FDIC BankFind MCP Server

Produce a CAMELS-style analytical assessment for a single FDIC-insured institution using the public off-site proxy model. Scores five components — Capital (C), Asset Quality (A), Earnings (E), Liquidity (L), Sensitivity (S) — using published FDIC financial data and derives a weighted composite rating (1=Strong to 5=Unsatisfactory), plus a proxy model overall band (1.0–4.0 scale). Output includes: - Composite and component ratings with individual metric scores - Proxy model overall assessment band with capital classification - Management overlay assessment (inferred from public data patterns) - Trend analysis across prior quarters for key metrics - Risk signals flagging critical and warning-level concerns - Structured JSON for programmatic consumption (legacy + proxy fields) NOTE: Management (M) is omitted from component scoring — cannot be assessed from public data. Sensitivity (S) uses proxy metrics (NIM trend, securities concentration). This is a public off-site analytical proxy, not an official CAMELS rating.

Analyze loan portfolio composition and credit concentration risk for an FDIC-insured institution. Computes CRE concentration relative to capital (per 2006 interagency guidance), loan-type breakdown, and flags concentration risks. Output includes: - Loan portfolio composition (CRE, C&I, consumer, residential, agricultural shares) - CRE and construction concentration relative to total capital - Loan-to-asset ratio - Concentration risk signals based on interagency guidance thresholds - Structured JSON for programmatic consumption NOTE: This is an analytical tool based on public financial data.

Analyze deposit composition, wholesale funding reliance, and funding risk for an FDIC-insured institution. Output includes: - Deposit composition (core, brokered, foreign deposit shares) - Wholesale funding reliance and FHLB advances relative to assets - Cash ratio for near-term liquidity - Funding risk signals based on supervisory thresholds - Structured JSON for programmatic consumption NOTE: This is an analytical tool based on public financial data.

Analyze securities portfolio size, composition, and concentration risk for an FDIC-insured institution. Output includes: - Securities relative to total assets and capital - MBS concentration within the securities portfolio - AFS/HTM breakdown (when available) - Risk signals for portfolio concentration and interest rate exposure - Structured JSON for programmatic consumption NOTE: This is an analytical tool based on public financial data. AFS/HTM breakdown is not currently available from the FDIC API.

Compare FDIC reporting snapshots across a set of institutions and rank the results by growth, profitability, or efficiency changes. This tool is designed for heavier analytical prompts that would otherwise require many separate MCP calls. It batches institution roster lookup, financial snapshots, optional office-count snapshots, and can also fetch a quarterly time series inside the server. Good uses: - Identify North Carolina banks with the strongest asset growth from 2021 to 2025 - Compare whether deposit growth came with branch expansion or profitability improvement - Rank a specific cert list by ROA, ROE, asset-per-office, or deposit-to-asset changes - Pull a quarterly trend series and highlight inflection points, streaks, and structural shifts Inputs: - state or certs: choose a geographic roster or provide a direct comparison set - start_repdte, end_repdte: Report Dates (REPDTE) in YYYYMMDD format — must be quarter-end dates (0331, 0630, 0930, 1231) - analysis_mode: snapshot or timeseries - institution_filters: optional extra institution filter when building the roster - active_only: default true - include_demographics: default true, adds office-count comparisons when available - sort_by: ranking field (default: asset_growth). All options: asset_growth, asset_growth_pct, dep_growth, dep_growth_pct, netinc_change, netinc_change_pct, roa_change, roe_change, offices_change, assets_per_office_change, deposits_per_office_change, deposits_to_assets_change - sort_order: ASC or DESC - limit: maximum ranked results to return Returns concise comparison text plus structured deltas, derived metrics, and insight tags for each institution.

Compare CAMELS-style health scores across a group of FDIC-insured institutions. Three usage modes: - Explicit list: provide certs (up to 50) for a specific comparison set - State-wide scan: provide state to compare all active institutions in that state - Asset-based: provide asset_min/asset_max to compare institutions by size Optionally provide cert to highlight a subject institution's position in the ranking. Output: structuredContent includes {model, official_status, report_date, institutions, metrics, peer_context, proxy_summary, proxy, deprecations}. Institutions include proxy scores and name_source. When a subject cert is provided, metrics[] is the preferred subject-vs-peer array for new UI bindings and proxy_summary is a flattened subject proxy. peer_context.subject_percentiles is deprecated, remains for backward compatibility, and is targeted for removal only in a future coordinated major release. Auto-peer selection derives asset bands from report-date financials and broadens the cohort if fewer than 10 peers match. NOTE: Public off-site analytical proxy — not official supervisory ratings.

