SRT Translation MCP Server

🚀 CHUNK-BASED TRANSLATION WORKFLOW INSTRUCTIONS 🚀

📋 OVERVIEW: This tool analyzes SRT files and creates intelligent chunks for efficient translation. It returns METADATA ONLY - use get_next_chunk() and translate_srt() for actual content.

🔍 WHAT IT DOES:

• SMART INPUT: Auto-detects file paths vs SRT content

• Creates small chunks (1-3 subtitles each) optimized for AI processing

• Detects languages (Arabic, English, Spanish, French) per chunk

• Identifies speakers and conversation boundaries

• Provides translation priority rankings (high/medium/low)

• Stores chunks in memory to avoid context limits

• Creates individual TODO tasks for tracking progress

📊 WHAT IT RETURNS (SMALL RESPONSE):

• chunkCount: Total number of chunks created

• totalDuration: File duration in milliseconds

• languageDistribution: Language counts (e.g., {"ar": 45, "en": 12})

• previewChunk: Preview of first chunk metadata only

• sessionId: For retrieving chunks later

• message: Instructions for next steps

• todos: Individual tasks for each chunk

🎯 RECOMMENDED WORKFLOW:

1. Call detect_conversations with storeInMemory=true

2. Review metadata to understand file structure (SMALL RESPONSE)

3. Use get_next_chunk to process chunks one by one

4. Use translate_srt() for actual translation

5. Track progress with todo_management

💡 EXAMPLES:

File Path Input: {"content": "/path/to/file.srt", "storeInMemory": true, "createTodos": true}

SRT Content Input: {"content": "1\n00:00:02,000 --> 00:00:07,000\nHello world", "storeInMemory": true}

⚠️ IMPORTANT:

• This returns METADATA ONLY - no actual text content

• Response is SMALL to avoid context overflow

• Use get_next_chunk() to retrieve individual chunks

• Use translate_srt() for actual translation

• Store chunks in memory for large files to avoid context limits