GrokMCP
An MCP server for Grok (xAI) that enables chat, reasoning, vision, and video generation using the AceDataCloud API.
README
GrokMCP
A Model Context Protocol (MCP) server for Grok (xAI) — chat/reasoning/vision and Grok Imagine video generation, powered by the AceDataCloud API.
Chat with Grok models, or generate short AI videos from a text prompt or a still image — directly from any MCP-compatible client (Claude Desktop, Claude Code, Cursor, etc.).
Features
- Chat / Reasoning / Vision — Talk to Grok 4 / Grok 3 family models, including vision (
grok-2-vision) and tool calling - Text to Video — Generate a video clip from a text description
- Image to Video — Animate a reference image into a video
- Async task tracking — Submit a job, poll for the result, single or batch
- stdio & HTTP transports — Local stdio for desktop clients, HTTP for remote hosting
Tools
| Tool | Description |
|---|---|
grok_chat_completions |
Chat completion (reasoning / vision / tool calling) with Grok chat models. |
grok_text_to_video |
Generate a video from a text prompt (model grok-imagine-video). |
grok_image_to_video |
Generate a video from an input image (+ optional motion prompt). |
grok_get_task |
Query the status/result of a single generation task. |
grok_get_tasks_batch |
Query the status/result of multiple tasks at once. |
grok_list_models |
List available models and their capabilities. |
grok_list_actions |
List all tools and example workflows. |
grok_get_prompt_guide |
Tips for writing effective video prompts. |
Models
Chat (grok_chat_completions)
| Model | Notes |
|---|---|
grok-4 |
Flagship reasoning model |
grok-4-1-fast |
Default — fast, capable |
grok-4-1-fast-non-reasoning |
Fast, no reasoning trace |
grok-3 |
Previous-gen flagship |
grok-3-mini |
Smaller/cheaper; supports reasoning_effort |
grok-2-vision |
Vision-capable (image understanding) |
Video
| Model | Text→Video | Image→Video | Notes |
|---|---|---|---|
grok-imagine-video |
✅ | ✅ | Default. Lower price. Up to 30s, duration-banded billing. |
grok-imagine-video-1.5-preview |
❌ | ✅ | Image-to-video only (requires image_url). Up to 15s, billed per second. |
Parameters
| Parameter | Applies to | Values |
|---|---|---|
prompt |
both | Text description (required for text-to-video) |
image_url |
image-to-video | Input image URL (required for -1.5-preview) |
reference_image_urls |
image-to-video | Optional list of style/content reference images |
aspect_ratio |
both | 1:1, 16:9 (default), 9:16, 4:3, 3:4, 3:2, 2:3 |
resolution |
both | 480p (default), 720p, 1080p |
duration |
both | grok-imagine-video: 1–30s; grok-imagine-video-1.5-preview: 1–15s (default 8) |
callback_url |
both | Optional async webhook |
Installation
Via uvx (recommended)
uvx mcp-grok
Via pip
pip install mcp-grok
mcp-grok
Configuration
Set your AceDataCloud API token (get one at https://platform.acedata.cloud):
export ACEDATACLOUD_API_TOKEN=your_api_token_here
Claude Desktop / Claude Code
Add to your MCP config (claude_desktop_config.json or .mcp.json):
{
"mcpServers": {
"grok": {
"command": "uvx",
"args": ["mcp-grok"],
"env": {
"ACEDATACLOUD_API_TOKEN": "your_api_token_here"
}
}
}
}
Remote (HTTP)
A hosted Streamable HTTP endpoint is available at:
https://grok.mcp.acedata.cloud/mcp
Environment Variables
| Variable | Description | Default |
|---|---|---|
ACEDATACLOUD_API_TOKEN |
API token (required) | — |
ACEDATACLOUD_API_BASE_URL |
API base URL | https://api.acedata.cloud |
GROK_DEFAULT_MODEL |
Default model | grok-imagine-video |
GROK_REQUEST_TIMEOUT |
Request timeout (seconds) | 180 |
MCP_SERVER_NAME |
MCP server name | grok |
MCP_TRANSPORT |
Transport mode (stdio/http) |
stdio |
LOG_LEVEL |
Logging level | INFO |
Usage Notes
- Generation is asynchronous: the generation tools return a
task_idquickly. Poll withgrok_get_task(task_id)until the state issucceededand thevideo_urlis available. - Generation typically takes ~30 seconds to a few minutes.
- Keep
resolutionat480panddurationshort for faster, cheaper iterations.
Development
pip install -e ".[dev,test]"
pytest --cov=core --cov=tools
ruff check .
License
MIT — see LICENSE.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases