Test MCP Server Feb6 USDT

You are equipped with a dedicated MCP server that exposes the Test MCP Server Feb6 USDT API through standard MCP endpoints and tools. This enables AI agents and language models to discover, query, and use the server’s capabilities in a structured, scalable way.

How to use

You interface with this MCP server by connecting via an MCP client to the exposed HTTP endpoint or by running the local stdio server. The HTTP method is suitable when you want a remote connection, while the local stdio option is useful for development and testing on your machine. You can enumerate available tools, invoke them, and receive responses in a consistent format.

How to install

Prerequisites: ensure you have network access and a supported runtime for your deployment path. The server supports Docker-based deployment and local development with Python and the uv tool.

# Option 1: Docker (recommended for quick start)
# Pull and run the provided container using the project’s docker scripts or compose setup
# Follow the repository's Docker-specific instructions to start the server

# Option 2: Local development (manual install)
# Install the uv tooling (if not already installed)
# Then install dependencies and run the server locally

Additional configuration and startup notes

The server is designed to expose an MCP endpoint at /mcp for client connections. You can run a local http-based MCP server or a local stdio-based process for testing. Ensure the port is accessible (default 8000) and adjust your environment as needed for your deployment scenario.

Troubleshooting

If the server fails to start or you encounter connection errors, verify that the MCP endpoint is reachable at the configured URL and that the port is not blocked by a firewall. Check logs for startup messages and runtime errors to identify misconfigurations or missing dependencies.

Tools and capabilities (data sources and actions)

The server provides a placeholder tool named example_tool. You can implement real endpoints and replace placeholder references with actual MCP-enabled tools as your API evolves.

Available tools

example_tool

Placeholder tool (to be implemented)