MCP Server

The Infoplaza Platform MCP Server makes all Infoplaza Platform APIs available as standardized tools within the Model Context Protocol (MCP) ecosystem.

This allows AI agents, assistants, and autonomous applications to directly query weather, geospatial, and mobility data through a unified interface that LLMs can understand and act upon.

What is MCP?

Model Context Protocol (MCP) is an open protocol that enables AI applications to securely access external data sources and tools. MCP servers act as bridges between AI models and external APIs, providing:

• Standardized interfaces for AI models to interact with external services
• Semantic descriptions of available tools and data
• Secure authentication and access control
• Structured responses optimized for LLM interpretation

Instead of making direct HTTP requests, AI assistants can use MCP tools that are described in a way they understand, making integration seamless and intuitive.

How It Works

The Infoplaza MCP Server exposes all platform APIs as MCP tools. When an AI assistant needs weather, geospatial, or mobility data, it can:

1. Discover available tools - Query the MCP server to see what APIs are available
2. Call tools with parameters - Request specific data using natural language or structured parameters
3. Receive structured responses - Get data formatted with semantic metadata for easy interpretation

The MCP server handles authentication, request validation, data normalization, and response formatting automatically.

Available APIs

The MCP server provides access to all Infoplaza Platform APIs.

Configuration

MCP Server Endpoint

https://platform-api.infoplaza.com/v1/mcp?api_key=API_KEY

Authentication

All MCP requests require your API key as a query parameter. The MCP server uses the same authentication system as the REST API.

Parameters:

• api_key (required) — Your Infoplaza Platform API key

Usage Examples

With Claude Desktop

Add the MCP server to your Claude Desktop configuration:

{
  "mcpServers": {
    "infoplaza": {
      "url": "https://platform-api.infoplaza.com/v1/mcp",
      "apiKey": "your-api-key-here"
    }
  }
}

Once configured, you can ask Claude questions like:

• "What's the weather forecast for Amsterdam tomorrow?"
• "Find traffic incidents near Utrecht"
• "Show me transit stops near Central Station in Rotterdam"

With Custom AI Applications

MCP servers can be integrated into any application that supports the Model Context Protocol. The server exposes tools that can be called programmatically:

// Example: Calling MCP tools from your application
const response = await mcpClient.callTool({
  name: "weather_forecast",
  arguments: {
    lat: 52.3676,
    lon: 4.9041
  }
});

Benefits

For AI Developers

• No API knowledge required - LLMs understand tool descriptions automatically
• Natural language interface - Users can request data conversationally
• Automatic error handling - MCP handles authentication and validation
• Semantic responses - Data is formatted for easy LLM interpretation

For End Users

• Conversational access - Ask for data naturally without knowing endpoints
• Intelligent responses - AI can combine multiple API calls for complex queries
• Context awareness - AI understands relationships between different data types

Tool Discovery

The MCP server provides tool descriptions that include:

• Tool names - Unique identifiers for each API endpoint
• Descriptions - Natural language explanations of what each tool does
• Parameters - Required and optional parameters with types and descriptions
• Examples - Sample usage patterns

AI models use these descriptions to determine which tools to call and how to use them correctly.

Response Format

MCP tools return structured responses that include:

• Data - The requested information in a standardized format
• Metadata - Semantic descriptions and context
• Error handling - Clear error messages when requests fail

This structure allows AI models to understand and present the data effectively to users.

Next Steps

• Get your API key from the Infoplaza Platform dashboard
• Configure the MCP server in your AI application
• Start building AI-powered applications with weather, geospatial, and mobility data

For more information about the Model Context Protocol, visit the official MCP documentation.