MCP Server for Sora AI Video Generation via AceDataCloud API
Project description
SoraMCP
A Model Context Protocol (MCP) server for AI video generation using Sora through the AceDataCloud API.
Generate AI videos directly from Claude, VS Code, or any MCP-compatible client.
Features
- Text-to-Video - Generate videos from text descriptions
- Image-to-Video - Animate images and create videos from reference images
- Character Videos - Reuse characters across different scenes
- Async Generation - Webhook callbacks for production workflows
- Multiple Orientations - Landscape and portrait videos
- Task Tracking - Monitor generation progress and retrieve results
Tool Reference
| Tool | Description |
|---|---|
sora_generate_video |
Generate an AI video from a text prompt using Sora. |
sora_generate_video_from_image |
Generate an AI video from reference images using Sora (Image-to-Video). |
sora_generate_video_with_character |
Generate an AI video featuring a character from a reference video. |
sora_generate_video_async |
Generate an AI video asynchronously with callback notification. |
sora_generate_video_v2 |
Generate an AI video using Sora Version 2 (partner channel). |
sora_generate_video_v2_async |
Generate an AI video asynchronously using Sora Version 2 with callback. |
sora_get_task |
Query the status and result of a video generation task. |
sora_get_tasks_batch |
Query multiple video generation tasks at once. |
sora_list_models |
List all available Sora models and their capabilities. |
sora_list_actions |
List all available Sora API actions and corresponding tools. |
Quick Start
1. Get Your API Token
- Sign up at AceDataCloud Platform
- Go to the API documentation page
- Click "Acquire" to get your API token
- Copy the token for use below
2. Use the Hosted Server (Recommended)
AceDataCloud hosts a managed MCP server — no local installation required.
Endpoint: https://sora.mcp.acedata.cloud/mcp
All requests require a Bearer token. Use the API token from Step 1.
Claude.ai
Connect directly on Claude.ai with OAuth — no API token needed:
- Go to Claude.ai Settings → Integrations → Add More
- Enter the server URL:
https://sora.mcp.acedata.cloud/mcp - Complete the OAuth login flow
- Start using the tools in your conversation
Claude Desktop
Add to your config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS):
{
"mcpServers": {
"sora": {
"type": "streamable-http",
"url": "https://sora.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Cursor / Windsurf
Add to your MCP config (.cursor/mcp.json or .windsurf/mcp.json):
{
"mcpServers": {
"sora": {
"type": "streamable-http",
"url": "https://sora.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
VS Code (Copilot)
Add to your VS Code MCP config (.vscode/mcp.json):
{
"servers": {
"sora": {
"type": "streamable-http",
"url": "https://sora.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Or install the Ace Data Cloud MCP extension for VS Code, which bundles all 11 MCP servers with one-click setup.
JetBrains IDEs
- Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
- Click Add → HTTP
- Paste:
{
"mcpServers": {
"sora": {
"url": "https://sora.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Claude Code
Claude Code supports MCP servers natively:
claude mcp add sora --transport http https://sora.mcp.acedata.cloud/mcp \
-h "Authorization: Bearer YOUR_API_TOKEN"
Or add to your project's .mcp.json:
{
"mcpServers": {
"sora": {
"type": "streamable-http",
"url": "https://sora.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Cline
Add to Cline's MCP settings (.cline/mcp_settings.json):
{
"mcpServers": {
"sora": {
"type": "streamable-http",
"url": "https://sora.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Amazon Q Developer
Add to your MCP configuration:
{
"mcpServers": {
"sora": {
"type": "streamable-http",
"url": "https://sora.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Roo Code
Add to Roo Code MCP settings:
{
"mcpServers": {
"sora": {
"type": "streamable-http",
"url": "https://sora.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Continue.dev
Add to .continue/config.yaml:
mcpServers:
- name: sora
type: streamable-http
url: https://sora.mcp.acedata.cloud/mcp
headers:
Authorization: "Bearer YOUR_API_TOKEN"
Zed
Add to Zed's settings (~/.config/zed/settings.json):
{
"language_models": {
"mcp_servers": {
"sora": {
"url": "https://sora.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
}
cURL Test
# Health check (no auth required)
curl https://sora.mcp.acedata.cloud/health
# MCP initialize
curl -X POST https://sora.mcp.acedata.cloud/mcp \
-H "Content-Type: application/json" \
-H "Accept: application/json" \
-H "Authorization: Bearer YOUR_API_TOKEN" \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-03-26","capabilities":{},"clientInfo":{"name":"test","version":"1.0"}}}'
3. Or Run Locally (Alternative)
If you prefer to run the server on your own machine:
# Install from PyPI
pip install mcp-sora
# or
uvx mcp-sora
# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"
# Run (stdio mode for Claude Desktop / local clients)
mcp-sora
# Run (HTTP mode for remote access)
mcp-sora --transport http --port 8000
Claude Desktop (Local)
{
"mcpServers": {
"sora": {
"command": "uvx",
"args": ["mcp-sora"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_token_here"
}
}
}
}
Docker (Self-Hosting)
docker pull ghcr.io/acedatacloud/mcp-sora:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-sora:latest
Clients connect with their own Bearer token — the server extracts the token from each request's Authorization header.
