sanzaru

TJC-LP/sanzaru

3.3

If you are the rightful owner of sanzaru and would like to certify it and/or have it hosted online, please leave a comment on the right or send an email to dayong@mcphub.com.

Sanzaru is a stateless, lightweight MCP server that integrates OpenAI's Sora Video API, Whisper, and GPT-4o Audio APIs using the OpenAI Python SDK.

Tools
3
Resources
0
Prompts
0

sanzaru

A stateless, lightweight MCP server that wraps OpenAI's Sora Video API, Whisper, and GPT-4o Audio APIs via the OpenAI Python SDK.

Features

Video Generation (Sora)

  • Create videos with sora-2 or sora-2-pro models
  • Use reference images to guide generation
  • Remix and refine existing videos
  • Download variants (video, thumbnail, spritesheet)

Image Generation

  • Generate images with gpt-image-1.5 (recommended) or GPT-5
  • Edit and compose images with up to 16 inputs
  • Iterative refinement via Responses API
  • Automatic resizing for Sora compatibility

Audio Processing

  • Transcription: Whisper and GPT-4o models
  • Audio Chat: Interactive analysis with GPT-4o
  • Text-to-Speech: Multi-voice TTS generation
  • Processing: Format conversion, compression, file management

Note: Content guardrails are enforced by OpenAI. This server does not run local moderation.

Requirements

  • Python 3.10+
  • OPENAI_API_KEY environment variable

Feature-specific paths (set only what you need):

  • VIDEO_PATH - Enables video generation features
  • IMAGE_PATH - Enables image generation features
  • AUDIO_PATH - Enables audio processing features

Quick Start

  1. Clone the repository:

    git clone https://github.com/TJC-LP/sanzaru.git
cd sanzaru

  2. Run the setup script:

    ./setup.sh

    The script will:

    • Prompt for your OpenAI API key
    • Create directories and .env configuration
    • Install dependencies with uv sync --all-extras --dev

  3. Start using:

    claude

That's it! Claude Code will automatically connect and you can start generating videos, images, and processing audio.

Installation

Quick Install

# All features
uv add "sanzaru[all]"

# Specific features
uv add "sanzaru[audio]"  # With audio support
uv add sanzaru           # Base (video + image only)
Alternative Installation Methods

From Source

git clone https://github.com/TJC-LP/sanzaru.git
cd sanzaru
uv sync --all-extras

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "sanzaru": {
      "command": "uvx",
      "args": ["sanzaru[all]"],
      "env": {
        "OPENAI_API_KEY": "your-api-key-here",
        "VIDEO_PATH": "/absolute/path/to/videos",
        "IMAGE_PATH": "/absolute/path/to/images",
        "AUDIO_PATH": "/absolute/path/to/audio"
      }
    }
  }
}

Or from source:

{
  "mcpServers": {
    "sanzaru": {
      "command": "uv",
      "args": ["run", "--directory", "/path/to/sanzaru", "sanzaru"]
    }
  }
}

Codex MCP

# Using uvx (from PyPI)
codex mcp add sanzaru \
  --env OPENAI_API_KEY="sk-..." \
  --env VIDEO_PATH="$HOME/sanzaru-videos" \
  --env IMAGE_PATH="$HOME/sanzaru-images" \
  --env AUDIO_PATH="$HOME/sanzaru-audio" \
  -- uvx "sanzaru[all]"

# Or from source
cd /path/to/sanzaru
set -a; source .env; set +a
codex mcp add sanzaru \
  --env OPENAI_API_KEY="$OPENAI_API_KEY" \
  --env VIDEO_PATH="$VIDEO_PATH" \
  --env IMAGE_PATH="$IMAGE_PATH" \
  --env AUDIO_PATH="$AUDIO_PATH" \
  -- uv run --directory "$(pwd)" sanzaru

Manual Setup

uv venv
uv sync

# Set required environment variables
export OPENAI_API_KEY=sk-...
export VIDEO_PATH=~/videos
export IMAGE_PATH=~/images
export AUDIO_PATH=~/audio

# Run server
uv run sanzaru

Feature Auto-Detection: Features are automatically enabled based on configured paths. Set only the paths you need.

Available Tools

CategoryToolsDescription
Videocreate_video, get_video_status, download_video, list_videos, delete_video, remix_videoGenerate and manage Sora videos with optional reference images
Imagegenerate_image, edit_image, create_image, get_image_status, download_imageGenerate with gpt-image-1.5 (sync) or GPT-5 (polling)
Referencelist_reference_images, prepare_reference_imageManage and resize images for Sora compatibility
Audiotranscribe_audio, chat_with_audio, create_audio, convert_audio, compress_audio, list_audio_files, get_latest_audio, transcribe_with_enhancementTranscription, analysis, TTS, and file management

Full API documentation: See

Basic Workflows

Generate a Video

# Create video from text
video = create_video(
    prompt="A serene mountain landscape at sunrise",
    model="sora-2",
    seconds="8",
    size="1280x720"
)

# Poll for completion
status = get_video_status(video.id)

# Download when ready
download_video(video.id, filename="mountain_sunrise.mp4")

Generate with Reference Image

# 1. Generate reference image (gpt-image-1.5, synchronous)
generate_image(
    prompt="futuristic pilot in mech cockpit",
    size="1536x1024",
    filename="pilot.png"
)

# 2. Prepare for video (resize to Sora dimensions)
prepare_reference_image("pilot.png", "1280x720", resize_mode="crop")

# 3. Animate
video = create_video(
    prompt="The pilot looks up and smiles",
    size="1280x720",
    input_reference_filename="pilot_1280x720.png"
)

Audio Transcription

# List available audio files
files = list_audio_files(format="mp3")

# Transcribe
result = transcribe_audio("interview.mp3")

# Or analyze with GPT-4o
analysis = chat_with_audio(
    "meeting.mp3",
    user_prompt="Summarize key decisions and action items"
)

Documentation

  • - Complete tool documentation with parameters and examples
  • - Working with reference images and resizing
  • - Generating and editing reference images
  • - Crafting effective video prompts
  • - Audio transcription, chat, and TTS
  • - Technical details and benchmarks

Performance

Fully asynchronous architecture with proven scalability:

  • ✅ 32+ concurrent operations verified
  • ✅ 8-10x speedup for parallel tasks
  • ✅ Non-blocking I/O with aiofiles + anyio
  • ✅ Python 3.14 free-threading ready

See for technical details.

License