What is the LumiFAI MCP Technical Analysis Server?

The LumiFAI MCP Technical Analysis Server is a tool that provides technical analysis capabilities for cryptocurrency trading, focusing on EMA calculations for Binance pairs.

What is MCP?

MCP (Model Context Protocol) standardizes how applications provide context to LLMs, enabling AI models to access and interact with external data and tools.

What are Exponential Moving Averages (EMAs)?

EMAs are technical indicators that show the average price of an asset over a specific period, giving more weight to recent prices.

What cryptocurrencies does the server support?

The server primarily focuses on Binance trading pairs.

What is SSE transport support?

SSE (Server-Sent Events) allows for real-time data streaming from the server to the client, improving responsiveness.

What are the prerequisites for running the server?

Python 3.13 or higher, MongoDB instance, and the uv package manager.

How do I install the server?

Clone the repository, create a virtual environment, install dependencies using uv sync, and set up environment variables.

What environment variables do I need to configure?

You need to set the MONGODB_URI variable in the .env file with your MongoDB connection string.

How do I run the server?

Run the command uv run mcp-server.py in your terminal.

What tools are available in the server?

get_emas for calculating EMAs and get_date_time for getting the current date and time.

What does get_emas do?

It calculates EMAs for specified cryptocurrency trading pairs, returning a DataFrame with fast (12-period) and slow (26-period) EMAs.

What is UBOS?

UBOS is a full-stack AI Agent Development Platform that helps businesses orchestrate AI Agents, connect them with enterprise data, and build custom AI Agents.

How does the LumiFAI MCP server integrate with UBOS?

The server provides data that AI Agents on UBOS can use for intelligent trading decisions.

Can I use my own LLMs with UBOS and the LumiFAI MCP server?

Yes, UBOS allows you to integrate your own Large Language Models (LLMs) into your AI Agents.

Where does the server get the OHLCV data from?

The server fetches OHLCV (Open, High, Low, Close, Volume) data from a MongoDB resource.