The fastest-growing consumer of financial information is no longer a person — it is an AI agent doing research, monitoring portfolios, or executing workflows on someone's behalf. These agents don't read charts or navigate menus. They need structured entities, stable identifiers, clean JSON, and honest metadata about freshness and provenance.
Most financial websites fail this test completely: data lives in rendered charts, paywalled terminals, or PDFs. The sites that win agent traffic are the ones that expose the same knowledge as clean endpoints and machine-readable indexes (llms.txt, OpenAPI schemas, MCP servers) — because an agent that can consume you becomes a distribution channel, not a scraper.
The emerging stack is recognizable: a knowledge layer (entities and relationships), an API layer (typed, versioned, cache-friendly), and an agent interface layer (tool definitions the agent can call directly). Provenance is not optional — an agent that cannot tell how old a number is will propagate stale data into decisions.
Finance Foundation is built agent-first on purpose: every page here has an API twin, the whole dataset is one GET away, and /llms.txt tells an agent exactly what exists and how to fetch it.