Grok MCP Plugin
@Bob-lance
Grok MCP Plugin について
MCP server for Grok AI API integration
基本情報
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"grok-mcp": {
"command": "node",
"args": [
"build/index.js"
],
"env": {
"XAI_API_KEY": "your-grok-api-key"
}
}
}
}ツール
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概要
What is Grok MCP Plugin?
Grok MCP Plugin is a Model Context Protocol (MCP) server that provides seamless access to Grok AI’s chat, vision, and function‑calling capabilities directly from Cline. It is built for developers using Cline with MCP support who want to integrate Grok AI into their workflows.
How to use Grok MCP Plugin?
Install Node.js (v16+), obtain a Grok AI API key from console.x.ai, and ensure Cline has MCP support. Clone the repo, run npm install && npm run build, then add the MCP server configuration to your Cline MCP settings (e.g., ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json). Use the three exposed tools via Cline’s <use_mcp_tool> syntax.
Key features of Grok MCP Plugin
- Chat completion with Grok language models
- Image understanding using Grok’s vision capabilities
- Function calling based on user input
- Supports both image URLs and base64‑encoded images
- Configurable temperature, max tokens, and model selection
Use cases of Grok MCP Plugin
- Generate text responses from Grok AI inside Cline
- Analyze images with natural language prompts
- Automate tasks by having Grok invoke external functions
- Build AI‑powered assistants integrated with Cline
FAQ from Grok MCP Plugin
What are the prerequisites to use this plugin?
Node.js v16 or higher, a Grok AI API key from console.x.ai, and Cline with MCP support.
How do I configure the plugin’s API key?
Set the XAI_API_KEY environment variable in your Cline MCP settings configuration under the env object.
What tools does the plugin expose?
Three tools: chat_completion for text generation, image_understanding for vision analysis, and function_calling for invoking functions.
Can I provide images as base64 instead of a URL?
Yes. Use the base64_image parameter (without the data:image prefix) instead of image_url.
What models are used by default?
Chat completion defaults to grok-3-mini-beta, image understanding defaults to grok-2-vision-latest. Both can be overridden.
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