KlingMCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LOG_LEVEL | No | Logging level | INFO |
| KLING_DEFAULT_MODE | No | Default generation mode | std |
| KLING_DEFAULT_MODEL | No | Default video model | kling-v2-master |
| KLING_REQUEST_TIMEOUT | No | Request timeout in seconds | 300 |
| ACEDATACLOUD_API_TOKEN | Yes | API token from AceDataCloud | |
| ACEDATACLOUD_API_BASE_URL | No | API base URL | https://api.acedata.cloud |
| KLING_DEFAULT_ASPECT_RATIO | No | Default aspect ratio | 16:9 |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| kling_list_modelsA | List all available Kling models for video generation. |
| kling_list_actionsA | List all available Kling API actions and corresponding tools. |
| kling_lip_syncA | Synchronize lip movements in a video to match a given audio track or text. |
| kling_talking_photoA | Animate a portrait photo to match a provided audio track (talking-photo). |
| kling_generate_motionA | Transfer motion from a reference video to a character image. |
| kling_get_taskA | Query the status and result of a video generation task. |
| kling_get_tasks_batchA | Query multiple video generation tasks at once. |
| kling_generate_videoA | Generate AI video from a text prompt using Kling. |
| kling_generate_video_from_imageA | Generate AI video using reference images as start and/or end frames. |
| kling_extend_videoA | Extend an existing video with additional content. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| kling_video_generation_guide | Guide for choosing the right Kling tool for video generation. |
| kling_workflow_examples | Common workflow examples for Kling video generation. |
| kling_prompt_suggestions | Prompt writing suggestions for Kling video generation. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 10 tools
Each tool targets a distinct capability: text-to-video, image-to-video, lip sync, talking photo, motion transfer, extension, task querying, and metadata listing. The purposes are clearly separated with explicit guidance on when to use each variant, leaving no ambiguity.
All tool names follow the kling_<action>_<object> pattern consistently using snake_case. Verbs like generate, list, get, extend, and noun phrases like lip_sync and talking_photo are uniformly formatted, making naming predictable and coherent.
With 10 tools, the server covers the core video generation lifecycle and specialized features without bloat. The count is well-scoped for a focused MCP server, each tool earning its place.
The tool set covers the main workflows: generation from text/image, motion transfer, lip sync, talking photos, video extension, and task monitoring. Minor gaps exist such as no explicit cancel/delete task endpoint, but agents can work around this for typical generation scenarios.