SRT Translation MCP Server

A Model Context Protocol (MCP) server for processing and translating SRT subtitle files with intelligent conversation detection and context preservation.

Features

• SRT File Processing: Parse, validate, and manipulate SRT subtitle files
• Large File Support: Intelligent chunking for processing large SRT files
• Conversation Detection: Context-aware analysis for better translation quality
• Style Tag Preservation: Maintain HTML-style formatting during translation
• Timing Synchronization: Preserve precise timing information
• MCP Integration: Standardized interface for AI assistant integration

Installation

# Install dependencies
npm install

# Build the project
npm run build

# Run tests
npm test

Usage

As an MCP Server

# Start the MCP server
npm start

# Or run directly with npx
npx srt-translation-mcp-server

Available MCP Tools

• parse_srt: Parse and validate SRT file content
• write_srt: Write SRT file from parsed data
• detect_conversations: Detect conversation boundaries in SRT content
• translate_srt: Translate SRT content with context preservation
• translate_chunk: Translate a specific chunk of SRT content

Example Usage

// Parse SRT file
const result = await mcpClient.callTool('parse_srt', {
  content: srtFileContent
});

// Detect conversations
const conversations = await mcpClient.callTool('detect_conversations', {
  content: srtFileContent
});

// Translate SRT file
const translated = await mcpClient.callTool('translate_srt', {
  content: srtFileContent,
  targetLanguage: 'es',
  preserveFormatting: true
});

Development

# Development mode with hot reload
npm run dev

# Run tests in watch mode
npm run test:watch

# Lint code
npm run lint

# Fix linting issues
npm run lint:fix

Architecture

Core Components

• SRT Parser: Handles SRT file parsing and validation
• Time Parser: Manages SRT time format operations
• Style Tags: Preserves HTML-style formatting
• Conversation Detector: Identifies conversation boundaries
• Translation Service: Context-aware translation processing
• MCP Server: Protocol implementation for AI integration

Key Features

1. Intelligent Chunking: Breaks large files at natural conversation boundaries
2. Context Preservation: Maintains conversation context for better translations
3. Style Tag Support: Preserves HTML formatting during translation
4. Timing Validation: Ensures timing sequences are valid and ascending
5. Error Handling: Comprehensive error reporting and validation

Testing

The project includes comprehensive tests for all core functionality:

• Time parsing and formatting
• SRT file parsing and validation
• Style tag detection and preservation
• Conversation detection algorithms
• Translation workflow integration

Run tests with:

npm test

License

MIT License - see LICENSE file for details.