MCP Kling

MCP server for Kling AI video generation

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "mcp-kling": {
      "command": "uvx",
      "args": [
        "mcp-kling"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Capabilities & Tool Schemas (8)Self-reported

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Kling.

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.

Documentation Overview

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 Reference

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):

config.json

{
  "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):

config.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):

config.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:

config.json

{
  "mcpServers": {
    "kling": {
      "url": "https://kling.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Claude Code

Claude Code supports MCP servers natively:

Terminal

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:

config.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):

config.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:

config.json

{
  "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:

config.json

{
  "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:

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):

config.json

{
  "language_models": {
    "mcp_servers": {
      "kling": {
        "url": "https://kling.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL Test

bash

# 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"}}}'

3. Or Run Locally (Alternative)

If you prefer to run the server on your own machine:

server.ts

# 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

Claude Desktop (Local)

config.json

{
  "mcpServers": {
    "kling": {
      "command": "uvx",
      "args": ["mcp-kling"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker (Self-Hosting)

Terminal

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

bash

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

bash

# 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 Tests

bash

# 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

bash

# Format code
ruff format .

# Lint code
ruff check .

Read the full README →View source on GitHub →

Related MCP Servers

View all in Multimedia Process View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

npm downloads

367

Package downloads in the last 30 days.

Last commit

27d ago

Most recent push to the default branch.

Tools exposed

Callable tools this server registers over MCP.

Directory activity

1 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about MCP Kling

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "mcp-kling": { "command": "uvx", "args": ["mcp-kling"] } }

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Technical Specs & Signals

CategoryMultimedia Process

11/13 checks healthy over the last 45d

53Quality signal: Good · 53/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools23/30

Adoption & activity7/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 5d ago via OSV.dev · mcp-kling (PyPI)

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More in 🎥 Multimedia Process →Best MCP servers for Multimedia & Media Processing →Alternatives to MCP Kling →Install in Claude Desktop Install in Cursor Install in VS Code Setup guides for all 13 MCP clients

MCP Kling

MCP server for Kling AI video generation

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "mcp-kling": {
      "command": "uvx",
      "args": [
        "mcp-kling"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Capabilities & Tool Schemas (8)Self-reported

Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Kling.

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.

Documentation Overview

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 Reference

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):

config.json

{
  "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):

config.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):

config.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:

config.json

{
  "mcpServers": {
    "kling": {
      "url": "https://kling.mcp.acedata.cloud/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_TOKEN"
      }
    }
  }
}

Claude Code

Claude Code supports MCP servers natively:

Terminal

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:

config.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):

config.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:

config.json

{
  "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:

config.json

{
  "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:

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):

config.json

{
  "language_models": {
    "mcp_servers": {
      "kling": {
        "url": "https://kling.mcp.acedata.cloud/mcp",
        "headers": {
          "Authorization": "Bearer YOUR_API_TOKEN"
        }
      }
    }
  }
}

cURL Test

bash

# 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"}}}'

3. Or Run Locally (Alternative)

If you prefer to run the server on your own machine:

server.ts

# 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

Claude Desktop (Local)

config.json

{
  "mcpServers": {
    "kling": {
      "command": "uvx",
      "args": ["mcp-kling"],
      "env": {
        "ACEDATACLOUD_API_TOKEN": "your_token_here"
      }
    }
  }
}

Docker (Self-Hosting)

Terminal

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

bash

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

bash

# 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 Tests

bash

# 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

bash

# Format code
ruff format .

# Lint code
ruff check .

Read the full README →View source on GitHub →

Related MCP Servers

View all in Multimedia Process View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

Stargazers on the source repository.

npm downloads

367

Package downloads in the last 30 days.

Last commit

27d ago

Most recent push to the default branch.

Tools exposed

Callable tools this server registers over MCP.

Directory activity

1 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about MCP Kling

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "mcp-kling": { "command": "uvx", "args": ["mcp-kling"] } }

AllMCPs Directory Badge

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Badge Style:

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Markdown (GitHub README)

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<a href="https://allmcps.com/mcp/mcp-kling"><img src="https://allmcps.com/api/badge/mcp-kling?style=directory" alt="MCP Kling on AllMCPs" /></a>

Technical Specs & Signals

CategoryMultimedia Process

11/13 checks healthy over the last 45d

53Quality signal: Good · 53/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools23/30

Adoption & activity7/15

Community engagement0/10

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 5d ago via OSV.dev · mcp-kling (PyPI)

★ Spotlight Slot

Feature Your MCP Server

Get maximum visibility for your server across our directory, search results, and detail pages.

Spotlight Your Server

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Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

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Add our SVG badge (dark/light directory styles) or embeddable widget to your site.