activity data includes:

Submissions: View all stories and links a user has submitted to Hacker News. This provides insight into what topics they find valuable enough to share with the community and can help identify subject matter expertise.

Comments: Access the complete comment history for any user. These comments often reveal technical knowledge, opinions on industry trends, and engagement with specific topics. Analyzing comment patterns can help you identify thought leaders in particular domains or understand how active community members discuss emerging technologies.

Karma Analysis: The karma score reflects how much value the community has found in a user's contributions through upvotes. Higher karma typically indicates respected, long-term community members whose opinions carry weight.

Practical Applications

User profile and activity data enables several valuable use cases:

Expert Identification: Find knowledgeable contributors in specific technical areas by analyzing their submission and comment histories. If you need perspectives on Rust programming, machine learning, or startup strategy, you can identify users who consistently engage with these topics.

Influence Mapping: Understand which community members drive conversations and whose submissions regularly reach the front page. This helps identify influential voices in the tech community.

Engagement Research: Study how particular users interact with topics relevant to your interests, learning from their insights and perspectives accumulated over time.

Making Requests

Requesting user data is straightforward through natural language queries. Ask your AI assistant questions like "Show me the profile for user [username]" or "What has [username] been discussing recently?" The server handles the technical details, returning organized data you can immediately analyze or discuss.