🏦 Banking & Financial Stability MCP
Pricing
Pay per event + usage
🏦 Banking & Financial Stability MCP
MCP server: US banking & financial-stability data for AI agents — FDIC bank financials & health metrics, bank-regulator enforcement actions, and systemic-risk signals. Connect Claude/GPT to monitor bank soundness, supervision and financial-system stability.
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Pay per event + usage
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NexGenData
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One MCP connection. Bank health, regulator enforcement, and systemic-risk signals — agent-ready.
Banking & Financial Stability MCP is a Model Context Protocol server that gives any AI agent direct, structured access to the data that describes the health and supervision of the US financial system: FDIC bank financials, Federal Reserve and CFTC enforcement actions, CFPB consumer complaints and HMDA fair-lending data, FINRA broker disclosures, Reg SHO threshold lists, SEC fails-to-deliver, and global central-bank policy rates.
Connect once and call nine clean tools, each returning normalized JSON. This server covers institution-level health and supervision — it complements, rather than duplicates, our macro-series FRED + Treasury Macro MCP (which covers rates, yields, and economic indicators).
Why this exists
Financial-stability data is scattered across a dozen regulators — the FDIC, Federal Reserve, CFPB, CFTC, FINRA, and SEC — each with its own portal, format, and refresh cadence. Assembling a coherent view of a bank's health, its supervisory history, and the market-structure stress around it means stitching all of them together. This server does that once and exposes the result as agent-native tools, built on the same NexGenData infrastructure used by bank analysts, fintech risk teams, and financial journalists.
The nine tools
| Tool | What it does |
|---|---|
bank_financials | FDIC bank financial health & call-report metrics |
fed_enforcement | Federal Reserve enforcement actions against banks |
cftc_enforcement | CFTC enforcement (derivatives, swaps, commodities) |
cfpb_complaints | CFPB consumer-finance complaints by company/product |
hmda_fair_lending | HMDA mortgage data & fair-lending disparities |
finra_brokercheck | FINRA broker/firm registration & disclosures |
reg_sho_threshold | Reg SHO daily threshold securities (short/FTD pressure) |
fails_to_deliver | SEC fails-to-deliver settlement data |
central_bank_rates | Global central-bank policy rates (BIS) |
Every tool accepts a criteria object and a limit, returning a uniform {tool, count, total_available, results} envelope.
Quick start
{"mcpServers": {"banking-financial-stability": {"url": "https://nexgendata--banking-financial-stability-mcp.apify.actor/mcp","headers": { "Authorization": "Bearer YOUR_APIFY_TOKEN" }}}}
Call a tool:
{"name": "bank_financials","arguments": { "criteria": { "state": "TX" }, "limit": 25 }}
Common agent workflows
Bank-health screening. Run bank_financials across a state or peer group, then layer fed_enforcement to flag institutions under supervisory action — an early-warning view of stress.
Counterparty & vendor diligence. Combine finra_brokercheck, cfpb_complaints, and cftc_enforcement to assemble a firm's regulatory and complaint history in one pass.
Fair-lending analysis. Use hmda_fair_lending to surface lenders with statistically notable approval-rate disparities.
Market-structure stress. Pair reg_sho_threshold and fails_to_deliver to watch settlement pressure on specific tickers.
Rate context. Use central_bank_rates to anchor any of the above against the global monetary backdrop.
Pricing
Pay-per-event: $0.10 per tool call, $0.05 per bulk result (>10 records), negligible session-start fee. No subscription, no seat. An agent firing 200 queries a month costs about $20 — versus the enterprise pricing of S&P Global, Moody's, or Bloomberg's regulatory feeds.
How this compares
vs. S&P Global / Moody's / Bloomberg: enterprise seats built for human analysts. This is agent-native, priced per call, and returns machine-ready JSON.
vs. raw FDIC + Fed + CFPB + CFTC + FINRA + SEC portals: each is free but isolated, with its own format and rate limit. This unifies nine of them behind one schema and one connection.
vs. our FRED + Treasury Macro MCP: that one covers macro series (rates, yields, auctions). This one covers institution-level health and supervision. Use both together for a full picture.
Companion servers
- FRED + Treasury Macro Data MCP — macro series, yield curves, auctions.
- SEC Corporate Events MCP — market-moving filings.
- Legal & IP Intelligence MCP — litigation and enforcement detail.
FAQ
Do I need regulator API keys? No — only an Apify token for the MCP endpoint.
How fresh is the data? Each tool queries its source live at call time.
Can I filter by institution, state, or date? Yes — pass those in the criteria object; supported filters depend on the source.
Is this financial advice? No. This returns public regulatory and market data for informational use only — not investment or financial advice.
Is the schema stable? Yes — every tool returns the same envelope; we version changes.
Banking & Financial Stability MCP — by NexGenData. Bank health and supervision, agent-ready.
