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Wallex MCP Server

@SajjadKiani

基本信息

分类

其他

传输方式

stdio

作者

SajjadKiani

关于 Wallex MCP Server

暂无概览

Wallex MCP Server 配置

暂无标准配置

该服务器的 README 中没有可解析的 MCP 配置块,请前往代码仓库查看安装说明。

代码仓库

Wallex MCP Server 工具

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当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Wallex MCP Server?

Wallex MCP Server is a FastMCP-based server that enables LLMs to interact with the Wallex REST API. It provides tools and resources for querying balances, placing and canceling orders, and fetching market data. The server is built with FastMCP, uses an HTTPX client wrapper, and validates responses with Pydantic schemas.

How to use Wallex MCP Server?

Run in development mode with fastmcp dev wallex_mcp/server.py. For production, use mcpo --port 8001 --api-key "wallex-local" -- fastmcp run wallex_mcp/server.py. Configuration is loaded from environment variables via config.py.

Key features of Wallex MCP Server

  • Tools: get_balance, place_order, cancel_order
  • Resources: wallex://market/{symbol}, wallex://orders/{id}, instruments
  • Built with FastMCP and Pydantic for type safety
  • Uses HTTPX for async API calls
  • Includes a Dockerfile for containerized deployment

Use cases of Wallex MCP Server

  • Automated cryptocurrency trading via LLM prompts
  • Real-time portfolio balance checking
  • Order management (placing and canceling)
  • Market data retrieval for analysis

常见问题

1

How do I run Wallex MCP Server in development?

Use the command `fastmcp dev wallex_mcp/server.py` for development with hot-reloading.

2

How do I deploy Wallex MCP Server in production?

Run `mcpo --port 8001 --api-key "wallex-local" -- fastmcp run wallex_mcp/server.py` with your API key.

3

What tools and resources are available?

Tools: `get_balance`, `place_order`, `cancel_order`. Resources: market data (by symbol), order status (by ID), and instruments list.

4

What are the dependencies?

The server requires Python, FastMCP, HTTPX, and Pydantic as listed in `requirements.txt`. A Dockerfile is provided for containerized use.

5

How is configuration handled?

Environment variables are loaded by `config.py` in the server package. The production command also requires an API key passed via `--api-key`.

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