CCXT
Enables Large Language Models to interact with cryptocurrency exchanges for tasks like fetching market data, managing accounts, and creating orders.
About
This project provides a Model Context Protocol (MCP) server that exposes functions from the CCXT library, allowing Large Language Models (LLMs) to interact with cryptocurrency exchanges. It supports tasks like fetching balances, market data, creating orders, and more, in a standardized and asynchronous manner. Built using FastMCP, the server wraps common CCXT functions, provides clear tool definitions using `typing.Annotated` and `pydantic.Field`, and handles authentication for both public market data and private account actions.
Key Features
- Asynchronous operations using `asyncio` and `ccxt.async_support`.
- 2 GitHub stars
- Provides separate tools for public and private data.
- Wraps CCXT functions for exchange interaction.
- Clear parameter descriptions using `typing.Annotated` and `pydantic.Field`.
- Supports API key, secret, and passphrase authentication.
Use Cases
- Automating cryptocurrency trading strategies using LLMs.
- Integrating cryptocurrency data and trading functionalities into LLM-powered applications.
- Enabling LLMs to manage and monitor cryptocurrency portfolios.
Sponsored