MCP Crypto Server
by yanqinghao
A high-performance cryptocurrency market data and analysis platform built with FastMCP, CCXT, and TimescaleDB. It provides real-time data, advanced analytics, and LLM-powered insights, enabling seamless integration with AI applications.
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What is MCP Crypto Server?
MCP Crypto Server is a powerful platform that provides real-time cryptocurrency market data, advanced analytics, and LLM-powered insights. Built on the Model Context Protocol (MCP), it enables seamless integration with AI applications while offering robust cryptocurrency exchange connectivity via CCXT and time-series data storage with TimescaleDB.
How to use MCP Crypto Server?
To use the server, you need to clone the repository, install the dependencies using uv, set up TimescaleDB using Docker, configure your environment variables, and then start the server using the command uv run python main.py. MCP clients can then connect to the server and query resources, tools, and prompts.
Key features of MCP Crypto Server
Real-time Market Data
Historical Data Analysis
LLM Integration
MCP Protocol Support
Scalable Architecture
TimescaleDB Storage
Multi-Exchange Support
Use cases of MCP Crypto Server
Real-time cryptocurrency market data analysis
Advanced analytics and insights using LLMs
Integration with AI applications via MCP
Historical price and volume data analysis
FAQ from MCP Crypto Server
What is FastMCP?
What is FastMCP?
FastMCP is a server framework based on the Model Context Protocol, used for building the MCP Crypto Server.
What is CCXT?
What is CCXT?
CCXT is a library for cryptocurrency exchange connectivity, allowing the server to connect to various exchanges.
What is TimescaleDB?
What is TimescaleDB?
TimescaleDB is a time-series database extension for PostgreSQL, used for efficient storage and querying of historical data.
How do I add a new exchange?
How do I add a new exchange?
Update the services/exchange_service.py file, implement exchange-specific handling, and update the available symbols in resources/symbols.py.
How do I manage dependencies?
How do I manage dependencies?
The project uses uv for fast and efficient dependency management. Use uv add package_name to add dependencies and uv pip sync to update them.