Scan FDIC-insured institutions for early warning risk signals using the public_camels_proxy_v1 analytical engine. Standardized signal codes with severity levels: - Critical: capital_undercapitalized (PCA breach), earnings_loss (ROA < 0), reserve_coverage_low (< 50%) - Warning: capital_buffer_erosion, credit_deterioration, credit_deterioration_trending, earnings_pressure, margin_compression, funding_stress, funding_ltd_stretched, rate_risk_proxy_elevated, wholesale_funding_elevated - Info: merger_distorted_trend, stale_reporting_period Three scan modes: - State-wide: provide state to scan all active institutions - Explicit list: provide certs (up to 50) - Asset-based: provide asset_min/asset_max Output: Per-institution risk signals ranked by severity count. The proxy engine drives signal generation internally; the output is signal-shaped, not assessment-shaped. NOTE: Public off-site analytical proxy — not official supervisory ratings.

Use this when the model needs the full citation text for a result returned by search. Pass the search result id (e.g. 'institution:3511', 'failure:1234', 'branch:<UNINUM>', 'schema:institutions').

Analyze the geographic franchise footprint of an FDIC-insured institution using Summary of Deposits (SOD) data. Shows how an institution's branches and deposits are distributed across metropolitan statistical areas (MSAs), providing a market-by-market breakdown of branch count, deposit totals, and percentage of the institution's total deposits. Output includes: - Total branch count, deposits, and market count - Market-by-market breakdown sorted by deposits - Structured JSON for programmatic consumption Branches outside MSAs are grouped under "Non-MSA / Rural".

Use this when the user knows an exact FDIC Certificate Number and needs one institution profile. To discover a CERT first, call fdic_search_institutions or fdic_search.

Use this when the user knows the CERT of a failed institution and needs its specific failure record. Returns failure details (date, resolution type, estimated DIF cost in the COST field, acquirer); responds with `found: false` if the institution did not fail.

Profile a bank holding company by grouping its FDIC-insured subsidiaries and aggregating financial metrics. Look up by holding company name or by any subsidiary's CERT number. Output includes: - Consolidated summary with total assets, deposits, and asset-weighted ROA/equity ratio - List of all FDIC-insured subsidiaries with individual metrics - Structured JSON for programmatic consumption NOTE: This is an analytical tool based on public financial data.

Analyze deposit market share and concentration for an MSA or city market using FDIC Summary of Deposits (SOD) data. Computes market share for all institutions in a geographic market, ranks them by deposits, and calculates the Herfindahl-Hirschman Index (HHI) for market concentration analysis per DOJ/FTC merger guidelines. Two entry modes: - MSA market: provide msa as the numeric MSABR code (e.g., msa: 19100 for Dallas-Fort Worth-Arlington, msa: 42660 for Seattle-Tacoma-Bellevue). Use fdic_search_sod to look up MSABR codes. - City market: provide city (branch city name, e.g., "Austin") and state (two-letter code, e.g., "TX"). Output includes: - Market overview with total deposits, institution count, and HHI classification - Optional highlighted institution showing rank and share (provide cert) - Top institutions ranked by deposit market share - Structured JSON for programmatic consumption Requires at least one of: msa (numeric MSABR code), or city + state.

Build a peer group for an FDIC-insured institution and rank it against peers on financial and efficiency metrics at a single report date. Three usage modes: - Subject-driven: provide cert and repdte — auto-derives peer criteria from the subject's asset size and charter class - Explicit criteria: provide repdte plus asset_min/asset_max, charter_classes, state, or raw_filter - Subject with overrides: provide cert plus explicit criteria to override auto-derived defaults Metrics ranked (fixed order): - Total Assets, Total Deposits, ROA, ROE, Net Interest Margin - Equity Capital Ratio, Efficiency Ratio, Loan-to-Deposit Ratio - Deposits-to-Assets Ratio, Non-Interest Income Share Rankings use competition rank (1, 2, 2, 4). Rank, denominator, and percentile all use the same comparison set: matched peers plus the subject institution. Output includes: - Subject rankings and percentiles (when cert provided) - Peer group medians - Peer list with CERTs (pass to fdic_compare_bank_snapshots for trend analysis) - Metric definitions with directionality metadata Override precedence: cert derives defaults, then explicit params override them.

