anything-to-md

Anything-to-MD Skill

Convert any file to clean, LLM-ready Markdown. Supports 50+ file formats including documents, images (OCR), audio/video, and YouTube URLs.

Quick Start

# Convert single file
anything-to-md file document.pdf -o ./output

# Convert entire directory
anything-to-md dir ./my-docs ./my-mds --report

# Extract YouTube transcript
anything-to-md youtube "https://youtube.com/watch?v=xxx"

Capabilities

File Types Supported

| Category | Formats | |----------|---------| | Documents | PDF, DOCX, XLSX, PPTX, ODT, ODS, ODP | | Web | HTML, HTM, XHTML | | eBooks | EPUB, MOBI | | Data | CSV, TSV, JSON, XML | | Images | PNG, JPG, GIF, BMP, TIFF, WEBP (with OCR) | | Audio | MP3, WAV, M4A, FLAC, OGG, AAC | | Video | MP4, MKV, AVI, MOV, WEBM | | URLs | YouTube, Wikipedia, RSS feeds |

Video Intelligent Routing (NEW)

Videos are processed through a smart 4-phase pipeline:

PROBE → DECIDE → EXTRACT → FUSE

Phase 1: PROBE (< 5 seconds)

• ffprobe: Detect embedded subtitle tracks, audio streams
• Sidecar detection: Check for .srt/.vtt files
• Sample frame OCR: Extract 5 frames, run quick OCR to detect on-screen text

Phase 2: DECIDE - Choose optimal strategy

| Video Type | Strategy | Description | |------------|----------|-------------| | Has embedded subtitles | embedded_subtitle | Extract with ffmpeg, parse SRT | | Has sidecar .srt/.vtt | sidecar_subtitle | Parse external subtitle file | | Audio + on-screen text | hybrid | faster-whisper + frame OCR | | Pure audio (podcast) | audio_transcribe | faster-whisper transcription | | PPT recording / tutorial | visual_ocr | Scene detection + keyframe OCR | | Unknown / mixed | full_pipeline | Run all extraction methods |

Phase 3: EXTRACT

• Subtitles: ffmpeg extraction → SRT parsing
• Audio: faster-whisper (4x faster than OpenAI Whisper)
• Frames: PySceneDetect for scene changes + perceptual hash deduplication
• OCR: RapidOCR (PaddleOCR models + ONNX runtime)

Phase 4: FUSE

• Timeline alignment across sources
• Content deduplication (subtitle vs audio vs OCR)
• Priority: subtitle > audio > OCR for overlapping content

Key Insight: Don't OCR every frame. Scene detection reduces 1-hour video from ~108,000 frames to 50-200 keyframes.

MCP Tools Available

1. convert_file_to_markdown - Convert a single file
2. convert_directory_to_markdown - Batch convert entire directories
3. convert_youtube_to_markdown - Extract YouTube transcripts
4. get_supported_formats - List all supported formats

Usage Examples

Example 1: Convert Single File

# Using MCP tool
result = await convert_file_to_markdown(
    file_path="/path/to/document.pdf",
    output_dir="/path/to/output",
    output_name="document.md"
)

Example 2: Batch Convert Directory

# Using MCP tool
result = await convert_directory_to_markdown(
    source_dir="/path/to/documents",
    target_dir="/path/to/markdown-output",
    preserve_structure=True,
    skip_patterns=["*.tmp", "draft_*"]
)

Example 3: YouTube Transcript

# Using MCP tool
result = await convert_youtube_to_markdown(
    url="https://www.youtube.com/watch?v=dQw4w9WgXcQ",
    output_path="./transcript.md"
)

Example 4: Video with On-Screen Text

# Video intelligent routing is automatic
result = await convert_file_to_markdown(
    file_path="/path/to/tutorial.mp4",
    output_dir="/path/to/output"
)
# Output includes:
# - Audio transcription (if speech detected)
# - On-screen text via OCR (if detected)
# - Extracted keyframes saved to <video>_frames/

Output Format

The converter produces clean, structured Markdown:

# Document Title

## Section 1

Content with preserved structure...

### Subsection

- Lists are preserved
- Tables converted to Markdown tables
- Headers maintain hierarchy

| Column A | Column B |
|----------|----------|
| Data     | Data     |

Video Output Format

# Video Transcript: tutorial

## Metadata

- **Source**: `tutorial.mp4`
- **Duration**: 00:15:32
- **Strategy**: hybrid
- **Audio transcribed**: true
- **Subtitles extracted**: false
- **Frames analyzed**: 47
- **Frames with text**: 32

## Transcript

### Audio Transcription

- [00:00:01] Welcome to this tutorial on...
- [00:00:15] Let's start by opening the editor...

### On-Screen Text (OCR)

- [00:01:23] npm install anything-to-md
- [00:02:45] const converter = new AnythingToMD()

## Extracted Frames

Frames saved to: `tutorial_frames/`

Configuration

Environment Variables

• ANYTHING_TO_MD_ENABLE_PLUGINS=true - Enable MarkItDown plugins

Skip Patterns

Default patterns to skip:

• .git/, __pycache__/, node_modules/
• .venv/, venv/
• .pyc, .pyo
• .DS_Store, Thumbs.db

Add custom patterns via CLI:

anything-to-md dir ./src ./output --skip "*.test.*" --skip "temp_*"

Dependencies

Required

• markitdown - Microsoft's document converter
• pypdf - PDF fallback

PDF Enhancement

• mineru (CLI) - High-quality OCR for PDFs

Video Processing

• ffmpeg / ffprobe - Video analysis and extraction
• rapidocr-onnxruntime - OCR engine
• faster-whisper - Audio transcription
• scenedetect + opencv-python - Scene detection
• imagehash + Pillow - Frame deduplication

Integration

With Claude Code

The MCP server can be configured in Claude Code settings:

{
  "mcpServers": {
    "anything-to-md": {
      "command": "uvx",
      "args": ["anything-to-md-mcp"]
    }
  }
}

With AionUI

Add to AionUI MCP configuration:

mcp_servers:
  - name: anything-to-md
    command: python -m anything_to_md.mcp_server
    enabled: true

Troubleshooting

File not converting?

1. Check if format is supported: anything-to-md formats
2. Ensure file isn't corrupted
3. Check error message in conversion report

YouTube extraction failing?

1. Ensure yt-dlp is installed: pip install yt-dlp
2. Video may not have subtitles/transcript available
3. Check if video is age-restricted

Video OCR missing text?

1. Ensure rapidocr-onnxruntime is installed: pip install rapidocr-onnxruntime
2. For hard-coded subtitles, text may be too small
3. Try increasing scene detection sensitivity in code

Large directory taking too long?

1. Use --skip patterns to exclude unnecessary files
2. Consider processing in smaller batches