Question 1

What is the Grok AI MCP Server?

Accepted Answer

The Grok AI MCP Server is a Node.js-based server that integrates with the xAI Grok API to provide AI-driven analysis tools for the Solana blockchain and other applications. It uses the Model Context Protocol (MCP) to expose tools for analyzing transactions, addresses, images, and general queries.

Question 2

What is MCP (Model Context Protocol)?

Accepted Answer

MCP is an open protocol that standardizes how applications provide context to Large Language Models (LLMs), enabling AI models to access and interact with external data sources and tools.

Question 3

What can I analyze with the Grok AI MCP Server?

Accepted Answer

You can analyze Solana blockchain transactions and addresses, process images using Grok's vision capabilities, and ask general questions with optional context and image support.

Question 4

What are the prerequisites for using the Grok AI MCP Server?

Accepted Answer

You need Node.js (version 16 or higher), npm, and an API key from xAI.

Question 5

How do I install the Grok AI MCP Server?

Accepted Answer

Clone the repository, install dependencies using `npm install`, set up your xAI API key in a `.env` file, and run the server with `npm start`.

Question 6

How do I interact with the server?

Accepted Answer

The server uses MCP over stdio. You can interact with it programmatically using an MCP client or by sending JSON requests via a compatible interface. Refer to the MCP SDK Documentation for details on client implementation.

Question 7

What is UBOS?

Accepted Answer

UBOS is a full-stack AI Agent development platform that helps you orchestrate AI Agents, connect them with your enterprise data, build custom AI Agents with your LLM model and Multi-Agent Systems.

Question 8

What models does the Grok AI MCP Server use?

Accepted Answer

The server uses `grok-2-vision-latest` for vision tasks and `grok-2-latest` for text-only queries.

Question 9

How can I contribute to the Grok AI MCP Server project?

Accepted Answer

Fork the repository, create a feature branch, commit your changes, push to the branch, and open a pull request.

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