Labsco
DeepSRT logo

DeepSRT

★ 50

from DeepSRT

Summarize YouTube videos using the DeepSRT API.

🔥🔥🔥✓ VerifiedFreeNeeds API keys
#automation#devops#git#maps#translation#video-editing

DeepSRT MCP Server

A Model Context Protocol (MCP) server that provides YouTube video summarization and transcript extraction functionality through integration with DeepSRT's API and direct YouTube caption access.

TL;DR

{
  "mcpServers": {
    "deepsrt": {
      "type": "stdio",
      "command": "bunx",
      "args": [
        "@deepsrt/deepsrt-mcp@latest",
        "--server"
      ]
    }
  }
}

Architecture

graph TB
    subgraph "MCP Client"
        Client[Claude Desktop / Cline]
    end
    
    subgraph "DeepSRT MCP Server"
        Server[MCP Server]
        SummaryTool[get_summary]
        TranscriptTool[get_transcript]
        
        Server --> SummaryTool
        Server --> TranscriptTool
    end
    
    subgraph "External APIs"
        YouTube[YouTube InnerTube API]
        DeepSRT[DeepSRT Worker API]
        Captions[YouTube Caption API]
    end
    
    Client --> Server
    SummaryTool --> YouTube
    SummaryTool --> DeepSRT
    TranscriptTool --> YouTube
    TranscriptTool --> Captions

Sequence Flow

sequenceDiagram
    participant User
    participant MCP as MCP Client
    participant Server as DeepSRT MCP Server
    participant YouTube as YouTube InnerTube API
    participant DeepSRT as DeepSRT Worker API
    participant Captions as YouTube Caption API

    Note over User,Captions: Summary Generation Flow
    User->>MCP: Request video summary
    MCP->>Server: get_summary(videoId, lang, mode)
    
    Server->>Server: Extract video ID from URL
    Server->>YouTube: POST /youtubei/v1/player
    Note right of YouTube: Get video metadata<br/>and caption tracks
    YouTube-->>Server: Video details + caption tracks
    
    Server->>Server: Select best caption track<br/>(manual > auto-generated)
    Server->>Server: Extract transcript argument<br/>from caption URL
    
    par Summary Request
        Server->>DeepSRT: GET /transcript2?action=summarize
        Note right of DeepSRT: X-Transcript-Arg header<br/>contains caption URL params
        DeepSRT-->>Server: Generated summary
    and Title Translation
        Server->>DeepSRT: GET /transcript2?action=translate
        DeepSRT-->>Server: Translated title
    end
    
    Server->>Server: Format markdown response<br/>with metadata + summary
    Server-->>MCP: Formatted summary response
    MCP-->>User: Display summary

    Note over User,Captions: Transcript Extraction Flow
    User->>MCP: Request video transcript
    MCP->>Server: get_transcript(videoId, lang)
    
    Server->>Server: Extract video ID from URL
    Server->>YouTube: POST /youtubei/v1/player
    YouTube-->>Server: Video details + caption tracks
    
    Server->>Server: Select best caption track<br/>for preferred language
    Server->>Captions: GET caption XML from baseUrl
    Captions-->>Server: Raw XML transcript
    
    Server->>Server: Parse XML transcript<br/>- Extract timestamps<br/>- Decode HTML entities<br/>- Format text
    Server->>Server: Generate markdown response<br/>with timestamps
    Server-->>MCP: Formatted transcript
    MCP-->>User: Display transcript with timestamps

Technical Architecture

Core Components

1. MCP Server Layer

  • Runtime Support: Both Node.js and Bun execution
  • Protocol Handling: Model Context Protocol (MCP) request/response management
  • Tool Registration: get_summary and get_transcript tools
  • Error Handling: Comprehensive error management with user-friendly messages

2. Video Processing Pipeline

  • URL Parser: Supports multiple YouTube URL formats and direct video IDs
  • InnerTube Integration: Direct YouTube API access without API keys
  • Caption Discovery: Automatic detection of available caption tracks
  • Quality Selection: Prioritizes manual captions over auto-generated ones

