KlingMCP
A Model Context Protocol (MCP) server for AI video generation using Kling through the AceDataCloud API.
Generate AI videos, extend clips, and transfer motion directly from Claude, VS Code, or any MCP-compatible client.
Features
- Text to Video - Create AI-generated videos from text prompts
- Image to Video - Generate videos using reference start/end images
- Video Extension - Extend existing videos with additional content
- Motion Transfer - Transfer motion from a reference video to a character image
- Multiple Models - Support for 9 Kling models, including V3, V3 Omni, and canonical Kling O1
- Camera Control - Fine-grained camera movement control
- Task Tracking - Monitor generation progress and retrieve results
| Tool | Description |
|---|
kling_generate_video | Generate AI video from a text prompt using Kling. |
kling_generate_video_from_image | Generate AI video using reference images as start and/or end frames. |
kling_extend_video | Extend an existing video with additional content. |
kling_generate_motion | Transfer motion from a reference video to a character image. |
kling_get_task | Query the status and result of a video generation task. |
kling_get_tasks_batch | Query multiple video generation tasks at once. |
kling_list_models | List all available Kling models for video generation. |
kling_list_actions | List all available Kling 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://kling.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://kling.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": {
"kling": {
"type": "streamable-http",
"url": "https://kling.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": {
"kling": {
"type": "streamable-http",
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
VS Code (Copilot)
Add to your VS Code MCP config (.vscode/mcp.json):
{
"servers": {
"kling": {
"type": "streamable-http",
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Or install the Ace Data Cloud MCP extension for VS Code, which registers the hosted MCP servers with one-click setup.
JetBrains IDEs
- Go to Settings → Tools → AI Assistant → Model Context Protocol (MCP)
- Click Add → HTTP
- Paste:
{
"mcpServers": {
"kling": {
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Claude Code
Claude Code supports MCP servers natively:
claude mcp add kling --transport http https://kling.mcp.acedata.cloud/mcp \
-h "Authorization: Bearer YOUR_API_TOKEN"
Or add to your project's .mcp.json:
{
"mcpServers": {
"kling": {
"type": "streamable-http",
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Cline
Add to Cline's MCP settings (.cline/mcp_settings.json):
{
"mcpServers": {
"kling": {
"type": "streamable-http",
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Amazon Q Developer
Add to your MCP configuration:
{
"mcpServers": {
"kling": {
"type": "streamable-http",
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Roo Code
Add to Roo Code MCP settings:
{
"mcpServers": {
"kling": {
"type": "streamable-http",
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Continue.dev
Add to .continue/config.yaml:
mcpServers:
- name: kling
type: streamable-http
url: https://kling.mcp.acedata.cloud/mcp
headers:
Authorization: "Bearer YOUR_API_TOKEN"
Zed
Add to Zed's settings (~/.config/zed/settings.json):
{
"language_models": {
"mcp_servers": {
"kling": {
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
}
cURL Test
curl https://kling.mcp.acedata.cloud/health
curl -X POST https://kling.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:
pip install mcp-kling
uvx mcp-kling
export ACEDATACLOUD_API_TOKEN="your_token_here"
mcp-kling
mcp-kling --transport http --port 8000
Claude Desktop (Local)
{
"mcpServers": {
"kling": {
"command": "uvx",
"args": ["mcp-kling"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_token_here"
}
}
}
}
Docker (Self-Hosting)
docker pull ghcr.io/acedatacloud/mcp-kling:latest
docker run -p 8000:8000 ghcr.io/acedatacloud/mcp-kling:latest
Clients connect with their own Bearer token — the server extracts the token from each request's Authorization header.
