TMD Earthquake MCP Server

🌍 TMD Earthquake MCP Server v1.0

The TMD Earthquake server brings the Thai Meteorological Department’s real‑time seismic data directly into your AI assistant workflow. By exposing a set of well‑defined tools and resources over the Model Context Protocol, it lets Claude (or any MCP‑compatible client) query recent earthquakes, filter by magnitude or location, and receive concise summaries—all without leaving the chat interface. This removes the need for manual API calls or data‑scraping scripts, enabling developers to embed up‑to‑date geophysical information into applications such as emergency response dashboards, educational chatbots, or automated alert systems.

What Problem Does It Solve?

Earthquake monitoring requires low‑latency access to constantly updated datasets. Traditional approaches involve polling external APIs, parsing XML/JSON responses, and handling authentication or rate limits manually. The TMD Earthquake MCP server abstracts these complexities: it handles communication with the Thai Meteorological Department’s endpoint, normalises timestamps to both UTC and local time, and provides a unified toolset that can be invoked with natural language. Developers no longer need to write custom wrappers; instead they rely on a single, well‑documented MCP interface that delivers reliable, structured seismic data.

Core Capabilities

• Tool‑based queries: Five dedicated tools let users fetch the latest events, filter by magnitude or location, retrieve large‑earthquake lists, and obtain summary statistics. Each tool accepts intuitive parameters (e.g., , ) and returns a structured payload.
• Resource shortcuts: Two lightweight resources ( and ) expose quick access to the most recent event or all events for the current day, making it trivial to surface real‑time information in a conversation.
• Rich data fields: Every response includes UTC and Thai timestamps, geographic coordinates, epicenter depth, magnitude, event location in Thai, and optional descriptive notes. This granularity supports downstream analytics or visualisation pipelines.

Real‑World Use Cases

• Disaster Response: Emergency teams can ask an AI assistant “Show me recent earthquakes near Bangkok” and receive instant, actionable data to prioritize response efforts.
• Educational Platforms: Language learning apps or geography tutors can embed real‑time seismic events to illustrate tectonic activity, with Thai and English prompts supported natively.
• Public Alert Systems: Municipalities can integrate the server into chat‑based notification services, automatically pushing alerts when a magnitude threshold is exceeded.
• Research & Analytics: Data scientists can pull daily summaries into their analysis workflows, feeding machine‑learning models that predict aftershock probabilities or assess risk zones.

Integration into AI Workflows

Once configured in Claude Desktop (or any MCP‑aware client), the server appears as a connected plug‑in. Users interact through natural language, and the assistant translates those requests into tool calls with appropriate parameters. The server returns JSON‑structured results that can be rendered as tables, maps, or concise text summaries. Because the MCP framework handles authentication and error reporting, developers can focus on higher‑level business logic—such as triggering SMS alerts or updating a dashboard—without worrying about API rate limits or data parsing bugs.

Unique Advantages

• Localized Time Handling: The server automatically converts timestamps to Thai time, eliminating manual timezone calculations for developers targeting local audiences.
• Bilingual Support: Example commands in both English and Thai demonstrate the server’s readiness for multilingual contexts, a critical feature for national agencies.
• Extensibility: The toolset is designed to be easily expanded; adding a new filter or resource merely involves defining another MCP tool, keeping the server lightweight and maintainable.

In summary, the TMD Earthquake MCP Server turns raw seismic data into a conversational asset. It streamlines access to critical real‑time information, empowers developers to build responsive AI applications, and ensures that users—whether first responders or curious learners—receive accurate, timely earthquake insights with a simple chat prompt.