OS NGD Features API - MCP Server: Universal Adapter for Geographic Data Integration

Overview: What is OS NGD Features API - MCP Server?

The OS NGD Features API - MCP Server is a Python-based service that serves as an intermediary between Model Context Protocol (MCP) clients, such as AI applications like Claude Desktop, Continue, and Cursor, and the Ordnance Survey National Geographic Database (NGD) Features API. By acting as this bridge, it simplifies access to geographic data through MCP-compliant interfaces.

The service handles authentication, rate limiting, and error handling for the external dataset, ensuring seamless integration with various AI applications without requiring complex configuration or direct interaction with the OS NGD API endpoints. It provides a standardized interface that transforms responses from one format into MCP-compatible formats, making it easier for developers to implement and utilize geographic data within their systems.

🔧 Core Features & MCP Capabilities

Collection Management

This server supports operations such as listing collections, querying collections based on filters, and retrieving individual features by ID. These functionalities are translated into MCP-friendly APIs, allowing MCP clients to seamlessly perform CRUD (Create, Read, Update, Delete) operations within the context of geographic data.

Feature Search & Retrieval

Users can perform spatial and attribute-based searches on features, which are then converted into standardized responses based on the MCP protocol. This includes bulk operations where multiple features or identifiers can be retrieved in a single request, streamlining workflows that require processing large datasets.

Linked Identifier Operations

The service also facilitates querying linked identifiers, ensuring related data points can be easily accessed and utilized by AI applications. This is particularly useful when working with interconnected datasets such as those found within geographic information systems (GIS).

⚙️ MCP Architecture & Protocol Implementation

The architecture of the OS NGD Features API - MCP Server is designed to follow MCP standards meticulously, ensuring that it adheres to the protocol's guidelines and enhances interoperability across different environments.

Model Context Protocol

MCP defines a set of rules and conventions for creating adaptable and reusable models that can be integrated into various AI applications. The server implements these principles by converting raw API responses into structured MCP data objects, making it easier to consume and manipulate geographic information within an AI application's ecosystem.

The service architecture includes two main components:

• api_service: Handles communication with the external OS NGD Features API.

  • Authentication Management: Ensures secure access using provided API keys.
  • Request Handling & Response Formatting: Formats incoming requests and processes responses according to MCP standards.
  • Rate Limiting: Implements mechanisms to control request frequency, preventing overloading of remote services.

• mcp_service: Exposes NGD Features functionality as MCP-compliant tools.

  • Data Transformation: Translates API responses into MCP-compatible formats for seamless integration with MCP clients.
  • Business Logic Implementation: Applies specific logic required by client applications during data retrieval and manipulation processes.

🚀 Getting Started with Installation

To set up the OS NGD Features API - MCP Server, follow these steps:

1. Install Python (version 3.11 or higher).
2. Set Up Environment Variables: You will need to register for an Ordnance Survey Data Hub account to obtain your API key.

   export OS_API_KEY=your_api_key_here
   

3. Create Virtual Environment and Install Dependencies:

   python3 -m venv venv
   source venv/bin/activate
   pip install aiohttp mcp[cli]
   

4. Initialize the Server Configuration: Run the server with a configuration file.

{
  "mcpServers": {
    "os-ngd-api": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-os-ngd-api"],
      "env": {
        "OS_API_KEY": "${{ process.env.OS_API_KEY }}"
      }
    }
  }
}

💡 Key Use Cases in AI Workflows

The OS NGD Features API - MCP Server is particularly beneficial for AI applications that need to integrate with geographic data:

Workflow Scenario: Urban Planning Application

Imagine an urban planning application needing to analyze land use changes over multiple years. By utilizing this server, the app can easily make spatial and attribute queries against historical land use data from Ordnance Survey, automating the process of feature extraction and manipulation.

Technical Implementation: The MCP client would send queries via the standardized API, which the server then converts into structured MCP requests to the OS NGD Features API. These requests include parameters such as date ranges, geographical boundaries, and specific attributes related to land use. Upon receiving results, the server formats them according to MCP protocols before returning to the client.

Workflow Scenario: Real Estate Investment Tool

A real estate investment tool can benefit from quickly accessing detailed geographical data on properties for analysis purposes. The service enables swift retrieval of relevant features based on criteria like proximity to infrastructure or demographic insights, enhancing decision-making capabilities.

Technical Implementation: The real estate AI application could leverage this server through its MCP client by integrating the available tools such as search_features, get_linked_identifiers, etc., to refine property selections according to various filters. Results are then processed and displayed in a user-friendly manner tailored for investment analysis.

🔌 Integration with MCP Clients

The OS NGD Features API - MCP Server ensures seamless integration with existing and future MCP clients by adhering strictly to the protocol definitions:

• Claude Desktop: Fully supported, providing tested interoperability.
• Continue & Cursor: Both have compatibility marked as tools-only (no prompts support yet).

This level of flexibility allows developers to build custom workflows that integrate seamlessly into their AI applications without requiring extensive changes.

📊 Performance & Compatibility Matrix

Below is a matrix comparing the OS NGD Features API - MCP Server's compatibility with different MCP clients:

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

🛠️ Advanced Configuration & Security

For advanced setup and security considerations, the server provides flexible options:

Environment Variables

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

Error Handling & Security

Implement robust error handling strategies to manage authentication failures and other issues. Additionally, consider using encryption for sensitive data stored or transmitted between client applications and the MCP server.

❓ Frequently Asked Questions (FAQ)

1. Q: Can I use this server with non-MCP clients?

   • A: Yes, though it is primarily designed for MCP-compliant systems due to its adherence to specific protocol definitions.

2. Q: What are the system requirements for running this server?

   • A: Python 3.11 or later and an active Ordnance Survey API key.

3. Q: How do I securely manage authentication credentials?

   • A: Store them using environment variables to enhance security, especially when deploying in production environments.

4. Q: What happens if the external API experiences downtime?

   • A: The server will handle failures gracefully by retrying requests and offering fallback mechanisms to maintain service stability for MCP clients.

5. Q: Is there any support for customizing prompt templates within tools like Continue or Cursor?

   • A: Currently, only partial support exists; full customizability might require additional development work beyond the scope of this server's core functionalities.

👨‍💻 Development & Contribution Guidelines

Contributions to improve the OS NGD Features API - MCP Server are highly encouraged through issues and pull requests. Developers can find detailed instructions in the contribution guidelines provided within the repository for those looking to enhance or extend the server’s functionality.

🌐 MCP Ecosystem & Resources

For those interested, exploring other services built on Model Context Protocol can provide additional value for integrating diverse data sources into AI workflows. Join communities and forums dedicated to MCP development to connect with fellow developers and learn more about best practices and new tools.

By leveraging the OS NGD Features API - MCP Server, organizations and individuals working in geographic analysis and real-time data processing gain significant advantages through efficient access to critical information.