Question 1

What is the Raccoon AI MCP Server?

Accepted Answer

The Raccoon AI MCP Server is an implementation of the Model Context Protocol (MCP) that allows AI models, like those used in UBOS, to seamlessly interact with the web for tasks such as browsing, data extraction, and automation.

Question 2

What is MCP (Model Context Protocol)?

Accepted Answer

MCP is an open protocol standardizing how applications provide context to Large Language Models (LLMs). It enables AI models to access external data sources and tools.

Question 3

What can I do with the Raccoon AI MCP Server?

Accepted Answer

You can automate web browsing, extract structured data from websites, fill out forms, navigate UI elements, and handle multi-step processes across different websites.

Question 4

What are the prerequisites for using the server?

Accepted Answer

You need Python 3.8 or higher, Claude Desktop (or another MCP-compatible client), and your Raccoon AI Secret Key and Passcode.

Question 5

How do I install the Raccoon AI MCP Server?

Accepted Answer

You can install it using Smithery with the command `npx -y @smithery/cli@latest install @raccoonaihq/raccoonai-mcp-server --client claude` or from source by cloning the GitHub repository and installing the dependencies.

Question 6

How do I configure the server in Claude Desktop?

Accepted Answer

Use the command `mcp install src/raccoonai_mcp_server/server.py -v RACCOON_SECRET_KEY= -v RACCOON_PASSCODE=` after replacing the placeholders with your actual credentials.

Question 7

Where can I find my Raccoon AI Secret Key and Passcode?

Accepted Answer

You can find your credentials on the [Raccoon AI platform](https://platform.flyingraccoon.tech).

Question 8

Can I use this server with other AI platforms besides UBOS?

Accepted Answer

Yes, the server is MCP-compatible and can be used with any platform that supports the Model Context Protocol.

Question 9

What are some example use cases for the server?

Accepted Answer

Examples include extracting product information from e-commerce sites, summarizing news articles, automating form submissions, and generating detailed reports based on web data.

Question 10

Where can I find more documentation?

Accepted Answer

Refer to the [Raccoon LAM API Documentation](https://docs.flyingraccoon.tech/reference/lam/run) and the [Model Context Protocol Documentation](https://modelcontextprotocol.io).

Question 11

How does the Raccoon AI MCP Server enhance the UBOS platform?

Accepted Answer

It allows UBOS AI Agents to access real-time data, automate web tasks, interact with web services, and learn from web content, thereby significantly enhancing their capabilities and enabling more complex and sophisticated AI-driven solutions.

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