Wallex MCP Server

@SajjadKiani

Repository

Basic information

About Wallex MCP Server

No overview available yet

Wallex MCP Server config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Wallex MCP Server tools

Tool list not available yet

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Overview

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

Frequently asked questions

How do I run Wallex MCP Server in development?

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

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.

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.

What are the dependencies?

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

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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