Step-By-Step Implementation Walk Through:

(1) Create a new directory named "mcptool" in your C:\ drive by running the command: mkdir mcptool

(2) Open Visual Studio Code, click File, and select Open Folder.

(3) Select the folder “mcptool”

(4) Select “New Terminal” from the Menu.

(5) Type the following commands in your terminal:

PS C:\mcptool>mkdir mcp-perplexityHealthcareSearch and press Enter

PS C:\mcptool>cd mcp-perplexityHealthcareSearch and press Enter

PS C:\mcptool\mcp-perplexityHealthcareSearch> python -m venv .venv and press Enter

PS C:\mcptool\mcp-perplexityHealthcareSearch> .venv\Scripts\activate (For Windows) or source .venv\bin\activate (For Mac) and press Enter(.venv)

PS C:\mcptool\mcp-perplexityHealthcareSearch> pip install python-dotenv perplexityai mcp and press Enter

(6) Create a new file called “server.py” and paste the following Python code into Visual Studio Code.

(7) Get your Perplexity API key from https://www.perplexity.ai/account/api/keys

(8) Create a new file called ".env" in Visual Studio Code and replace the placeholder PERPLEXITY_API_KEY = "YOUR_API_KEY" with your actual API key.

(9) Open the Claude Desktop App, click the hamburger menu, select File, then go to Settings.

(10) Select the Developer menu and click "Edit Config" and then select the file name: claude_desktop_config.json and double click on the file to open it.

(11) Copy the configuration file and past it into the file: claude_desktop_config.json and save it.

(12) If successful, you will see a running status.

(13) Click the New Chat menu, then click "+" to check Connections. Verify that "PerplexityHealthcareSearch" appears and is toggled on.

(14) Use the following prompt to test the MCP adoption dashboard

Summarize the latest WHO outbreak alerts of Q4'2025 in Southeast Asia and provide dashboard for data analytic insights.

(15) The visualization displays a Q4 2025 Southeast Asia Outbreak Analytics Dashboard with comprehensive surveillance data for disease outbreaks in the region from October to December 2025.

(16) Use the following prompt to compare the MCP adoption dashboard results.

Summarize WHO outbreak alerts published in Q4 2025 (1 Oct–31 Dec 2025) that are relevant to Southeast Asia, and deliver an interactive analytics dashboard that lets users explore outbreaks organized by country, pathogen/event type, publication date, severity signals, and WHO recommendations.

Key Takeaways

• MCP (Model Context Protocol) enables seamless integration between AI systems and real-time external data, addressing traditional integration challenges
• The protocol offers a standardized approach that eliminates the need for costly bespoke integrations across different systems
• Implementation requires minimal setup with standard development tools (VS Code, Python) and API configurations
• The practical guide demonstrates how to build an MCP dashboard using Perplexity Real-time Search API integration
• MCP represents a strategic advancement for organizations seeking to scale their AI implementations efficiently