# 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

```bash
# Install dependencies
npm install

# Build the project
npm run build

# Run tests
npm test
```

## Usage

### As an MCP Server

```bash
# 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

```typescript
// 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

```bash
# 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:
```bash
npm test
```

## License

MIT License - see LICENSE file for details.