Selector AI FAQs

Question 1

What are the key features of the Selector AI FastMCP server?

Accepted Answer

The server is FastMCP-compatible, built on Python, supports real-time SSE streaming, offers interactive AI chat, has minimal boilerplate, and includes a built-in health check for container orchestration.

Question 2

How does the Docker-based client work?

Accepted Answer

The client spawns the server via Docker and communicates using stdin/stdout. It supports both CLI and programmatic access and uses environment variables for configuration.

Question 3

What do I need to get started with Selector AI FastMCP?

Accepted Answer

You'll need Python 3.8+, Docker, a Selector AI API key, and the Selector API URL. Simply clone the repository, install dependencies, set your environment variables, and build the Docker image.

Question 4

Can I integrate Selector AI FastMCP with Claude Desktop?

Accepted Answer

Yes, you can. Run the server and expose a socket or HTTP endpoint. Configure Claude Desktop to connect to this endpoint using the specified message format for seamless integration.

Question 5

What is Selector AI FastMCP?

Accepted Answer

Selector AI FastMCP is a full implementation of the Model Context Protocol (MCP) for Selector AI. It provides a streaming-capable server and interactive client, facilitating easy integration with AI models.

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