Ultra FAQs

Question 1

Can I monitor my AI model usage and costs with Ultra MCP?

Accepted Answer

Yes, Ultra MCP includes robust built-in usage analytics. It automatically tracks every LLM request with token counts and costs, storing data locally in a SQLite database. You can view detailed statistics and real-time costs via its modern web dashboard.

Question 2

What is Ultra MCP?

Accepted Answer

Ultra MCP is a Model Context Protocol server that unifies access to OpenAI, Google Gemini, and Azure AI models through a single interface. It's designed to enhance coding workflows, particularly for developers using tools like Claude Code and Cursor.

Question 3

Which AI models and developer tools does Ultra MCP support?

Accepted Answer

Ultra MCP supports OpenAI (O3), Google Gemini (2.5 Pro), and Azure AI models. It integrates seamlessly as a standard Model Context Protocol (MCP) interface for clients like Claude Code and Cursor, providing access to powerful deep reasoning and research tools.

Question 4

How does Ultra MCP simplify AI model integration for developers?

Accepted Answer

It offers a zero-config interactive setup via `npx ultra-mcp`, can be installed as an NPM package, and provides a unified MCP interface for multi-model access, significantly reducing friction in integrating various AI services into your coding environment.

Question 5

Is my AI usage data private with Ultra MCP?

Accepted Answer

Absolutely. Ultra MCP is designed with privacy in mind. All your AI usage data, including token counts and costs, is stored exclusively on your local machine within a SQLite database and never leaves your device.

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