An AI agent is a system built around a language model that plans and takes actions through tools in a loop — observing results and deciding the next step — to accomplish a goal, rather than producing a single reply.
An agent runs an iterative loop: the model reasons, calls a tool, reads the result, and repeats until the task is done. Tool calling and protocols like MCP are what give it hands; without external tools it can only talk.
Agents are increasingly the primary consumer of APIs — they discover and call data tools autonomously, which is why agent-native, MCP-first data delivery matters.
An investing agent asked to "screen for insider cluster-buys" calls a data tool, filters the rows, then calls another tool to enrich the survivors — several steps, one goal.
AI agents are Arkolith's primary customer. The product is shaped for the agent that calls our MCP server, with humans as the thin onboarding surface.
Arkolith turns this into live, sourced data your agent can query — SEC filings, insider activity, and market data behind one key, every datapoint traceable to its origin.