Frequently Asked Questions (FAQ)

Q: What is an MCP Server? A: An MCP (Model Context Protocol) server acts as a bridge, allowing AI models to access and interact with external data sources and tools. It standardizes how applications provide context to LLMs.

Q: What is the purpose of this Python MCP Server? A: This server provides real-time cryptocurrency price information via the CoinMarketCap API to AI agents and applications.

Q: What are the key features of this MCP Server? A: Real-time price retrieval, CoinMarketCap integration, environment-based configuration, and Docker container deployment.

Q: What are the requirements to run this server? A: Python 3.12+, uv (package and virtual environment manager), and Docker (optional).

Q: How do I install the server? A: Clone the repository, create a virtual environment using uv, and install dependencies using uv sync.

Q: How do I configure the server? A: Create a .env file in the project root and configure the necessary environment variables.

Q: How do I run the server locally? A: Execute python main.py in your terminal.

Q: How do I deploy the server using Docker? A: Build the Docker image using docker build -t mcp/python-server-mcp -f Dockerfile . and run the container.

Q: How do I add new tools to the MCP Server? A: Define the function in the src/__init__.py file, register the tool in the main() function, and document the tool with docstrings.

Q: How does this server integrate with UBOS? A: This server can be integrated with UBOS to provide real-time crypto data to AI agents within the UBOS platform.

Q: What is UBOS? A: UBOS is a full-stack AI Agent Development Platform that helps you orchestrate AI Agents, connect them with your enterprise data, build custom AI Agents with your LLM model and Multi-Agent Systems.