MCP Server with Claude Desktop – Interactive Tool API Demo MCP Server: Enhanced AI Application Integration through Modular Claude Protocol

Overview

This project showcases an MCP (Model Context Protocol) server integrated with the FastMCP framework, providing a set of interactive tools and resources designed to work seamlessly with AI applications such as Claude Desktop. The server includes core functionalities like arithmetic operations, real-time currency exchange rate fetching, and note-taking features—each tailor-made for easy invocation via both programmatic calls or natural language instructions.

🔧 Core Features & MCP Capabilities

The core of this project lies in its ability to expose programmable tools and resources through a standardized Protocol. This makes it incredibly versatile for integrating with various AI platforms, including Claude Desktop, Continue, Cursor, and more. The server demonstrates a range of capabilities leveraging the mcp (Modular Claude Protocol) framework:

• Arithmetic Tools: Capable of performing basic mathematical operations like addition, subtraction, multiplication, and division, all with robust error handling.

• Currency Exchange Tool: Utilizes an external API to provide real-time currency exchange rates. This feature can be invaluable for applications requiring international financial transactions.

• Sticky Notes Tool: Allows users to save, read, and summarize notes locally stored in a notes.txt file. This tool is particularly useful for quick data management tasks and reminders within AI-driven workflows.

The project not only serves as a foundational building block but also acts as an exemplar of how AI application developers can leverage the MCP to create modular, highly integrated tools.

⚙️ MCP Architecture & Protocol Implementation

Protocol Flow Diagram

To understand how this server functions, consider the following Mermaid diagram illustrating the flow of communication between different components during a typical user interaction:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Data Architecture Diagram

The following Mermaid diagram provides a visual representation of the data flow and architecture within the server:

graph TD
    A[User Request] --> B[MCP Client]
    B --> C[MCP Server]
    C --> D[Local Storage (Notes)]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Example Integration Scenarios

Use Case 1: Financial Analysis Tool for AI-Driven Portfolio Management

In this scenario, the server can be configured to connect with financial APIs via MCP. Users could perform real-time currency conversions and manage their portfolios by querying the server through natural language or programmatic commands.

Technical Implementation

import httpx
from mcp import run_tool

# Example function to fetch currency exchange rates using httpx
async def get_exchange_rate(base_currency, target_currency):
    async with httpx.AsyncClient() as client:
        response = await client.get(f'https://api.exchangerate-api.com/v4/latest/{base_currency}')
    data = response.json()
    return data['rates'][target_currency]

Use Case 2: Personal Assistant for Remote Teams

The server can act as a central hub for team collaboration, allowing members to easily save and recall notes using the sticky notes tool. This could be part of the broader infrastructure supporting AI-driven productivity tools.

Technical Implementation

def add_note(note_content):
    with open('notes.txt', 'a') as file:
        file.write(f"{note_content}\n")

def read_notes():
    with open('notes.txt', 'r') as file:
        return file.read()

🚀 Getting Started with Installation

Prerequisites

Before you begin, ensure that the following dependencies are installed:

• Python 3.9+
• uv – For virtual environment and dependency management
• mcp (with cli and server extras)
• httpx

You can install these tools using pip:

pip install -r requirements.txt

Installation Steps

1. Clone the git repository.

2. Navigate to the project directory.

3. Install necessary packages:

   uv update
   

4. Run the server:

   npx cli run --tool [name]
   

💡 Key Use Cases in AI Workflows

The MCP Server with Claude Desktop – Interactive Tool API Demo serves numerous use cases in AI workflows, making it a robust platform for developers aiming to integrate modular tools across AI applications. Key benefits include:

• Enhanced Collaboration: Allows team members to seamlessly share and manage notes within an AI-driven environment.

• Real-time Data Fetching: Utilizes external APIs like Exchangerate-API for up-to-date financial information, ensuring accuracy in dynamic scenarios.

• User-friendly Interface: Facilitates quick access to tools through both programmatic calls or natural language prompts, enhancing the user experience for AI applications.

🔌 Integration with MCP Clients

The server is compatible with multiple MCP clients, including but not limited to:

• Claude Desktop: Full compatibility ensuring smooth interaction.

• Continue: Also supports full-feature integration without issues.

• Cursor: Only supports tool execution, indicating partial support for the protocol.

For developers looking to leverage these tools in their AI applications, the server offers a flexible and reliable platform.

📊 Performance & Compatibility Matrix

MCP Client Compatibility

MCP Client	Resources	Tools	Prompts
Claude Desktop	✅	✅	✅
Continue	✅	✅	✅
Cursor	❌	✅	❌

🛠️ Advanced Configuration & Security

MCP Configuration Sample

Here’s a sample configuration for setting up the server:

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

Example of Setting Up Security Features

To ensure the server remains secure, you can implement authentication and authorization measures in conjunction with the mcp protocol. This might include setting up an API key for secure communication.

❓ Frequently Asked Questions (FAQ)

Q1: How do I install dependencies?

A1: Follow the instructions provided in the README to set up Python 3.9+, uv, mcp (with cli and server extras), and httpx.

Q2: Can this server be integrated with other AI clients besides Claude Desktop and Continue?

A2: Currently, it supports integration with Claude Desktop and Continue fully but only tools for Cursor.

Q3: Is there any special setup required to run the currency exchange tool?

A3: Yes, you need an API key from exchangerate-api.com for full functionality. Follow the README instructions to obtain and add it to your environment variables.

Q4: How do I handle errors in arithmetic operations within this server?

A4: Implement robust error handling mechanisms like try-except blocks or custom error classes to manage errors effectively during calculations.

Q5: Are there any security measures implemented for this server?

A5: Yes, the implementation includes basic security such as secure API key usage and can be further enhanced with additional authentication and authorization methods.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome from individuals who wish to improve or expand upon this project. Please adhere to the following guidelines:

• Use consistent code style.
• Write clear and concise documentation.
• Ensure all tests pass before submission.

If you’re interested in contributing, please reach out on GitHub for more information under our "Issues" tab.

🌐 MCP Ecosystem & Resources

For developers building AI applications and MCP integrations, this project provides a blueprint. Explore the broader MCP ecosystem at GitHub for additional resources and community-driven projects.