MCP Server for National Park Services Data - MCP Server Documentation

Overview: What is the MCP Server for National Park Services Data?

The MCP (Model Context Protocol) Server for National Park Services Data provides a standardized and efficient interface to retrieve detailed information about national parks in the United States. This server integrates seamlessly with AI applications such as Claude Desktop, Continue, Cursor, and others through Model Context Protocol (MCP), allowing them to access comprehensive park data using simple API calls. By leveraging the MCP Server, developers can enhance their AI workflows by ensuring compatibility and performance across multiple platforms.

🔧 Core Features & MCP Capabilities

This MCP server offers two primary functions:

1. Fetch List of National Parks by State
   • Tool Name: park-list
   • Parameters:
     • stateCode (string) – Two-letter U.S. state code
   • Response Example:

[
  {
    "fullName": "Yellowstone National Park",
    "description": "First national park in the U.S.",
    "parkCode": "yell"
  }
]

2. Fetch Details of a National Park
   • Tool Name: park-details
   • Parameters:
     • parkCode (string) – National Park lookup code
   • Response Example:

[
  {
    "fullName": "Yellowstone National Park",
    "description": "First national park in the U.S.",
    "states": "WY, MT, ID"
  }
]

These features are implemented using the MCP protocol to ensure compatibility and efficient data exchange between the server and various AI applications. The implementation details include proper routing, error handling, and secure API key management.

⚙️ MCP Architecture & Protocol Implementation

The server architecture is designed with scalability and performance in mind, adhering to the MCP protocol for seamless integration with different AI clients. The data flow from the input request through the process to the response is managed by the protocol, ensuring robust and efficient communication.

Model Context Protocol Flow Diagram

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

The diagram illustrates how MCP clients initiate requests, which are then processed by the server. The communication path ensures that data flows securely and efficiently from the AI application to the national park data source.

🚀 Getting Started with Installation

To get started, follow these steps to set up the MCP server:

1. Clone the Repository:

   git clone <repository-url>
   cd <repository-folder>
   

2. Install Dependencies:

   npm install
   

3. Configure Environment Variables:

   • Create a .env file in the root directory:

     API_KEY=your_nps_api_key_here
     

4. Run the Server:

   To start the MCP server using Node.js:

   npm run build
   node ./build/server.js
   

Alternatively, to use Claude Desktop:

1. Add This MCP Server to claude_desktop_config.json:

   {
       "mcpServers": {
           "nps": {
               "command": "node",
               "args": [
                   "/<Path to Server>/build/index.js"
               ],
               "env": {
                   "API_KEY": "Your NPS API Key"
               }
           }
       }
   }
   

2. Start or Restart Claude Desktop

3. Ensure Your MCP Server is Recognized and Running by Clicking on the Tools Icon in the Bottom Right Corner of Claude's Interface.

💡 Key Use Cases in AI Workflows

AI applications such as Claude Desktop can utilize this server to provide users with specific park details, making it easier to plan trips or research parks. For example:

Example 1: Querying Parks by State

• Scenario: A user wants to quickly find which national parks are located in California.

What National Parks are in the state of CA?

This request triggers a query to the MCP server, which in turn uses the NPS API to fetch relevant information. The results can then be displayed directly within Claude's interface.

Example 2: Getting Detailed Park Information

• Scenario: A user wants detailed information about Yellowstone National Park.

Give me details about Yellowstone National Park.

This command is processed by the MCP server, which queries the NPS API for the requested park data. The response structure contains full descriptions and other relevant attributes.

🔌 Integration with MCP Clients

The MCP server for national parks is designed to be compatible with multiple clients:

• Claude Desktop: Full Support (✅)
• Continue: Full Support (✅)
• Cursor: Tools Only (❌)

Real-world Integration Use Cases

1. Real-time Park Data Updates:

   • AI Application: Claude Desktop
   • Scenario: A developer integrates the MCP server to provide up-to-date park details in real time.

     {
       "mcpServers": {
         "[server-name]": {
           "command": "node",
           "args": [
             "/build/index.js"
           ],
           "env": {
             "API_KEY": "your_nps_api_key_here"
           }
         }
       }
     }
     

2. Enhanced AI Queries:

   • AI Application: Continue
   • Scenario: Enhance query capabilities by integrating park data directly into the conversational interface.

📊 Performance & Compatibility Matrix

Ensuring compatibility and performance with various MCP clients is crucial for efficient integration:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

🛠️ Advanced Configuration & Security

MCP Configuration Sample

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

Security Measures

1. Environment Variable Protection: Securely store API keys and sensitive data in the .env file.
2. Rate Limiting: Implement rate limiting to prevent abuse and ensure fair use of API resources.

❓ Frequently Asked Questions (FAQ)

1. Q: How do I obtain a valid NPS API key?

   • A: Sign up for an account at https://www.nps.gov/subjects/developer/get-started.htm and follow the instructions to generate your API key.

2. Q: What happens if I exceed my rate limits?

   • A: The MCP server includes built-in rate-limiting mechanisms, but it's advisable to implement additional measures as needed for your use case.

3. Q: Can this server be integrated with other AI applications besides Claude Desktop and Continue?

   • A: Yes, while the primary clients are currently supported by these platforms, the protocol is designed to be compatible with any MCP-compliant client.

4. Q: How do I debug issues if my queries aren’t working as expected?

   • A: Use the built-in logging capabilities in the server and the network debugging tools provided by your AI application to pinpoint and resolve issues systematically.

5. Q: Can I customize the park data displayed through prompts for specific use cases?

   • A: Yes, developers can extend the functionality by creating custom queries or modifying existing ones to fit their unique needs.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! To contribute, follow these steps:

1. Fork the Repository: Fork this repository on GitHub.

2. Clone the Forked Repository:

   git clone <forked-repository-url>
   cd <repository-folder>
   

3. Install Dependencies:

   npm install
   

4. Run Tests:

   npm test
   

5. Create a Pull Request:

   • Open a pull request from your forked repository.
   • Ensure that all tests pass and the changes are well-documented.

🌐 MCP Ecosystem & Resources

Explore the broader MCP ecosystem:

• MCP Protocol Documentation: Model Context Protocol Official Docs
• Community Forums: Join discussions on forums dedicated to Model Context Protocol.
• GitHub Repository: github.com/nationalparksdata/mcp-server

By integrating this MCP server into your AI workflows, you can provide users with valuable and timely information about national parks, enhancing the overall user experience.