LumiFAI MCP Technical Analysis Server

by Lumif-ai

Integrations

  • Processes cryptocurrency trading data from Binance pairs, specifically calculating and providing Exponential Moving Average (EMA) technical analysis indicators

  • Integrates with MongoDB for storage and retrieval of OHLCV (Open, High, Low, Close, Volume) cryptocurrency data which serves as the basis for technical analysis

LumiFAI MCP Technical Analysis Server

A FastMCP server that provides technical analysis tools for cryptocurrency trading data, specifically focusing on Exponential Moving Average (EMA) calculations for Binance pairs. The server defaults to SSE transport layer for communication.

Features

  • Calculate EMAs (12 and 26 periods) for cryptocurrency price data
  • Real-time date and time information
  • MongoDB integration for data storage and retrieval (Fetches data from DB resource which contains OHLCV data)
  • SSE (Server-Sent Events) transport support

Prerequisites

  • Python 3.13 or higher
  • MongoDB instance
  • uv package manager

Installation

  1. Clone the repository:
git clone <repository-url> cd lumifai-mcp-ta
  1. Create and activate a virtual environment and install dependencies:
uv sync
  1. Set up environment variables: Create a .env file in the root directory with the following content:
MONGODB_URI=your_mongodb_connection_string

Usage

Run the server:

uv run mcp-server.py

Available Tools

  1. get_emas(agent_name: str, time_ago: str, interval: int, interval_frequency: str)
    • Calculates EMAs for specified cryptocurrency trading pairs
    • Returns a DataFrame with fast (12-period) and slow (26-period) EMAs
  2. get_date_time()
    • Returns the current date and time
-
security - not tested
F
license - not found
-
quality - not tested

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Provides technical analysis tools for cryptocurrency trading data, calculating EMAs (12 and 26 periods) for Binance pairs using MongoDB for data storage.

  1. Features
    1. Prerequisites
      1. Installation
        1. Usage
          1. Available Tools

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