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io.github.AceDataCloud/mcp-grok

MCP server for Grok Imagine AI video generation

Media & ImagesPythonv2026.10.4.2

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 4.5 / Grok 4 / Grok 3 models, with image input 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

ToolDescription
grok_chat_completionsChat completion (reasoning / vision / tool calling) with Grok chat models.
grok_text_to_videoGenerate a video from a text prompt (any model except grok-imagine-video-1.5:official).
grok_image_to_videoGenerate a video from an input image (+ optional motion prompt).
grok_get_taskQuery the status/result of a single generation task.
grok_get_tasks_batchQuery the status/result of multiple tasks at once.
grok_list_modelsList available models and their capabilities.
grok_list_actionsList all tools and example workflows.
grok_get_prompt_guideTips for writing effective video prompts.

Models

Chat (grok_chat_completions)

ModelNotes
grok-4.5Default — latest flagship reasoning model
grok-4Previous flagship reasoning model
grok-3Earlier-generation model

Video

ModelText→VideoImage→VideoNotes
grok-imagine-video-1.5-fast:reverse✅✅Default. Fastest & cheapest. 6-30s, duration-banded billing.
grok-imagine-video:reverse✅✅Standard. 1-15s, billed per output second.
grok-imagine-video:official✅✅Official endpoint, higher fidelity. 1-15s, per second.
grok-imagine-video-1.5:official❌✅Official image-to-video only (requires image_url). Up to 1080p, per second.

Parameters

ParameterApplies toValues
promptbothText description (required for text-to-video)
image_urlimage-to-videoInput image URL (required for -1.5-preview)
reference_image_urlsimage-to-videoOptional list of style/content reference images
aspect_ratioboth1:1, 16:9 (default), 9:16, 4:3, 3:4, 3:2, 2:3
resolutionboth480p (default), 720p, 1080p
durationbothgrok-imagine-video-1.5-fast:reverse: 6–30s; other models: 1–15s (default 6)
callback_urlbothOptional 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

VariableDescriptionDefault
ACEDATACLOUD_API_TOKENAPI token (required)—
ACEDATACLOUD_API_BASE_URLAPI base URLhttps://api.acedata.cloud
GROK_DEFAULT_MODELDefault modelgrok-imagine-video-1.5-fast:reverse
GROK_REQUEST_TIMEOUTRequest timeout (seconds)180
MCP_SERVER_NAMEMCP server namegrok
MCP_TRANSPORTTransport mode (stdio/http)stdio
LOG_LEVELLogging levelINFO

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 .

Documentation

Documentation

License

MIT — see LICENSE.

Installation

Source-derived launch command. Check the maintainer’s required arguments and credentials before running:

bash
uvx mcp-grok

Set up in your AI client

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json
{
  "mcpServers": {
    "io-github-acedatacloud-mcp-grok": {
      "command": "uvx",
      "args": [
        "mcp-grok"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Package

mcp-grokpypi

Compatible MCP Clients

io.github.AceDataCloud/mcp-grok works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

  • Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.
  • Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.
  • VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.
  • Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.
  • Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

Learn More