Available Tools
Video Generation
| Tool | Description |
|---|---|
sora_generate_video |
Generate video from a text prompt |
sora_generate_video_from_image |
Generate video from reference images |
sora_generate_video_with_character |
Generate video with a character from reference video |
sora_generate_video_async |
Generate video with callback notification |
Tasks
| Tool | Description |
|---|---|
sora_get_task |
Query a single task status |
sora_get_tasks_batch |
Query multiple tasks at once |
Information
| Tool | Description |
|---|---|
sora_list_models |
List available Sora models |
sora_list_actions |
List available API actions |
Usage Examples
Generate Video from Prompt
User: Create a video of a sunset over mountains
Claude: I'll generate a sunset video for you.
[Calls sora_generate_video with prompt="A beautiful sunset over mountains..."]
Generate from Image
User: Animate this image of a city skyline
Claude: I'll bring this image to life.
[Calls sora_generate_video_from_image with image_urls and prompt]
Character-based Video
User: Use the robot character in a new scene
Claude: I'll create a new scene with the robot character.
[Calls sora_generate_video_with_character with character_url and prompt]
Available Models
| Model | Max Duration | Quality | Features |
|---|---|---|---|
sora-2 |
15 seconds | Good | Standard generation |
sora-2-pro |
25 seconds | Best | Higher quality, longer videos |
Video Options
Size:
small- Lower resolution, faster generationlarge- Higher resolution (recommended)
Orientation:
landscape- 16:9 (YouTube, presentations)portrait- 9:16 (TikTok, Instagram Stories)
Duration:
10seconds - All models15seconds - All models25seconds - sora-2-pro only
Configuration
Environment Variables
| Variable | Description | Default |
|---|---|---|
ACEDATACLOUD_API_TOKEN |
API token from AceDataCloud | Required |
ACEDATACLOUD_API_BASE_URL |
API base URL | https://api.acedata.cloud |
ACEDATACLOUD_OAUTH_CLIENT_ID |
OAuth client ID (hosted mode) | — |
ACEDATACLOUD_PLATFORM_BASE_URL |
Platform base URL | https://platform.acedata.cloud |
SORA_DEFAULT_MODEL |
Default model | sora-2 |
SORA_DEFAULT_SIZE |
Default video size | large |
SORA_DEFAULT_DURATION |
Default duration (seconds) | 15 |
SORA_DEFAULT_ORIENTATION |
Default orientation | landscape |
SORA_REQUEST_TIMEOUT |
Request timeout (seconds) | 3600 |
LOG_LEVEL |
Logging level | INFO |
Command Line Options
mcp-sora --help
Options:
--version Show version
--transport Transport mode: stdio (default) or http
--port Port for HTTP transport (default: 8000)
Development
Setup Development Environment
# Clone repository
git clone https://github.com/AceDataCloud/SoraMCP.git
cd SoraMCP
# Create virtual environment
python -m venv .venv
source .venv/bin/activate # or `.venv\Scripts\activate` on Windows
# Install with dev dependencies
pip install -e ".[dev,test]"
Run Tests
# Run unit tests
pytest
# Run with coverage
pytest --cov=core --cov=tools
# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration
Code Quality
# Format code
ruff format .
# Lint code
ruff check .
# Type check
mypy core tools
Build & Publish
# Install build dependencies
pip install -e ".[release]"
# Build package
python -m build
# Upload to PyPI
twine upload dist/*
Project Structure
SoraMCP/
├── core/ # Core modules
│ ├── __init__.py
│ ├── client.py # HTTP client for Sora API
│ ├── config.py # Configuration management
│ ├── exceptions.py # Custom exceptions
│ ├── server.py # MCP server initialization
│ ├── types.py # Type definitions
│ └── utils.py # Utility functions
├── tools/ # MCP tool definitions
│ ├── __init__.py
│ ├── video_tools.py # Video generation tools
│ ├── task_tools.py # Task query tools
│ └── info_tools.py # Information tools
├── prompts/ # MCP prompt templates
│ └── __init__.py
├── tests/ # Test suite
│ ├── conftest.py
│ ├── test_client.py
│ ├── test_config.py
│ ├── test_integration.py
│ └── test_utils.py
├── deploy/ # Deployment configs
│ └── production/
│ ├── deployment.yaml
│ ├── ingress.yaml
│ └── service.yaml
├── .env.example # Environment template
├── .gitignore
├── CHANGELOG.md
├── Dockerfile # Docker image for HTTP mode
├── docker-compose.yaml # Docker Compose config
├── LICENSE
├── main.py # Entry point
├── pyproject.toml # Project configuration
└── README.md
API Reference
This server wraps the AceDataCloud Sora API:
- Sora Videos API - Video generation
- Sora Tasks API - Task queries
Contributing
Contributions are welcome! Please:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing) - Open a Pull Request
License
MIT License - see LICENSE for details.
Links
Made with love by AceDataCloud
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