GrokMCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| LOG_LEVEL | No | Logging level | INFO |
| MCP_TRANSPORT | No | Transport mode (stdio or http) | stdio |
| MCP_SERVER_NAME | No | MCP server name | grok |
| GROK_DEFAULT_MODEL | No | Default model for video generation | grok-imagine-video |
| GROK_REQUEST_TIMEOUT | No | Request timeout in seconds | 180 |
| ACEDATACLOUD_API_TOKEN | Yes | API token (required) - get one at https://platform.acedata.cloud | |
| ACEDATACLOUD_API_BASE_URL | No | API base URL | https://api.acedata.cloud |
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 |
|---|---|
| grok_chat_completionsA | Create a Grok (xAI) chat completion via the AceDataCloud Grok API. |
| grok_list_modelsA | List all available Grok models (chat + video) and their capabilities. |
| grok_list_actionsA | List all available Grok Imagine tools and workflows. |
| grok_get_prompt_guideA | Get guidance on writing effective prompts for Grok Imagine video generation. |
| grok_get_taskA | Query the status and result of a video generation task. |
| grok_get_tasks_batchA | Query multiple video generation tasks at once. |
| grok_text_to_videoA | Generate AI video from a text prompt using Grok Imagine. |
| grok_image_to_videoA | Generate AI video from a reference image using Grok Imagine. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| grok_video_generation_guide | Guide for choosing the right Grok Imagine tool for video generation. |
| grok_workflow_examples | Common workflow examples for Grok Imagine video generation. |
| grok_style_suggestions | Style and prompt writing suggestions for Grok Imagine. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 8 tools
The core capabilities (chat, text-to-video, image-to-video) are clearly distinct, and get_task vs get_tasks_batch is unambiguous. The only mild overlap is between grok_list_actions and grok_list_models, which both serve as informational/discovery helpers, but their outputs differ enough to be told apart.
All tools use a consistent snake_case grok_ prefix with a predictable verb_noun structure (grok_get_task, grok_list_models, grok_text_to_video). grok_chat_completions is a slight outlier with a noun-only form, but the set is broadly uniform.
Eight tools is well-scoped for a chat-plus-video-generation service, with each tool covering a distinct operation (generation, task polling, batch polling, discovery). Nothing feels redundant or padded.
The surface covers the full generation lifecycle: model/prompt discovery, text and image video generation, and single/batch task status retrieval. Minor gaps exist such as no task cancellation or deletion, but core workflows are fully supported.