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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.

Deploy Server
A
security – no known vulnerabilities
F
license - not found
A
quality - confirmed to work

MCP directory API

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