Bilibili Mcp
What is Bilibili Mcp
bilibili_mcp is a Model Context Protocol (MCP) server that provides access to Bilibili’s API functionalities, allowing users to interact with various features of the Bilibili platform.
Use cases
Use cases for bilibili_mcp include developing applications that search for videos based on keywords, retrieving detailed information about specific videos, accessing user profiles, and collecting comments for analysis.
How to use
To use bilibili_mcp, ensure you have Python 3.7 or higher installed. Install the necessary dependencies using ‘pip install bilibili-api mcp-server-fastmcp’, and then run the server with ‘python bilibili_mcp_server.py’.
Key features
Key features of bilibili_mcp include searching Bilibili content, retrieving video information, getting user information, and fetching video comments.
Where to use
bilibili_mcp can be used in applications that require integration with Bilibili’s content, such as video analysis tools, social media applications, or educational platforms that utilize Bilibili’s resources.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Bilibili Mcp
bilibili_mcp is a Model Context Protocol (MCP) server that provides access to Bilibili’s API functionalities, allowing users to interact with various features of the Bilibili platform.
Use cases
Use cases for bilibili_mcp include developing applications that search for videos based on keywords, retrieving detailed information about specific videos, accessing user profiles, and collecting comments for analysis.
How to use
To use bilibili_mcp, ensure you have Python 3.7 or higher installed. Install the necessary dependencies using ‘pip install bilibili-api mcp-server-fastmcp’, and then run the server with ‘python bilibili_mcp_server.py’.
Key features
Key features of bilibili_mcp include searching Bilibili content, retrieving video information, getting user information, and fetching video comments.
Where to use
bilibili_mcp can be used in applications that require integration with Bilibili’s content, such as video analysis tools, social media applications, or educational platforms that utilize Bilibili’s resources.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Bilibili MCP Server
A Model Context Protocol (MCP) server that provides access to Bilibili’s API functionality.
Features
- Search Bilibili content
- Get video information
- Get user information
- Fetch video comments
Installation
- Ensure you have Python 3.7+ installed
- Install dependencies:
pip install bilibili-api mcp-server-fastmcp
- Run the server:
python bilibili_mcp_server.py
API Endpoints
General Search
@mcp.tool('general_search')
def general_search(keyword: str) -> dict
Searches Bilibili for the given keyword.
Example:
{
"keyword": "python tutorial"
}Video Information
@mcp.tool('video_info')
def video_info(aid: int) -> dict
Gets information about a video by its AID.
Example:
{
"aid": 123456
}User Information
@mcp.tool('user_info')
def user_info(uid: int) -> dict
Gets information about a user by their UID.
Example:
{
"uid": 123456
}Video Comments
@mcp.tool('video_comments')
def video_comments(aid: int, page: int = 1) -> dict
Gets comments for a video by AID and page number.
Example:
{
"aid": 123456,
"page": 1
}Popular Videos
@mcp.tool('popular_videos')
def popular_videos() -> dict
Gets currently popular videos on Bilibili.
Example:
{}Error Handling
All endpoints return:
- Success: API response data
- Error: Dictionary with “error” key containing error message
Common errors:
- Invalid input parameters (ValueError)
- API request failures
- Network issues
Logging
The server logs all operations to stdout with timestamps. Logs include:
- API calls with parameters
- Successful responses
- Error conditions
License
没有
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.
