Grok MCP
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.
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
- Python 3.11 or higher
- xAI API key (Get one here)
- Astral UV
Installation
- Clone the repository:
bash git clone https://github.com/merterbak/Grok-MCP.git cd Grok-MCP - Create a venv environment:
bash uv venv source .venv/bin/activate # macOS/Linux or .venv\Scripts\activate on Windows - 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 requestservice_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 viaresponse_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 toimages/.
Image and video
generate_image— create or edit images with Grok Imagine (multi-reference editing supported). Passsave=trueto write the results toimages/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 inchats/.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.