MCP ServerSTDIOOfficialv0.1.5

Frankxmx Dailyhot MCP Server

Aggregate trending data from 55+ platforms including Weibo, Zhihu, Bilibili, and GitHub for LLM and RAG applications. Developers use this to inject real-time trending content into AI systems without building individual platform scrapers.

io.github.FrankXMX/dailyhotmcp

Hosted URL

Local install

Transport

STDIO

Auth

1 required env var

What the Frankxmx Dailyhot MCP server does

How models use it and what it is built for.

Aggregate trending data from 55+ platforms including Weibo, Zhihu, Bilibili, and GitHub for LLM and RAG applications. Developers use this to inject real-time trending content into AI systems without building individual platform scrapers.

Connect to Frankxmx Dailyhot

Local install — runs as a subprocess.

npx @frank-x/dailyhot-mcp@0.1.5

Environment variables

Configuration this server reads at startup.

  • YOUR_API_KEYRequiredSecret

    Your API key for the service

Resources

Where to find authoritative docs and source for Frankxmx Dailyhot.

Example prompts for Frankxmx Dailyhot

Paste any of these into Agent Studio after connecting Frankxmx Dailyhot.

  • Show me today's top trending topics across Weibo and Zhihu
  • What are the most popular GitHub repositories trending right now
  • Fetch the current hot list from Bilibili and return as structured JSON
  • Explain how to configure YOUR_API_KEY for production deployment

Frankxmx Dailyhot MCP server — FAQ

Common questions about connecting and running Frankxmx Dailyhot.

  • What platforms does this MCP server pull trending data from?

    It aggregates hot lists from 55+ platforms including Weibo, Zhihu, Bilibili, GitHub, and others. The exact platform list is available in the server documentation.

  • How do I set up the API key for dailyhotmcp?

    Set the YOUR_API_KEY environment variable before running the server. This is required for authentication with the trending data service.

  • Can I use this server with RAG and LLM applications?

    Yes, it's specifically designed for LLM and RAG scenarios. You can inject real-time trending data into your AI pipelines to keep responses current.

  • What format does the trending data come back in?

    The server returns structured data suitable for LLM processing. Refer to the server's schema documentation for exact field formats and response structure.

  • Is there rate limiting or pricing for the API key?

    Rate limits and pricing depend on your API key tier. Check your account dashboard or the service documentation for current limits and billing details.

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