In the rapidly evolving world of software development, ensuring smooth communication between various components of your application is crucial. The Model Context Protocol (MCP) provides a standardized way to manage, transfer, and share context across models, systems, or even teams. In this blog post, we will walk you through creating an MCP server, making it easy for developers and non-developers alike to implement and interact with complex systems.
We will focus on building a beginner-friendly MCP server for an HR leave management use case using Python, leveraging the Claude Desktop and its Python SDK. By the end of this guide, you’ll have the foundational knowledge to build and deploy your own MCP server that can be adapted for various use cases.
What is the Model Context Protocol (MCP)?
Before diving into the specifics of building an MCP server, let’s take a moment to understand what MCP is. MCP is a protocol designed to allow systems to communicate about “context” — this can include environment variables, configuration settings, or any other information that helps a system function optimally.
In simpler terms, MCP is about sharing information between different parts of your system or between different systems in a way that each part understands the context of what is happening.
Why MCP Matters
MCP allows systems to adapt dynamically based on changing contexts, enabling more flexible, adaptable, and scalable architectures. It is particularly useful when building systems that require quick access to evolving or shared information, like HR systems, CRM software, and other enterprise solutions.
Prerequisites for Building the MCP Server
To build an MCP server for the HR leave management use case, you will need the following:
- Claude Desktop: A robust AI framework that simplifies interaction with your data and processes.
- Python SDK for Claude: This will help you integrate Claude with your Python-based server.
- Python (3.x+): The programming language for building your MCP server.
- Basic knowledge of web development: Familiarity with HTTP, REST APIs, and basic web server concepts will help.
Step-by-Step Guide to Building the MCP Server
Step 1: Set Up Your Environment
Start by setting up your development environment. Ensure that you have Python and the necessary dependencies installed.
- Install Python 3.x
If you haven’t already, download and install the latest version of Python from the official website here. - Install Claude Desktop and SDK
Download and set up Claude Desktop on your system. You can find the installation guide and SDK documentation on the official website. - Install Dependencies
You’ll also need some Python libraries, includingFlask(for building the web server) and any libraries necessary for Claude SDK. pip install flask pip install claude-sdk
Step 2: Define Your MCP Data Structure
For an HR leave management system, your MCP server needs to handle specific data related to employee leave requests, approval processes, and leave balance tracking.
Define your data structure for leave requests. Here’s an example of what you might need:
- Employee ID
- Leave Type (Sick, Annual, etc.)
- Leave Dates
- Approval Status
- Manager Comments
This data will be the context that your MCP server handles. You can store this in a database or even use a simple file system to hold mock data for now.
Step 3: Create the MCP Server with Flask
In this step, we’ll create a basic Flask server that can accept and manage leave requests.
Create the Project Directory
mkdir mcp-server
cd mcp-server
Set Up the Basic Flask Application Create a file named app.py in your project directory:
from flask import Flask, request, jsonify
import claude_sdk
app = Flask(__name__)
# Initialize Claude SDK
claude = claude_sdk.Client(api_key='your-api-key')
# In-memory database to simulate leave requests
leave_requests = []
@app.route('/leave_request', methods=['POST'])
def create_leave_request():
data = request.json
# Add the leave request to the in-memory database
leave_requests.append(data)
# Context sharing with Claude (just a mock example)
claude.send_context(data)
return jsonify({"message": "Leave request submitted successfully"}), 200
@app.route('/leave_requests', methods=['GET'])
def get_leave_requests():
return jsonify(leave_requests), 200
if __name__ == '__main__':
app.run(debug=True)
In this example:
/leave_requestaccepts POST requests for submitting new leave requests.
/leave_requestsreturns a list of all leave requests in the system.
Step 4: Integrating Claude Context Management
One of the key aspects of this MCP server is using Claude to share context. Here, you can use Claude’s SDK to send and receive context.
In the create_leave_request route, we use claude.send_context(data) to send the leave request data to Claude. This helps share the context across your system and enables Claude to take actions based on the data it receives.
Note: You can extend this step by using Claude’s more advanced capabilities to process leave requests automatically, analyze trends in employee leave, or integrate approval workflows.
Step 5: Running the Server
Now that your MCP server is set up, it’s time to run it:
python app.pyThe Flask server should now be running at http://127.0.0.1:5000/.
You can send POST requests to /leave_request to simulate new leave requests, and GET requests to /leave_requests to view all stored leave requests.
Step 6: Testing the Server
You can use tools like Postman or curl to test your server:
Submit a Leave Request: Using curl:
curl -X POST http://127.0.0.1:5000/leave_request -H "Content-Type: application/json" -d '{"employee_id": 123, "leave_type": "Annual", "leave_dates": ["2025-05-01", "2025-05-03"], "status": "Pending"}'Get All Leave Requests: Using curl:
curl http://127.0.0.1:5000/leave_requestsConclusion
In this tutorial, we created an MCP server using Python, Flask, and Claude Desktop for an HR leave management use case. This server facilitates the management of employee leave requests by sharing context between systems via the Model Context Protocol.
With this foundational setup, you can expand the server to include more complex features, such as automated leave approval, advanced context processing with Claude, and integration with external systems (like email notifications or calendar syncing).
By mastering the basics of MCP servers, you’ll be equipped to handle more complex scenarios, build scalable systems, and create adaptable software architectures.
Further Reading: