vid-agent-mcp

MCP server for video understanding — transcribe Bilibili videos, search, and analyze local files through natural conversation with Claude.

Chat with Claude and ask it to watch a video for you. Send a Bilibili link, get back a structured summary with key points, visual moments, and a "worth watching" verdict — all through MCP tools.

How it works

You: "转录一下这个视频 BV1pzjy6GEkC"

Claude: *calls transcribe tool*
        → Downloads video via BBDown
        → Transcribes audio with faster-whisper
        → Identifies key visual moments via VLM
        → Returns structured summary

You: "最近有什么AI Agent新视频？"

Claude: *calls search_by_intent tool*
        → Expands intent into multiple search queries
        → Searches Bilibili concurrently
        → Merges & ranks results by popularity

Tools

Tool	Description
transcribe	Download + analyze a Bilibili video
transcribe_local	Analyze a local video file
search	Search Bilibili by keyword
search_by_intent	AI-powered search with natural language
get_result	Read a previously saved result

Setup

Prerequisites

• Python 3.11+
• ffmpeg (install via conda install ffmpeg or system package manager)
• BBDown (for Bilibili downloads) — install from here or use an existing install
• A MiMo API key (or any OpenAI-compatible VLM API)

Install

# 1. Clone
git clone https://github.com/ikerrrrrrrrrrr/bili-vid-agent
cd bili-vid-agent

# Or install the MCP server directly
pip install vid-agent-mcp

# 2. Configure
cp .env.example .env
# Edit .env with your API key

# 3. Run
vid-agent-mcp

Claude Desktop configuration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "vid-agent": {
      "command": "vid-agent-mcp",
      "env": {
        "VLM_API_KEY": "your-key-here"
      }
    }
  }
}

Or point to a local install:

{
  "mcpServers": {
    "vid-agent": {
      "command": "conda",
      "args": ["run", "-n", "vid_agent", "vid-agent-mcp"]
    }
  }
}

Configuration

All config via .env file or environment variables:

Variable	Default	Description
VLM_API_KEY	—	MiMo API key (required)
VLM_BASE_URL	https://api.xiaomimimo.com/v1	API base URL
VLM_MODEL	mimo-v2-omni	Model for visual analysis
SUMMARY_MODEL	mimo-v2.5-pro	Model for summary generation
BBDOWN_PATH	bbdown	Path to BBDown binary
WHISPER_MODEL	turbo	Whisper model size
CACHE_DIR	./cache	Download/transcription cache
WORK_DIR	./work	Working directory

License

Apache 2.0