Bilibili Video Info MCP
Retrieves subtitle content, danmaku (bullet comments), and user comments from Bilibili videos using their URL, allowing AI agents to analyze and process video-related text content from the platform.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Bilibili Video Info MCPget subtitles for https://www.bilibili.com/video/BV1x341177NN"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server for Bilibili Video Info
A Bilibili MCP Server that can retrieve subtitles, danmaku (bullet comments), and comments information from videos using the video URL.
Usage
This MCP server supports three transport methods:
stdio
{
"mcpServers": {
"bilibili-video-info-mcp": {
"command": "uvx",
"args": [
"bilibili-video-info-mcp"
],
"env": {
"SESSDATA": "your valid sessdata"
}
}
}
}sse (Server-Sent Events) run bilibili-video-info-mcp in sse mode
cp .env.example .env
uvx run --env .env bilibili-video-info-mcp ssethen config your mcp client
{
"mcpServers": {
"bilibili-video-info-mcp": {
"url": "http://{your.ip.address}:$PORT$/sse"
}
}
}streamable-http (HTTP Streaming) run bilibili-video-info-mcp in streamable-http mode
cp .env.example .env
uvx run --env .env bilibili-video-info-mcp streamable-httpthen config your mcp client
{
"mcpServers": {
"bilibili-video-info-mcp": {
"url": "http://{your.ip.address}:$PORT$/mcp"
}
}
}
}Related MCP server: bilibili-subtitle-fetch
MCP Tools List
1. Get Video Subtitles
{
"name": "get_subtitles",
"arguments": {
"url": "https://www.bilibili.com/video/BV1x341177NN"
}
}2. Get Video Danmaku (Bullet Comments)
{
"name": "get_danmaku",
"arguments": {
"url": "https://www.bilibili.com/video/BV1x341177NN"
}
}3. Get Video Comments
{
"name": "get_comments",
"arguments": {
"url": "https://www.bilibili.com/video/BV1x341177NN"
}
}FAQ
1. How to find SESSDATA?
Log in to the Bilibili website
Open browser developer tools (F12)
Go to Application/Storage -> Cookies
Find the value corresponding to SESSDATA
2. Error "SESSDATA environment variable is required"
Make sure you have set the environment variable:
export SESSDATA="your SESSDATA value"3. What video link formats are supported?
Standard Bilibili video links are supported, such as:
https://b23.tv/xxxxx (short links)
Any link containing a BV number
Available Tools
3 toolsget_commentsARead-only
Get popular comments from a Bilibili video
Args:
url: Bilibili video URL, e.g., https://www.bilibili.com/video/BV1x341177NN
Returns:
List of popular comments including comment content, user information, and metadata such as like counts
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds that the tool returns comment content, user info, and metadata, which is useful but does not cover potential rate limits or pagination behavior. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (3 sentences), well-structured with clear purpose, Args, and Returns sections. Every sentence adds value with no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only tool with one parameter and no output schema, the description adequately covers purpose, parameter format, and return content. Missing error handling or rate limits but acceptable given simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description provides a detailed explanation of the 'url' parameter with an example URL, adding meaningful context beyond the schema's 'Url' title.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get', the resource 'popular comments', and the source 'Bilibili video'. It distinguishes from sibling tools (get_danmaku for danmaku, get_subtitles for subtitles).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide guidance on when to use this tool vs alternatives like get_danmaku. It only describes what it does, without context on selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_danmakuARead-only
Get danmaku (bullet comments) from a Bilibili video
Args:
url: Bilibili video URL, e.g., https://www.bilibili.com/video/BV1x341177NN
Returns:
List of danmaku (bullet comments) with content, timestamp and user information
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, indicating safe read operation. The description goes beyond by detailing the return structure (list with content, timestamp, user info), adding value. No mention of potential errors or authentication, but sufficient for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, using two clear paragraphs. The first states the purpose, the second details arguments and returns. No redundant sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and no output schema, the description covers purpose, parameter format, and return values adequately. However, it lacks details on potential limitations (e.g., pagination) or edge cases, which would be beneficial but not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description adds meaning by providing an example URL format and explaining the parameter expects a Bilibili video URL. This compensates for the schema's lack of description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get danmaku') and the resource ('from a Bilibili video'). It includes an example URL, making the purpose unambiguous. The tool is distinct from siblings get_comments and get_subtitles as it specifies 'bullet comments'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage is implied by the tool name and description, but there is no explicit guidance on when to use this tool versus alternatives. No exclusions or prerequisites are mentioned, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_subtitlesARead-only
Get subtitles from a Bilibili video
Args:
url: Bilibili video URL, e.g., https://www.bilibili.com/video/BV1x341177NN
Returns:
List of subtitles grouped by language. Each entry contains subtitle content with timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true; the description adds value by specifying the return structure (list grouped by language with timestamps) beyond the annotations, but does not disclose other behaviors like rate limits or auth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (5 lines) and front-loaded with the purpose, but the Args/Returns formatting could be more streamlined; still efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read tool with one parameter and no output schema, the description covers input format and output structure adequately, though it omits potential errors or prerequisites.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description compensates by explaining the 'url' parameter with an example and format, adding meaning beyond the bare schema definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Get subtitles from a Bilibili video' and provides an example URL, making the tool's purpose clear and distinguishing it from sibling tools like get_comments and get_danmaku.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives; it does not mention context for use or exclusion criteria, leaving agents to infer from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
3 tool updates
- First observed
get_comments - First observed
get_danmaku - First observed
get_subtitles
TDQS
Each tool retrieves a distinct type of content: comments, danmaku, and subtitles. There is no overlap in functionality, making it easy for an agent to select the appropriate tool.
All tool names follow a consistent 'get_' prefix followed by a resource name in snake_case (get_comments, get_danmaku, get_subtitles), providing a predictable pattern.
With 3 tools, the count is reasonable for a focused MCP server. It is within the ideal range, though it could be expanded slightly to cover more video info without becoming unwieldy.
The server name suggests it covers Bilibili video information, but the tool set lacks essential video metadata such as title, description, uploader, or statistics, leaving a significant gap for general video information tasks.
Maintenance
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