A robust MCP (Model Context Protocol) server that provides comprehensive web search and analysis capabilities using xAI's Grok API.
grok-search-mcp is an MCP project maintained in the stat-guy/grok-search-mcp repository. The maintainer describes its purpose as “A robust MCP (Model Context Protocol) server that provides comprehensive web search and analysis capabilities using xAI's Grok API”. Read the project documentation for the complete scope.
The documented npm package is grok-search-mcp. The configuration below comes from the maintainer’s example; adapt its paths and account values to your environment.
The example declares XAI_API_KEY. Secret-looking values have been replaced with placeholders. Required and optional labels are shown only when the documentation states them.
Project documentation · Repository · Discovery listing. This profile records the public documentation checked on 2026-10-08.
Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.
| Tool | What it does |
|---|---|
| grok_search | |
| grok_web_search | |
| grok_news_search | |
| grok_twitter | |
| health_check |
{
"mcpServers": {
"grok-search": {
"command": "npx",
"args": [
"grok-search-mcp"
],
"env": {
"XAI_API_KEY": "YOUR_XAI_API_KEY"
}
}
}
}From the project documentation. Replace placeholders and example paths before connecting.
| Variable | Description | Required |
|---|---|---|
| XAI_API_KEY | Declared in the maintainer’s client configuration. | Yes |
Retrieve public web pages as readable Markdown with the reference Fetch MCP server, including pagination for longer responses.
Use Firecrawl MCP to retrieve website content and extract information for research through Firecrawl’s API-backed web tools.
The original Chromium automation reference server — simple, screenshot-driven browser control.
Puppeteer-powered browser control that drives pages from the accessibility tree instead of pixels.
Automates browsers and APIs, enabling Large Language Models (LLMs) to interact with web pages for tasks like screenshot capture and JavaScript
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.