Frequently Asked Questions about LocalTides MCP Server

Q: What is an MCP Server? A: MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs. An MCP server acts as a bridge, allowing AI models to access and interact with external data sources and tools.

Q: What data does the LocalTides MCP Server provide access to? A: The server provides access to NOAA Tides and Currents API data, including water levels, tide predictions, currents data, meteorological data (wind, temperature), and sun/moon phase information.

Q: How do I install the LocalTides MCP Server? A: You can install it either via Smithery using the command npx -y @smithery/cli install @RyanCardin15/tidesandcurrents --client claude or manually by cloning the repository, installing dependencies (npm install), building the TypeScript code (npm run build), and starting the server (npm start).

Q: What are some potential use cases for this server? A: Use cases include maritime navigation, coastal management, fishing industry optimization, renewable energy forecasting, environmental monitoring, search and rescue operations, and enhancing tourism/recreation applications.

Q: Can I use this server with any MCP host? A: Yes, it is compatible with any MCP host, including Claude Desktop.

Q: How can I test the server after installation? A: You can test it using the fastmcp command-line tool (npx fastmcp dev dist/index.js) or the MCP Inspector (npx fastmcp inspect dist/index.js).

Q: What output formats are supported? A: The server supports data retrieval in JSON, XML, and CSV formats.

Q: Where can I find documentation for the NOAA Tides and Currents API? A: Documentation is available at: CO-OPS Data API: https://api.tidesandcurrents.noaa.gov/api/prod/, CO-OPS Metadata API: https://api.tidesandcurrents.noaa.gov/mdapi/prod/, CO-OPS Derived Product API: https://api.tidesandcurrents.noaa.gov/dpapi/prod/

Q: How does this relate to UBOS? A: UBOS is a full-stack AI Agent Development Platform. The LocalTides MCP Server, when used on UBOS, allows you to create AI Agents that utilize real-time environmental data, connect them with your enterprise data, and build custom AI Agents using your own LLM models and Multi-Agent Systems.