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mcp-server-tools-assignment

by nethravathik409-ui
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Python
Remote

Assignment 2: MCP Server with 5 Tools

This project implements a small Model Context Protocol (MCP) server with five tools and a client that calls them over stdio.

What this project does

The server exposes five tools, each of which makes one GET request to a public API and returns only the relevant fields.

Tool

Input

Public API

Returned data

weather

city

https://wttr.in/{city}?format=j1

city, temp_c, condition, humidity

country_info

name

https://restcountries.com/v3.1/name/{name}

name, capital, region, population, currencies, languages

exchange_rates

base

https://open.er-api.com/v6/latest/{base}

base currency + selected rates

public_holidays

year, country_code

https://date.nager.at/api/v3/PublicHolidays/{year}/{country_code}

list of holiday objects with date, localName, name

define_word

word

https://api.dictionaryapi.dev/api/v2/entries/en/{word}

word and one or more short definitions

The client starts the server as a subprocess, lists the available tools, and calls each tool with sample input.

Related MCP server: AI Assistant Hub MCP Server

Project structure

mcp-server-tools-assignment/
├── client/
│   └── client.py
├── server/
│   ├── http.py
│   ├── server.py
│   └── tools/
│       ├── country.py
│       ├── dictionary.py
│       ├── exchange.py
│       ├── holidays.py
│       └── weather.py
├── config.py
├── README.md
├── requirements.txt
└── .venv/

Setup

cd mcp-server-tools-assignment
python3 -m venv .venv
. .venv/bin/activate
python -m pip install -r requirements.txt

Run the server directly

cd mcp-server-tools-assignment
. .venv/bin/activate
python -m server.server

This starts the MCP server over stdio.

Run the client

cd mcp-server-tools-assignment
. .venv/bin/activate
python client/client.py

This launches the server, lists the available tools, and calls each tool with sample data.

Notes on behavior

  • The project uses the mcp Python package and communicates over stdio transport.

  • The server and client are separate Python programs.

  • Each tool function makes one GET request to a public API and returns only the relevant fields.

  • Error handling is included so that invalid input or API failures do not crash the server.

Section 7 test cases and output

The following are the actual validation calls and representative outputs from the working project.

1) Weather

{'city': 'Mumbai'}

Output:

CASE:weather
{'meta': None, 'content': [{'type': 'text', 'text': '{\n  "city": "Mumbai",\n  "temp_c": 28.0,\n  "condition": "Light rain shower",\n  "humidity": 78\n}', 'annotations': None, 'meta': None}], 'structuredContent': None, 'isError': False}

2) Country info

{'name': 'India'}

Output:

CASE:country_info
{'meta': None, 'content': [{'type': 'text', 'text': '{\n  "name": "India",\n  "capital": "New Delhi",\n  "region": "Asia",\n  "population": 1380004385,\n  "currencies": [\n    "INR"\n  ],\n  "languages": [\n    "Hindi",\n    "English"\n  ]\n}', 'annotations': None, 'meta': None}], 'structuredContent': None, 'isError': False}

3) Exchange rates

{'base': 'USD'}

Output:

CASE:exchange_rates
{'meta': None, 'content': [{'type': 'text', 'text': '{\n  "base": null,\n  "rates": {\n    "USD": 1,\n    "EUR": 0.862295,\n    "INR": 95.581563,\n    "GBP": 0.738249,\n    "JPY": 160.045067,\n    "AUD": 1.395915,\n    "CAD": 1.389176,\n    "SGD": 1.273831\n  }\n}', 'annotations': None, 'meta': None}], 'structuredContent': None, 'isError': False}

4) Public holidays

{'year': 2025, 'country_code': 'US'}

Output:

CASE:public_holidays
{'meta': None, 'content': [{'type': 'text', 'text': '{\n  "date": "2025-01-01",\n  "localName": "New Year\'s Day",\n  "name": "New Year\'s Day"\n}', ... ], 'structuredContent': None, 'isError': False}

The output contains multiple holiday records, which confirms the tool is returning a non-empty list.

5) Dictionary lookup

{'word': 'example'}

Output:

CASE:define_word
{'meta': None, 'content': [{'type': 'text', 'text': '{\n  "word": "example",\n  "definitions": [\n    {\n      "partOfSpeech": "noun",\n      "meaning": "A thing characteristic of its kind or illustrating a general rule."\n    },\n    {\n      "partOfSpeech": "verb",\n      "meaning": "To serve as a pattern or model for others."\n    }\n  ]\n}', 'annotations': None, 'meta': None}], 'structuredContent': None, 'isError': False}

6) Failure path test

{'word': 'asdfghjkl'}

Output:

CASE:define_word
{'meta': None, 'content': [{'type': 'text', 'text': '{\n  "word": "asdfghjkl",\n  "definitions": [],\n  "error": "not found"\n}', 'annotations': None, 'meta': None}], 'structuredContent': None, 'isError': False}

This confirms the tool does not crash on a nonsense word; it returns a clean not found response, while valid words return real definitions.

Requirements

mcp<2
requests>=2.31.0

Purpose of the assignment

This assignment demonstrates how an MCP server exposes tools, how a client discovers them, and how the client calls them over stdio. It is a beginner-friendly example of how external APIs can be wrapped as tools that an AI or application can call in a structured and repeatable way.

This server cannot be deployed

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Maintenance

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ResponsivenessNo issues

Resources

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