The problem, in three acts
Why “more data” hasn’t made anyone’s AI a better analyst.
Raw feeds hand your AI numbers, not answers.
Ask a real question — “Did management raise full-year guidance on the call?” — and a market-data API has no field for it. Web search doesn’t save your AI either: it quotes whatever ranks — aggregator pages, stale numbers, someone’s blog — with no way to tell fresh from wrong. The answer lives in filing prose and spoken remarks, so your AI does what AIs do with missing data: it guesses.
The answers exist — behind a $30,000 seat.
Institutional platforms employ analysts to extract exactly this layer — operational KPIs, non-GAAP reconciliations, guidance — and sell it per seat, per year, with no API for most of it. That price wall is why the extracted layer never reached individual investors.
Equibles extracts the answer layer — and hands it to your AI.
We read every filing, release and earnings call, extract the figures the feeds skip, verify each one in a second pass, and attach the verbatim source quote. We’d rather show no value than a wrong one. Then we serve it where you already work — no terminal, no API key:
Paste this URL into ChatGPT or Claude:
https://mcp.equibles.com/mcp
Approve access once. ChatGPT and Claude hold a short-lived OAuth token — nothing to copy, paste or rotate.
Step-by-step for every clientBuilding with code? The same 90+ tools work with an API key — over the MCP docs or the REST reference.