What it does
This is a Model Context Protocol (MCP) server that gives any AI agent direct, structured access to the data describing the health and supervision of the US financial system. Connect once and call nine clean tools - each returning normalized JSON - instead of stitching together a dozen regulator portals with different formats and refresh cadences.
Who it's for
Bank and credit analysts, fintech risk teams, AI-agent builders, and financial journalists who need institution-level bank health and supervisory history exposed as agent-native tools.
Sample fields / output
-
bank_financials- FDIC call-report health metrics -
fed_enforcement/cftc_enforcement- regulator enforcement actions -
cfpb_complaints+ HMDA fair-lending data - FINRA broker disclosures
- Reg SHO threshold lists & SEC fails-to-deliver
- global central-bank policy rates
Example use cases
- Give an AI agent live, structured bank-health and call-report lookups.
- Screen a bank's supervisory and enforcement history across the FDIC, Fed, CFTC and CFPB at once.
- Monitor market-structure stress via Reg SHO threshold lists and SEC fails-to-deliver.
Run Banking & Financial Stability MCP on Apify ->
Related actors: FDIC Bank Leads, FINRA BrokerCheck Search, FRED + Treasury Macro MCP
FAQ
What is MCP?
Model Context Protocol - an open standard that lets AI agents call external tools. This server exposes nine financial-stability tools any MCP-compatible agent can use.
What does it cover that a macro feed doesn't?
Institution-level health and supervision - individual bank financials, enforcement actions and broker disclosures - complementing macro-series feeds like FRED + Treasury rates.
How many tools does it expose?
Nine, spanning FDIC bank financials, Fed/CFTC enforcement, CFPB complaints + HMDA, FINRA disclosures, Reg SHO, SEC fails-to-deliver and central-bank rates.
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