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Fdic Banks MCP Server

io.github.cyanheads/fdic-banks-mcp-server

Search FDIC-insured banks, Call Report financials, peer rankings, failures, deposit market share.

Yes, your AI can use this right now.Answered a live MCP handshake in 327 ms with no sign-in needed and exposes 9 tools.

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URL: https://fdic-banks.caseyjhand.com/mcp

9 tools, verified live

Pulled straight from the server with tools/list on 2026-10-17.
fdic_search_institutionsread-only

Find FDIC-insured banks and savings institutions by name, CERT, location, size, charter class, or holding company — including closed, merged, and failed institutions. Name matching is fuzzy, case-insensitive, and also matches former and trade names (a result says which it matched); every word must match. Returns institution records keyed by CERT, the FDIC certificate number every other fdic_ too

fdic_get_institution_financialsread-only

Get one institution's quarterly Call Report financials by CERT — balance sheet, income, returns, credit quality, and capital ratios — most recent quarter first, with its name, status, and holding company. Unsuffixed income and return metrics are single-quarter figures; _ytd metrics accumulate from January 1. Dollar amounts are in thousands. Quarterly data lands about seven weeks after quarter

fdic_compare_peersread-only

Compare one institution with a peer group for one quarter: for each metric, the institution's value next to the peer median, quartiles, minimum and maximum, and its percentile and rank. The default peer group is every institution in the same asset-size band that reported that quarter; narrow it to one state, widen it to all sizes, or name the peers by CERT. Dollar amounts are in thousands; ratios

fdic_query_financialsread-only

Pull a multi-institution, multi-quarter Call Report panel — one row per institution per quarter — filtered by CERTs, headquarters state, asset range, and thresholds on any catalog metric. Use it to screen (every bank in a state with a noncurrent-loan rate above 3%) or to build a trend panel for SQL. Returns an inline preview sorted as requested; when the panel exceeds the preview it is staged

fdic_search_failuresread-only

Search FDIC-insured bank failures and assistance transactions since 1934 by name, CERT, headquarters state, failure date range, resolution method, or size. Returns each event with failure date, acquirer, total assets and deposits, and the FDIC's estimated loss to the insurance fund, plus totals over every matching event; group_by adds counts and losses per year, state, method, or fund. Searches fa

fdic_get_depositsread-only

Get Summary of Deposits data (branch-level domestic deposits, annual as of June 30, 1994 onward). With cert only: the institution's branches and its deposit market share in each state where it has offices. With a geography (state, county, city, ZIP, or MSA code): every institution in that market ranked by deposits, with market share and the Herfindahl-Hirschman index. With both: the institution's

fdic_list_referenceread-only

List the vocabulary the other fdic_ tools accept and return: every financial metric name with its FDIC field, unit, and basis (single quarter, year-to-date, or point in time), bank charter classes, failure resolution methods, insurance funds, the asset bands fdic_compare_peers uses, and the years each dataset covers. Served from built-in tables; no request to FDIC.

fdic_dataframe_describeread-only

Describe the df_<id> dataframes that fdic_query_financials and fdic_get_deposits staged when a result exceeded its inline preview, plus any that fdic_dataframe_query saved with register_as. Pass name (from a dataset field) for one dataframe in full: source tool, the parameters it was called with, row count, creation and expiry time, column schema, and the unit and basis of each amount, ratio, or c

fdic_dataframe_queryread-only

Run one read-only SELECT (DuckDB SQL) across the df_<id> dataframes that fdic_query_financials and fdic_get_deposits staged or an earlier register_as saved; joins, aggregates, window functions, and CTEs work. Before writing SQL, pass each table name to fdic_dataframe_describe to read its columns. DOUBLE columns come back as JSON numbers and dollar columns are thousands of US dollars; BIGINT result

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