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Bilibili▌

wangshunnn

by wangshunnn

Connect with Bilibili to access user info, video details, and search seamlessly. Enjoy Bilibili TV features without leav

Integrates with Bilibili video platform to retrieve user information, video details, and perform searches without switching contexts.

github stars

★ 13

GitHubnpm
0 commentsdiscussion

Both formats append explainx.ai attribution and the canonical URL for this MCP server listing.

No API key neededDirect access to Chinese video platform

best for

  • / Content creators researching Bilibili videos
  • / Analyzing Chinese video content and creators
  • / Quick video fact-checking and verification

capabilities

  • / Get user information by user ID
  • / Retrieve detailed video information by video ID
  • / Search for videos by keywords
  • / Access video metadata and statistics

what it does

Access Bilibili video platform data directly in Claude. Retrieve user profiles, video details, and search results without leaving your chat interface.

about

Bilibili is a community-built MCP server published by wangshunnn that provides AI assistants with tools and capabilities via the Model Context Protocol. Connect with Bilibili to access user info, video details, and search seamlessly. Enjoy Bilibili TV features without leav It is categorized under other. This server exposes 3 tools that AI clients can invoke during conversations and coding sessions.

how to install

You can install Bilibili in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.

license

MIT

Bilibili is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.

readme

bilibili MCP Server

MIT licensed NPM version NPM Unpacked Size (with version)

English | 简体中文

Model Context Protocol (MCP) Server for the bilibili.com API.

<a href="https://glama.ai/mcp/servers/@wangshunnn/bilibili-mcp-server"> <img width="380" height="200" src="https://glama.ai/mcp/servers/@wangshunnn/bilibili-mcp-server/badge" alt="bilibili Server MCP server" /> </a>

Features

User Info

  • Get user information by mid
  • Search video information by bvid
  • Search videos by keywords

Usage

Claude Desktop

Refer to the official documentation

config for npm (recommended)

{
  "mcpServers": {
    "bilibili": {
      "command": "npx",
      "args": ["-y", "@wangshunnn/bilibili-mcp-server"]
    }
  }
}

or

config for local cloned repo

{
  "mcpServers": {
    "bilibili": {
      "command": "node",
      "args": [
        "/ABSOLUTE/PATH/TO/PARENT/FOLDER/bilibili-mcp-server/dist/index.js"
      ]
    }
  }
}

Save the configuration and restart. You will see the new bilibili MCP option as shown below:

<div align="center"> <img src="./assets/claude-desktop-1.png" alt="" width="500"> <img src="./assets/claude-desktop-2.png" alt="" width="500"> <img src="./assets/claude-desktop-setting.png" alt="" width="500"> </div>

Demo Vedio

https://github.com/user-attachments/assets/813dece6-c9b5-4bc5-96c1-c3b4d284cc76

Local Development

  1. Install dependencies
pnpm i
  1. build
pnpm build
# or
pnpm dev
  1. debug for local repo, see above.

Publishing

To publish a new version to npm:

# For patch version update (0.0.x)
pnpm publish:patch

# For minor version update (0.x.0)
pnpm publish:minor

# For major version update (x.0.0)
pnpm publish:major

These commands will automatically:

  1. Bump the version in package.json
  2. Build the project
  3. Publish to npm registry

Credits

FAQ

What is the Bilibili MCP server?
Bilibili is a Model Context Protocol (MCP) server profile on explainx.ai. MCP lets AI hosts (e.g. Claude Desktop, Cursor) call tools and resources through a standard interface; this page summarizes categories, install hints, and community ratings.
How do MCP servers relate to agent skills?
Skills are reusable instruction packages (often SKILL.md); MCP servers expose live capabilities. Teams frequently combine both—skills for workflows, MCP for APIs and data. See explainx.ai/skills and explainx.ai/mcp-servers for parallel directories.
How are reviews shown for Bilibili?
This profile displays 34 aggregated ratings (sample rows for discoverability plus signed-in user reviews). Average score is about 4.6 out of 5—verify behavior in your own environment before production use.