Available Models
| Model | Description | Use Case |
|---|
kling-v1 | First generation | Basic video generation |
kling-v1-6 | V1 extended | Improved quality over v1 |
kling-v2-master | V2 master (default) | High-quality, balanced performance |
kling-v2-1-master | V2.1 master | Enhanced quality and consistency |
kling-v2-5-turbo | V2.5 turbo | Faster generation, good quality |
kling-o1 | Kling O1 | Omni image/video reference generation |
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 |
KLING_DEFAULT_MODEL | Default video model | kling-v2-master |
KLING_DEFAULT_MODE | Default generation mode | std |
KLING_DEFAULT_ASPECT_RATIO | Default aspect ratio | 16:9 |
KLING_REQUEST_TIMEOUT | Request timeout in seconds | 300 |
LOG_LEVEL | Logging level | INFO |
Command Line Options
mcp-kling --help
Options:
--version Show version
--transport Transport mode: stdio (default) or http
--port Port for HTTP transport (default: 8000)
Development
Setup Development Environment
git clone https://github.com/AceDataCloud/KlingMCP.git
cd KlingMCP
python -m venv .venv
source .venv/bin/activate
pip install -e ".[dev,test]"
Run Tests
pytest
pytest --cov=core --cov=tools
pytest tests/test_integration.py -m integration
Code Quality
ruff format .
ruff check .
mypy core tools
Build & Publish
pip install -e ".[release]"
python -m build
twine upload dist/*
Project Structure
KlingMCP/
├── core/ # Core modules
│ ├── __init__.py
│ ├── client.py # HTTP client for Kling API
│ ├── config.py # Configuration management
│ ├── exceptions.py # Custom exceptions
│ ├── oauth.py # OAuth 2.1 provider
│ ├── 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
│ ├── motion_tools.py # Motion transfer tools
│ ├── task_tools.py # Task query tools
│ └── info_tools.py # Information tools
├── prompts/ # MCP prompts
│ └── __init__.py # Prompt templates
├── tests/ # Test suite
│ ├── conftest.py
│ └── __init__.py
├── deploy/ # Deployment configs
│ └── production/
│ ├── deployment.yaml
│ ├── ingress.yaml
│ └── service.yaml
├── .env.example # Environment template
├── 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 Kling API:
- Kling Videos API - Video generation (text2video, image2video, extend)
- Kling Motion API - Motion transfer
- Kling 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
Documentation
Documentation
License
MIT License - see LICENSE for details.
Links
Made with love by AceDataCloud
Turbo, storyboards and commerce
Use kling_generate_turbo_video for V3 Turbo (std 720p / pro 1080p, integer 3–15 seconds). Native audio is included and cannot be disabled. Tail frames, standalone negative prompts, cfg_scale, camera controls and Omni references are unsupported.
Use kling_generate_storyboard for V3/V3 Omni multishot generation: shot_type="intelligence" uses a prompt; customize takes 1–6 indexed multi_prompt shots whose durations sum to the total. For example: {"shot_type":"customize","duration":5,"multi_prompt":[{"index":1,"prompt":"Ocean","duration":2},{"index":2,"prompt":"Beach","duration":3}]}.
Commerce tools are kling_apparel_video, kling_goods_studio, kling_video_commerce and kling_virtual_try_on. Each takes a structured request with contents and typed settings. Product studio needs ref_image and goods_title, with duration 15/30/60. Try-on needs one product_image and one person_image URL. Creator video needs exactly one avatar and a speech_script. These tools return asynchronous task IDs by default; use kling_get_task, or set async=false in the request. Billing uses the selected resolution/content tier and actual output duration or image count.
Owned assets
Use kling_manage_elements to list verified presets or manage previously owned platform IDs. Custom element creation is unavailable while pricing is pending. kling_manage_voices additionally accepts action="create", voice_name and a 5–30 second voice_url; creation costs 0.07 Credits.
kling_generate_with_assets accepts either element_list for V3/V3 Omni/O1 or voice_list for V2.6 pro with generate_audio=true. Voice prompts use <<<voice_1>>>/<<<voice_2>>> and specified voices cost 1.68 Credits/second. All IDs are platform IDs; the server checks user/application ownership. Presets cannot be deleted. Poll asynchronous voice creation and video tasks using kling_get_task.