🧠 MCP Server Practice
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About 🧠 MCP Server Practice
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Config
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Overview
What is 🧠 MCP Server Practice?
A modular FastAPI-based server powered by FastMCP that showcases practical implementations of AI tools, math operations, web search, audio response generation, and external API integration. It is designed for AI agents or CLI tools that need to call these tools via a standardized interface.
How to use 🧠 MCP Server Practice?
The server is launched with mcp.run(transport="stdio"). Each tool is defined using the @mcp.tool() decorator, making them accessible as callable interfaces. No installation or configuration commands are given beyond the Python + dotenv environment.
Key features of 🧠 MCP Server Practice
- Math utilities:
addandmultiplyfor integer arithmetic. - Live weather data for any city via WeatherAPI.
- Web search using OpenAI’s web search tool.
- Audio response generation (WAV format) using OpenAI’s
gpt-4o. - Custom resource
greeting://{name}returning a personalized greeting.
Use cases of 🧠 MCP Server Practice
- Adding or multiplying numbers through an AI agent.
- Getting real‑time weather conditions for a city.
- Performing live web searches and retrieving concise results.
- Converting text queries into spoken audio files.
- Generating personalized greeting strings from a resource route.
FAQ from 🧠 MCP Server Practice
What runtime and dependencies are required?
Python with the FastAPI, FastMCP, OpenAI, and python‑dotenv packages, plus environment variables for API keys.
How does audio generation work?
audio_query(text) uses OpenAI’s gpt-4o audio capabilities and saves the resulting WAV file to the /audio folder.
What transport does the server use?
The server runs with transport="stdio", as shown in the startup command mcp.run(transport="stdio").
Are there any authentication or security measures described?
The README does not mention authentication or security measures beyond using a .env file for environment variables.
Frequently asked questions
What runtime and dependencies are required?
Python with the FastAPI, FastMCP, OpenAI, and python‑dotenv packages, plus environment variables for API keys.
How does audio generation work?
`audio_query(text)` uses OpenAI’s `gpt-4o` audio capabilities and saves the resulting WAV file to the `/audio` folder.
What transport does the server use?
The server runs with `transport="stdio"`, as shown in the startup command `mcp.run(transport="stdio")`.
Are there any authentication or security measures described?
The README does not mention authentication or security measures beyond using a `.env` file for environment variables.
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