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🧠 MCP Server Practice

@Dhiraj123-star

About 🧠 MCP Server Practice

No overview available yet

Basic information

Category

Other

Runtime

python

Transports

stdio

Publisher

Dhiraj123-star

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

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: add and multiply for 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.

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