Glossary
Key terms and concepts in agricultural APIs and precision farming.
Key terms and concepts in agricultural APIs and precision farming.
Model Context Protocol (MCP) is an open protocol that defines how AI applications — particularly large language models — connect to external data sources, APIs, and tools through a standardized interface. Think of it as USB-C for AI integrations: one plug, many devices.
Before MCP, every AI application that needed external data had to build custom integrations for each data source. A developer connecting Claude to John Deere would write completely different code than one connecting it to Climate FieldView. MCP eliminates this N-to-N integration problem by defining a common protocol that any AI client and any data provider can implement.
An MCP server exposes two primitives:
get_field_boundaries, list_equipment). Each tool has a typed schema describing its inputs and outputs.The AI client (Claude, GPT, or your own app) connects to one or more MCP servers over a standard transport (HTTP with server-sent events or stdio). The client discovers available tools and resources at connection time, then invokes them as needed during a conversation.
FieldMCP is an MCP server that provides unified access to agricultural data platforms. Instead of integrating directly with each provider's proprietary API, you connect your AI application to FieldMCP's MCP gateway, which handles authentication, data normalization, and provider-specific quirks behind a single interface.
The gateway runs on Cloudflare Workers and supports the full MCP specification including tool discovery, typed invocations, and streaming responses. See the quickstart guide to connect your first AI client, or read the authentication docs to understand how OAuth 2.1 secures the connection.