Grok MCP

Communauté Médias et design

Access xAI's Grok API with agentic tool calling, image generation, vision and file support.

Que pouvez-vous faire avec Grok MCP ?

  • Agentic Tool Calling: Web search, X search, code execution, and image generation with multi-step reasoning
  • Multiple Grok Models: Access to latest models such as grok-4.6, grok-4.5, grok-build-0.1 and more
  • Image and Video Generation: Create images and videos using Grok Imagine
  • Vision Capabilities: Analyze images with Grok's vision models
  • Files API: Upload, manage, and chat with documents
  • Stateful Conversations: Maintain conversation context as id across multiple requests
  • Local Chat History: Option to save persistent client side chat history as JSON files in chats/

Installation

Les étapes d'installation sont dans la documentation ci-dessous. Documentation

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. Grok-MCP
  2. Features
  3. Prerequisites
  4. Installation
  5. Configuration
  6. Available Tools
  7. License

Grok-MCP

MCP server for xAI’s Grok API with Web/X search, vision, image/video generation and file support.

Features

  • Agentic Tool Calling: Web search, X search, code execution, and image generation with multi-step reasoning
  • Multiple Grok Models: Access to latest models such as grok-4.6, grok-4.5, grok-build-0.1 and more
  • Image and Video Generation: Create images and videos using Grok Imagine
  • Vision Capabilities: Analyze images with Grok's vision models
  • Files API: Upload, manage, and chat with documents
  • Stateful Conversations: Maintain conversation context as id across multiple requests
  • Local Chat History: Option to save persistent client side chat history as JSON files in chats/

Prerequisites

Installation

  1. Clone the repository: bash git clone https://github.com/merterbak/Grok-MCP.git cd Grok-MCP
  2. Create a venv environment: bash uv venv source .venv/bin/activate # macOS/Linux or .venv\Scripts\activate on Windows
  3. Install dependencies:
uv sync

Configuration

Claude Desktop Integration

Add this to your Claude Desktop configuration file:

{
  "mcpServers": {
    "grok": {
      "command": "uv",
      "args": [
        "--directory",
        "/path/to/Grok-MCP",
        "run",
        "python",
        "main.py"
      ],
      "env": {
        "XAI_API_KEY": "your_api_key_here"
      }
    }
  }
}
Claude Code Integration

Run this command from inside the project directory:

claude mcp add grok-mcp -e XAI_API_KEY=your_api_key_here -- uv run --directory /path/to/Grok-MCP python main.py

Or if you have a .env file with your key:

 claude mcp add grok-mcp -- uv run --directory /path/to/Grok-MCP python main.py

Verify it's registered:

claude mcp list
Filesystem MCP (Optional)

Claude Desktop can't send uploaded images in the chat to an MCP tool. The easiest way to give access to files directly from your computer is official Filesystem MCP server. After setting it up you’ll be able to just write the image’s file path (such as /Users/mert/Desktop/image.png) in chat and Claude can use it with any vision chat tool.

{
  "mcpServers": {
    "filesystem": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/Users/<your-username>/Desktop",
        "/Users/<your-username>/Downloads"
      ]
    }
  }
}

For stdio:

uv run python main.py

Docker:

docker compose up --build

Mcp Inspector:

mcp dev main.py

Available Tools

Each tool has a full docstring in src/server.py with its arguments and return format. MCP client surfaces those directly, so this list is just a quick map of what's available.

Note: For using images and files, you must provide paths to chat. See Filesystem MCP (Optional) for setup.

Chat and reasoning
  • chat — standard chat completion with optional persistent history, multi-agent support, and a per request service_tier.
  • chat_with_vision — analyze local or remote images with a Grok vision model.
  • chat_with_files — chat grounded on previously uploaded documents.
  • stateful_chat — continue a server-side stored conversation via response_id.
  • retrieve_stateful_response — fetch a stored response by ID.
  • delete_stateful_response — delete a stored response by ID.
Agentic tools
  • web_search — autonomous web research with domain filters and citations.
  • x_search — autonomous search over X (Twitter) posts, with handle and date filters.
  • code_executor — solve tasks by running Python in a sandbox.
  • grok_agent — unified agent that mixes files, images, web search, X search, code execution, and server-side image generation. Generated images are written to images/.
Image and video
  • generate_image — create or edit images with Grok Imagine (multi-reference editing supported). Pass save=true to write the results to images/ instead of returning temporary URLs.
  • generate_video — text-to-video, image-to-video, or video editing with Grok Imagine.
  • extend_video — extend an existing generated video with a follow-up prompt.
Files
  • upload_file — upload a local document.
  • list_files — list uploaded files with sorting.
  • get_file — fetch file metadata by ID.
  • get_file_content — download file content as text.
  • delete_file — delete a file by ID.
Local chat history
  • list_chat_sessions — list saved sessions in chats/.
  • get_chat_history — get a session's full transcript.
  • clear_chat_history — delete a session's local history file.
Models
  • list_models — list all Grok language and image models with live pricing.

License

This project is open source and available under the MIT License.

Questions fréquentes

Qu'est-ce que Grok MCP ?

Access xAI's Grok API with agentic tool calling, image generation, vision and file support.

Comment installer Grok MCP ?

Suivez les étapes d'installation de sa documentation, affichée sur cette page et dans son dépôt.

Grok MCP est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient Grok MCP ?

Il est publié par merterbak. AI.tn le référence sans le maintenir ni le recommander.

Issu des listes communautaires awesome-mcp-servers et du dépôt GitHub du projet. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.