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DNDzgz MCP Server

MCP Server

Real-time Zaragoza transit data via Model Context Protocol

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Updated Jun 8, 2025

About

Provides real-time tram, bus, and Bizi station information for Zaragoza using the DNDzgz API, with tools for arrivals, station lists, geolocation, and Google Maps links.

Capabilities

Resources
Access data sources
Tools
Execute functions
Prompts
Pre-built templates
Sampling
AI model interactions

Screenshot of an example using Claude Desktop, asking in Spanish to get the tram estimations for Romareda station

The Mcp Dndzgz server is a specialized MCP (Model Context Protocol) endpoint that exposes real‑time public transport and mobility data for Zaragoza, Spain. By wrapping the official DNDzgz API, it allows AI assistants such as Claude to retrieve up‑to‑date tram arrivals, bus schedules, bicycle‑sharing station status, and geolocation services without the assistant having to manage API keys or data parsing logic. This abstraction reduces friction for developers who want to embed local transit information into conversational agents, dashboards, or mobile applications.

At its core, the server offers a suite of tools that map directly to common user queries. For instance, returns arrival times for a chosen tram stop, while does the same for bus stops. Complementary listing tools—like , , and —provide searchable inventories of stops, sorted by proximity to a supplied latitude/longitude. The bicycle‑sharing tools ( and ) deliver real‑time availability of bikes and parking slots, enabling “bike‑to‑destination” planning. Finally, utility tools such as and bridge the gap between raw coordinates and user‑friendly map URLs or formatted addresses.

These capabilities are especially valuable for developers building location‑aware conversational agents. A user can ask, “What’s the next tram to Plaza de España?” and the assistant simply calls with the relevant station ID, returning a concise arrival estimate. In more complex scenarios, an assistant could chain multiple tools: geolocate the user’s address, find nearby tram stations, fetch arrival times, and generate a Google Maps link—all within a single dialogue turn. This seamless integration streamlines the development of travel assistants, city guides, or smart‑home voice controls that rely on accurate, real‑time transit data.

Real‑world use cases span tourism apps that provide visitors with live transport updates, logistics platforms that schedule pickups based on public transit schedules, and accessibility tools that help users navigate Zaragoza’s multimodal network. Because the server handles authentication (via a Google Maps API key) and data normalization, developers can focus on conversational design rather than infrastructure concerns. The MCP’s transport flexibility—supporting both HTTP and stdio—further simplifies deployment in cloud, on‑premise, or local environments.

In summary, the Mcp Dndzgz server turns Zaragoza’s transit APIs into a developer‑friendly, AI‑ready service. By offering precise, location‑based tools and utility functions, it empowers conversational agents to deliver timely, contextually relevant mobility information—making city exploration and daily commuting smoother for users.