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GrokMCP

by AceDataCloud
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Python
Hybrid

GrokMCP

PyPI version Python License: MIT

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

Related MCP server: Grok MCP

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_id quickly. Poll with grok_get_task(task_id) until the state is succeeded and the video_url is available.

  • Generation typically takes ~30 seconds to a few minutes.

  • Keep resolution at 480p and duration short for faster, cheaper iterations.

Development

pip install -e ".[dev,test]"
pytest --cov=core --cov=tools
ruff check .

License

MIT — see LICENSE.

Install Server
A
license - permissive license
A
quality
B
maintenance

How are these scores calculated?

Maintenance

–Maintainers
–Response time
–Release cycle
1Releases (12mo)
Commit activity

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