3. Transcript Processing

  • XML Parser: Handles YouTube's <timedtext> format
  • Entity Decoder: Converts HTML entities to readable text
  • Timestamp Formatter: Converts milliseconds to [MM:SS] format
  • Content Filter: Removes music notation and empty segments

4. Summary Generation

  • DeepSRT Integration: Direct API calls to worker.deepsrt.com
  • Multi-language Support: Supports zh-tw, en, ja, and other languages
  • Mode Selection: Narrative and bullet-point summary formats
  • Title Translation: Automatic title translation to target language

Key Features

No Pre-caching Required

  • Works immediately for any YouTube video with captions
  • Real-time transcript extraction and processing
  • No dependency on external caching systems

Intelligent Caption Selection

  • Priority Order: Manual > Auto-generated > Any available
  • Language Preference: Respects user's preferred language
  • Fallback Strategy: Graceful degradation to available options

Robust Error Handling

  • Network timeout management (30-second timeout)
  • API error translation to user-friendly messages
  • Graceful handling of videos without captions
  • Comprehensive validation of input parameters

Multi-format Output

  • Markdown Formatting: Rich text with headers and metadata
  • Structured Data: Video information, duration, author details
  • Timestamped Transcripts: Precise timing information
  • Localized Summaries: Content in user's preferred language

Performance Characteristics

  • Fast Startup: < 1 second server initialization
  • Efficient Processing: Parallel API calls for summary + title translation
  • Memory Efficient: Streaming XML parsing, no large data buffering
  • Network Optimized: Single request per video for metadata + captions

Recent Updates

v0.1.9 (Latest)

  • ✅ Fixed critical test logic flaws: Tests now correctly validate API responses instead of checking non-existent success properties
  • ✅ Enhanced error handling: Improved graceful handling of YouTube API rate limiting (HTTP 429)
  • ✅ Robust test suite: All 56 tests now pass consistently with proper error resilience
  • ✅ Verified API integration: Confirmed both DeepSRT and YouTube APIs work correctly when not rate limited
  • ✅ Multi-language support: Validated zh-tw, en, ja summary generation
  • ✅ Production-ready: Test suite handles real-world API limitations professionally

v0.1.3

  • ✅ Fixed CLI argument parsing: Now supports both --key=value and --key value formats
  • ✅ Fixed bullet mode: --mode bullet now works correctly and generates bullet-point summaries
  • ✅ Improved bunx compatibility: Direct execution with bunx @deepsrt/deepsrt-mcp works without installation

v0.1.2

  • ✅ Fixed CLI execution: Made CLI the default binary for direct npx/bunx execution
  • ✅ Updated package configuration: Proper binary resolution for different execution methods

v0.1.1

  • ✅ Added comprehensive testing: Unit tests, integration tests, and end-to-end tests
  • ✅ Enhanced CLI tool: Full-featured command-line interface with help and examples
  • ✅ Direct transcript extraction: No pre-caching required, works with any YouTube video

Features

  • Generate summaries for YouTube videos
  • Extract full transcripts with timestamps from YouTube videos
  • Support for both narrative and bullet-point summary modes
  • Multi-language support (default: zh-tw)
  • Direct YouTube caption access (no API key required)
  • Seamless integration with MCP-enabled environments

How it Works

Summary Generation

  1. Direct YouTube Integration

    • Extracts video information and captions directly from YouTube using the InnerTube API
    • Fetches transcript content from YouTube's caption system
    • Sends transcript data to DeepSRT API for summarization

  2. Real-time Processing

    • No pre-caching required - works immediately for any video with captions
    • Automatically selects the best available captions (manual preferred over auto-generated)
    • Supports multiple languages and summary modes

Transcript Extraction

  1. Direct YouTube Access

    • Transcripts are extracted directly from YouTube's caption system using the InnerTube API
    • No pre-caching required - works immediately for any video with captions

  2. Caption Selection

    • Automatically selects the best available captions (manual captions preferred over auto-generated)
    • Supports language preference selection
    • Falls back gracefully to available alternatives

  3. Timestamp Formatting

    • Provides clean, formatted transcripts with timestamps in [MM:SS] format
    • Handles both manual and auto-generated captions
    • Includes video metadata and caption information
%%{init: {'theme': 'dark', 'themeVariables': { 'primaryColor': '#2496ED', 'secondaryColor': '#38B2AC', 'tertiaryColor': '#1F2937', 'mainBkg': '#111827', 'textColor': '#E5E7EB', 'lineColor': '#4B5563', 'noteTextColor': '#E5E7EB'}}}%%
sequenceDiagram
    participant User
    participant MCP as MCP Client
    participant YouTube as YouTube API
    participant DeepSRT as DeepSRT API

    Note over User,DeepSRT: Summary Generation Flow (Direct Processing)
    User->>MCP: Request video summary
    MCP->>YouTube: Get video info & captions via InnerTube API
    YouTube-->>MCP: Return video details & caption tracks
    MCP->>YouTube: Fetch transcript XML from caption URL
    YouTube-->>MCP: Return raw transcript content
    MCP->>DeepSRT: Send transcript + metadata for summarization
    DeepSRT-->>MCP: Return generated summary
    MCP-->>User: Return formatted summary

    Note over User,DeepSRT: Transcript Extraction Flow (Direct)
    User->>MCP: Request video transcript
    MCP->>YouTube: Get video info & captions via InnerTube API
    YouTube-->>MCP: Return video details & caption tracks
    MCP->>YouTube: Fetch transcript XML from caption URL
    YouTube-->>MCP: Return raw transcript content
    MCP->>MCP: Parse & format transcript with timestamps
    MCP-->>User: Return formatted transcript with metadata

Transcript

[00:18] ♪ We're no strangers to love ♪ [00:22] ♪ You know the rules and so do I ♪ [00:27] ♪ A full commitment's what I'm thinking of ♪ ...


#### Summary Output (Narrative Mode)

瑞克·艾斯利 - 永遠不會放棄你

Author: Rick Astley
Duration: 3:33
Language: zh-tw
Mode: narrative

Summary

這是一首經典的流行歌曲，表達了對愛情的承諾和忠誠...


#### Summary Output (Bullet Mode)

How Robots Are Helping Amazon Deliver on Prime Day

Author: Bloomberg Television
Duration: 5:45
Language: zh-tw
Mode: bullet

Summary

本影片主要探討亞馬遜如何運用機器人技術來提升倉儲效率...

機器人技術在亞馬遜倉儲的應用與效益

  • 亞馬遜已部署了第一百萬個機器人，並在Prime Day等高峰期用於滿足訂單需求 [00:00:00]
  • 機器人旨在為員工提供安全且高生產力的工作環境 [00:00:30]
  • 移動機器人可以搬運超過一千磅的貨物，並移動貨架以減少員工的行走距離 [00:00:54] ...

## Development

Install dependencies:
```bash
npm install

Running Tests

# Run unit tests (fast, no network calls)
npm test

# Run unit tests only
npm run test:unit

# Run network tests (requires internet, may be slower)
npm run test:network

# Run all tests including network tests
npm run test:all

# Run tests in watch mode
npm run test:watch

# Run tests with CI reporter (for CI/CD)
npm run test:ci

Test Types:

  • Unit Tests (src/index.test.ts, src/integration.test.ts) - Fast tests with mocked data
  • Network Tests (src/transcript.test.ts, src/e2e.test.ts) - Real YouTube API integration tests

Examples

See the examples/ directory for reference implementations:

  • examples/standalone-summarizer.ts - Standalone script showing direct API usage patterns

Running the Server

With Bun (Recommended for development - faster startup):

# Development mode (runs TypeScript directly)
npm run dev
# or
bun src/index.ts

# Using npm script
npm run start:bun

With Node.js (Production):

# Build first
npm run build

# Then run
npm run start:node
# or
node build/index.js

Testing the Server

You can test the server using the MCP inspector:

npm run inspector

Or test manually with JSON-RPC:

# List available tools
echo '{"jsonrpc": "2.0", "id": 1, "method": "tools/list"}' | bun src/index.ts

# Test get_transcript
echo '{"jsonrpc": "2.0", "id": 1, "method": "tools/call", "params": {"name": "get_transcript", "arguments": {"videoId": "dQw4w9WgXcQ", "lang": "en"}}}' | bun src/index.ts

Build for Production

Build for production:

npm run build

Watch mode for development:

npm run watch

Demo