Bilibili MCP
B

Bilibili MCP

A tool for obtaining Bilibili's hot list based on FastMCP, supporting real-time calls to popular video data through an MCP client
2 points
8.9K

What is bilibili-mcp?

bilibili-mcp is a convenient tool for connecting to Bilibili's hot list. You can obtain information about the most popular Bilibili videos currently through simple commands. It is designed for content creators, data analysts, and Bilibili enthusiasts, allowing them to grasp Bilibili's popular trends without complex operations.

How to use bilibili-mcp?

Just install the Python environment and run simple commands, and you can call the hot list query function through an MCP client (such as Cursor). The system will automatically handle data acquisition and format conversion, and return clear and readable video information.

Applicable scenarios

• Content creators looking for popular topics • Data analysts tracking video popularity trends • Bilibili users quickly discovering high-quality content • Teaching demonstrations of API call examples

Main features

Real-time hot list data
Directly obtain information about the most popular videos on Bilibili currently, with timely and accurate data updates
Customizable query
Supports setting the number of returned results (up to 10) to meet different needs
Structured data
Returns standard format data including title, link, description, views, and likes
Advantages
Easy to use, no complex configuration required
Fast response, efficient data acquisition
Seamless integration with mainstream MCP clients
Lightweight design, low resource consumption
Limitations
Only supports obtaining the top 10 videos on the hot list
Relies on Bilibili's public interface and may be affected by interface changes
Requires a Python 3.12 or higher environment

How to use

Install dependencies
Ensure that Python 3.12+ is installed on the system, and then install the required dependency packages through pip
Start the service
Use the uv tool to run the bilibili-mcp service
Call the function
Call the get_popular method in the MCP client to obtain hot list data

Usage examples

Obtaining inspiration for content creation
Creators understand current popular content trends by querying the hot list and find inspiration for creation
Collecting samples for data analysis
Researchers regularly obtain hot list data to analyze the relationship between video popularity and content characteristics

Frequently Asked Questions

Why can I only get a maximum of 10 results?
What is the data update frequency?
Do I need a Bilibili account or API key?

Related resources

Bilibili official website
Bilibili Danmaku Video Website
FastMCP documentation
Documentation for the MCP protocol implementation framework
Python httpx library
Documentation for the HTTP client library

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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