Build chart-ready data for a concise QBP Lite report from reproducible public BankFind quarterly financials. Includes executive snapshot metrics, trend series, community-bank comparison data, source notes, and explicit exclusions for non-public or non-BankFind QBP items.

Overlay macro/regional economic data on a bank's geographic context. Uses FRED (Federal Reserve Economic Data) for state unemployment, national unemployment, and federal funds rate. Provides trend analysis and narrative context for bank performance assessment. Gracefully degrades if FRED API is unavailable. Output includes: - State and national unemployment rates with trend analysis - Federal funds rate and rate environment classification - Narrative assessment of macro conditions for bank performance - Structured JSON for programmatic consumption NOTE: Requires FRED_API_KEY environment variable for reliable data access. Degrades gracefully without it.

Use this when the model needs citation-friendly FDIC BankFind search results for institutions, failed banks, branches, or schema documentation. Returns up to 8 results with id, title, and source URL.

Use this when the user wants quarterly demographic and market-structure attributes (office counts, metro classification, county/territory codes, geographic reference data) for FDIC-insured institutions. Filter by CERT and/or REPDTE. See fdic://schemas/demographics for the full field catalog.

Use this when the user wants details on failed FDIC-insured institutions filtered by name, state, date range, resolution type, estimated loss, or DIF cost. The failures field for estimated loss (DIF cost) is COST; for highest-cost failures use sort_by: COST and sort_order: DESC. Do not use ESTIMATED_LOSS. Returns failure records with pagination; see fdic://schemas/failures for the full field catalog.

Use this when the user wants quarterly Call Report data (balance sheet, income, capital, performance ratios) for FDIC-insured institutions. Filter by CERT and/or REPDTE plus optional ElasticSearch filters. See fdic://schemas/financials for the full 1,100+ field catalog.

Use this when the user wants structural-change events (mergers, acquisitions, name changes, charter conversions, failures) for FDIC-insured institutions, filtered by CERT, type, change code, date range, or state. See fdic://schemas/history for the full field catalog.

Use this when the user needs FDIC-insured institution search results by name, state, CERT, asset size, charter class, or regulatory status. Returns institution profile rows with pagination; use fdic://schemas/institutions for the full field catalog.

Use this when the user wants branch/office locations for FDIC-insured institutions, filtered by CERT, state, city, county, metro area, or branch type. Returns address, coordinates, branch number, and service-type rows; see fdic://schemas/locations for the full field catalog.

Use this when the user wants annual branch-level deposit data (SOD, as of June 30 each year) — branch deposits, MSAs, geographic distribution. Filter by CERT and/or year. See fdic://schemas/sod for the full field catalog.

Use this when the user wants annual financial-summary snapshots (assets, deposits, ROA, ROE, offices) for FDIC-insured institutions, filtered by CERT and/or year. See fdic://schemas/summary for the full field catalog.

Use this when the user wants a scannable single-institution dashboard with identity, public financial metrics, risk signals, and source links. ChatGPT renders an interactive widget; Claude and other MCP clients render the same data as a Markdown table.

Compute UBPR-equivalent ratio analysis for an FDIC-insured institution. Includes summary ratios (ROA, ROE, NIM, efficiency), loan mix, capital adequacy, liquidity metrics, and year-over-year growth rates. Ratios are computed from Call Report data and are UBPR-equivalent, not official FFIEC UBPR output. Output includes: - Summary ratios: ROA, ROE, NIM, efficiency ratio, pretax ROA - Loan mix: real estate, commercial, consumer, agricultural shares - Capital adequacy: Tier 1 leverage, Tier 1 risk-based, equity ratio - Liquidity: loan-to-deposit, core deposit ratio, brokered deposits, cash ratio - Year-over-year growth: assets, loans, deposits - Structured JSON for programmatic consumption NOTE: This is an analytical tool based on public financial data.

Use this when the model needs the full citation text for a result returned by search. Pass the search result id (e.g. 'institution:3511', 'failure:1234', 'branch:<UNINUM>', 'schema:institutions').

Use this when the model needs citation-friendly FDIC BankFind search results for institutions, failed banks, branches, or schema documentation. Returns up to 8 results with id, title, and source URL.