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FAQ

What is the MCP Server used for? The MCP Server is designed to optimize code reviews by leveraging AI models to provide second opinions and detailed analysis on large codebases.

How does the MCP Server select the appropriate AI model? The server automatically selects between OpenAI’s O3 model and Google’s Gemini 2.5 Pro based on the token count of the context provided.

What happens if an API key is missing? If an API key is missing, the server will use the available model within its token limit or return an informative error if both keys are absent.

Can the MCP Server handle network connectivity issues? Yes, the server has built-in fallback mechanisms to switch models in case of network issues, ensuring continuous operation.

How does the MCP Server integrate with existing workflows? The server uses environment variables for configuration and JSON-RPC for tool calls, making it compatible with various development environments.

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