Use Cases▌

Extended AI Capabilities

Add new capabilities to Claude beyond text generation

Example

Access external data sources, execute code, interact with tools and services

✓

Transform Claude from chatbot to action-taking agent

Context Enhancement

Provide Claude with access to relevant context and data

Example

Load project documentation, access knowledge bases, query databases

✓

Get more accurate, context-aware responses

Workflow Automation

Automate multi-step workflows combining AI and external tools

Example

Research → Summarize → Create document → Send notification

✓

Complete complex tasks end-to-end without manual steps

Implementation Guide▌

Prerequisites

  • ›Claude Desktop 0.7.0+ or Cursor IDE with MCP support
  • ›Basic understanding of MCP architecture and capabilities
  • ›Access credentials for integrated services (if required)
  • ›Willingness to experiment and iterate on configuration

Time Estimate

15-60 minutes depending on server complexity

Installation Steps

  1. 1.Install MCP server: npm install -g [package-name] or via GitHub
  2. 2.Add server configuration to ~/.claude/mcp.json
  3. 3.Provide required credentials and configuration
  4. 4.Restart Claude Desktop to load new server
  5. 5.Test basic functionality with simple prompts
  6. 6.Explore capabilities and experiment with use cases
  7. 7.Document successful patterns for reuse

Troubleshooting

  • ⚠MCP server not loading: Check config syntax, verify installation
  • ⚠Connection errors: Check network, firewall, credentials
  • ⚠Feature not working: Read server docs, check required parameters
  • ⚠Performance issues: Monitor resource usage, check for network latency
  • ⚠Conflicts with other servers: Check port assignments, namespace collisions

Best Practices▌

✓ Do

  • +Read server documentation thoroughly before setup
  • +Start with simple use cases to validate functionality
  • +Test in non-production environment first
  • +Monitor resource usage and performance
  • +Keep servers updated for bug fixes and new features
  • +Document configuration for team members
  • +Use environment variables for sensitive configuration

✗ Don't

  • −Don't grant overly permissive access to MCP servers
  • −Don't skip reading security considerations in docs
  • −Don't expose sensitive data without proper controls
  • −Don't run untrusted MCP servers without code review
  • −Don't ignore error messages—investigate root cause

💡 Pro Tips

  • ★Combine multiple MCP servers for powerful workflows
  • ★Create custom MCP servers for your specific needs
  • ★Share successful configurations with team
  • ★Use MCP inspector for debugging
  • ★Join MCP community for tips and troubleshooting

Technical Details▌

Architecture

Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.

Protocols

  • Model Context Protocol (MCP)
  • JSON-RPC 2.0
  • stdio or HTTP transport

Compatibility

  • Claude Desktop
  • Cursor IDE
  • Custom MCP clients

When to Use This▌

✓ Use When

Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.

✗ Avoid When

Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.

Integration▌

  • →Tool composition: Chain multiple MCP tools in workflows
  • →Context augmentation: Provide AI with relevant external data
  • →Action delegation: Let AI execute tasks on external systems
  • →Bidirectional sync: Keep AI context and external systems in sync

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.

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Ratings

4.6★★★★★34 reviews
  • ★★★★★Chaitanya Patil· Dec 12, 2024

    Strong directory entry: Bilibili surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • ★★★★★Piyush G· Nov 3, 2024

    Bilibili has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.

  • ★★★★★Shikha Mishra· Oct 22, 2024

    According to our notes, Bilibili benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.

  • ★★★★★Yash Thakker· Sep 13, 2024

    We wired Bilibili into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • ★★★★★Sophia Gonzalez· Sep 13, 2024

    We evaluated Bilibili against two servers with overlapping tools; this profile had the clearer scope statement.

  • ★★★★★Aisha Johnson· Sep 5, 2024

    Bilibili is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

  • ★★★★★Meera Jain· Sep 5, 2024

    I recommend Bilibili for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.

  • ★★★★★Daniel Shah· Aug 24, 2024

    We wired Bilibili into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.

  • ★★★★★Kiara Torres· Aug 24, 2024

    Strong directory entry: Bilibili surfaces stars and publisher context so we could sanity-check maintenance before adopting.

  • ★★★★★Dhruvi Jain· Aug 4, 2024

    Bilibili is a well-scoped MCP server in the explainx.ai directory — install snippets and categories matched our Claude Code setup.

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