MCP server for Kling AI video generation
Remote endpoints: streamable-http: https://kling.mcp.acedata.cloud/mcp
Valid MCP server (2 strong, 2 medium validity signals). 4 known CVEs in dependencies (0 critical, 3 high severity) Package registry verified. Imported from the Official MCP Registry.
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Set these up before or after installing:
Environment variable: ACEDATACLOUD_API_TOKEN
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
From the project's GitHub README.
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.
| 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. |
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.
Connect directly on Claude.ai with OAuth — no API token needed:
https://kling.mcp.acedata.cloud/mcpAdd 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"
}
}
}
}
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"
}
}
}
}
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 bundles all MCP servers with one-click setup.
{
"mcpServers": {
"kling": {
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
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"
}
}
}
}
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"
}
}
}
}
Add to your MCP configuration:
{
"mcpServers": {
"kling": {
"type": "streamable-http",
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Add to Roo Code MCP settings:
{
"mcpServers": {
"kling": {
"type": "streamable-http",
"url": "https://kling.mcp.acedata.cloud/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_TOKEN"
}
}
}
}
Add to .continue/config.yaml:
mcpServers:
- name: kling
type: streamable-http
url: https://kling.mcp.acedata.cloud/mcp
headers:
Authorization: "Bearer YOUR_API_TOKEN"
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"
}
}
}
}
}
# Health check (no auth required)
curl https://kling.mcp.acedata.cloud/health
# MCP initialize
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"}}}'
If you prefer to run the server on your own machine:
# Install from PyPI
pip install mcp-kling
# or
uvx mcp-kling
# Set your API token
export ACEDATACLOUD_API_TOKEN="your_token_here"
# Run (stdio mode for Claude Desktop / local clients)
mcp-kling
# Run (HTTP mode for remote access)
mcp-kling --transport http --port 8000
{
"mcpServers": {
"kling": {
"command": "uvx",
"args": ["mcp-kling"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_token_here"
}
}
}
}
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.
| 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-video-o1 | Video O1 | Advanced reasoning-based generation |
| 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 |
mcp-kling --help
Options:
--version Show version
--transport Transport mode: stdio (default) or http
--port Port for HTTP transport (default: 8000)
# Clone repository
git clone https://github.com/AceDataCloud/KlingMCP.git
cd KlingMCP
# 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 unit tests
pytest
# Run with coverage
pytest --cov=core --cov=tools
# Run integration tests (requires API token)
pytest tests/test_integration.py -m integration
# Format code
ruff format .
# Lint code
ruff check .
# Type check
mypy core tools
# Install build dependencies
pip install -e ".[release]"
# Build package
python -m build
# Upload to PyPI
twine upload dist/*
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
This server wraps the AceDataCloud Kling API:
Contributions are welcome! Please:
git checkout -b feature/amazing)git commit -m 'Add amazing feature')git push origin feature/amazing)MIT License - see LICENSE for details.
Made with love by AceDataCloud
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