Binance MCP Server 🚀
@SayantiPalKCMS
Binance MCP Server 🚀 について
Binance MCP Server is a robust tool that allows AI agents to connect with the Binance cryptocurrency exchange. It offers essential trading tools and market data access for efficient trading. 🐙💻
基本情報
設定
以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。
{
"mcpServers": {
"binance-mcp-server-sayantipalkcms": {
"command": "python",
"args": [
"main.py"
]
}
}
}ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
What is Binance MCP Server?
The Binance MCP Server provides unofficial tools and a server implementation for Binance’s Model Context Protocol (MCP). It is designed to help developers build crypto trading AI agents efficiently.
How to use Binance MCP Server?
Clone the repository, install dependencies (Python 3.7+ and pip install -r requirements.txt), then download the latest release from the GitHub Releases page. Edit the configuration file with your Binance API keys, trading pair, and strategy, and run python main.py to start the server.
Key features of Binance MCP Server
- Easy integration with Binance’s API
- Real-time market data access
- Customizable trading agents
- Robust framework for trading bots
- Community support for developers
Use cases of Binance MCP Server
- Build and deploy crypto trading bots
- Implement and test trading strategies such as mean reversion
- Access real-time Binance market data
- Create customizable AI-powered trading agents
FAQ from Binance MCP Server
Do I need Binance API keys to use the server?
Yes, you must provide your Binance API key and secret in the configuration file.
What are the runtime prerequisites?
Python 3.7 or higher and pip are required. Install all dependencies using the provided requirements.txt.
Is this an official Binance product?
No, this project is an unofficial community-driven implementation.
How can I customize my trading strategy?
Modify the strategy field in the configuration file and implement your own logic in a new Python file using the server’s provided functions and classes.
How do I start the server after configuration?
Run the command python main.py from the project directory. Monitor performance using the generated logs.
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