Skip to main content
Glama
jflamb

FDIC BankFind MCP Server

by jflamb

Search Institution Demographics Data

fdic_search_demographics
Read-onlyIdempotent

Search quarterly demographic data for FDIC-insured banks to analyze office locations, geographic classifications, and market structure using filters like certificate numbers, report dates, and metro areas.

Instructions

Search BankFind demographics data for FDIC-insured institutions.

Returns quarterly demographic and market-structure attributes such as office counts, territory assignments, metro classification, county/country codes, and selected geographic reference data.

Common filter examples:

  • Demographics for a specific bank: CERT:3511

  • By report date: REPDTE:20251231

  • Institutions in metro areas: METRO:1

  • Institutions with out-of-state offices: OFFSTATE:[1 TO *]

  • Minority status date present: MNRTYDTE:[19000101 TO 99991231]

Key returned fields:

  • CERT: FDIC Certificate Number

  • REPDTE: Report Date — the last day of the quarterly reporting period (YYYYMMDD)

  • QTRNO: Quarter number

  • OFFTOT: Total offices

  • OFFSTATE: Offices in other states

  • OFFNDOM: Offices in non-domestic territories

  • OFFOTH: Other offices

  • OFFSOD: Offices included in Summary of Deposits

  • METRO, MICRO: Metro/micro area flags

  • CBSANAME, CSA: Core-based statistical area data

  • FDICTERR, RISKTERR: FDIC and risk territory assignments

  • SIMS_LAT, SIMS_LONG: Geographic coordinates

Args:

  • cert (number, optional): Filter by institution CERT number

  • repdte (string, optional): Report Date in YYYYMMDD format (quarter-end dates: 0331, 0630, 0930, 1231)

  • filters (string, optional): Additional ElasticSearch query filters

  • fields (string, optional): Comma-separated field names

  • limit (number): Records to return (default: 20)

  • offset (number): Pagination offset (default: 0)

  • sort_by (string, optional): Field to sort by

  • sort_order ('ASC'|'DESC'): Sort direction (default: 'ASC')

Prefer concise human-readable summaries or tables when answering users. Structured fields are available for totals, pagination, and demographic records.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filtersNoFDIC API filter using ElasticSearch query string syntax. Combine conditions with AND/OR, use quotes for multi-word values, and [min TO max] for ranges (* = unbounded). Common fields: NAME (institution name), STNAME (state name), STALP (two-letter state code), CERT (certificate number), ASSET (total assets in $thousands), ACTIVE (1=active, 0=inactive). Examples: STNAME:"California", ACTIVE:1 AND ASSET:[1000000 TO *], NAME:"Chase"
fieldsNoComma-separated list of FDIC field names to return. Leave empty to return all fields. Field names are ALL_CAPS (e.g., NAME, CERT, ASSET, DEP, STALP). Example: NAME,CERT,ASSET,DEP,STALP
limitNoMaximum number of records to return (1-10000, default: 20)
offsetNoNumber of records to skip for pagination (default: 0)
sort_byNoField name to sort results by. Example: ASSET, NAME, FAILDATE
sort_orderNoSort direction: ASC (ascending) or DESC (descending)ASC
certNoFilter by FDIC Certificate Number
repdteNoFilter by Report Date (REPDTE) in YYYYMMDD format. FDIC data is published quarterly on: March 31, June 30, September 30, and December 31. Example: 20251231 for Q4 2025. If omitted, returns all available dates.

Implementation Reference

  • Registration of the fdic_search_demographics tool using the McpServer instance.
    export function registerDemographicsTools(server: McpServer): void {
      server.registerTool(
        "fdic_search_demographics",
        {
          title: "Search Institution Demographics Data",
          description: `Search BankFind demographics data for FDIC-insured institutions.
    
    Returns quarterly demographic and market-structure attributes such as office counts, territory assignments, metro classification, county/country codes, and selected geographic reference data.
    
    Common filter examples:
      - Demographics for a specific bank: CERT:3511
      - By report date: REPDTE:20251231
      - Institutions in metro areas: METRO:1
      - Institutions with out-of-state offices: OFFSTATE:[1 TO *]
      - Minority status date present: MNRTYDTE:[19000101 TO 99991231]
    
    Key returned fields:
      - CERT: FDIC Certificate Number
      - REPDTE: Report Date — the last day of the quarterly reporting period (YYYYMMDD)
      - QTRNO: Quarter number
      - OFFTOT: Total offices
      - OFFSTATE: Offices in other states
      - OFFNDOM: Offices in non-domestic territories
      - OFFOTH: Other offices
      - OFFSOD: Offices included in Summary of Deposits
      - METRO, MICRO: Metro/micro area flags
      - CBSANAME, CSA: Core-based statistical area data
      - FDICTERR, RISKTERR: FDIC and risk territory assignments
      - SIMS_LAT, SIMS_LONG: Geographic coordinates
    
    Args:
      - cert (number, optional): Filter by institution CERT number
      - repdte (string, optional): Report Date in YYYYMMDD format (quarter-end dates: 0331, 0630, 0930, 1231)
      - filters (string, optional): Additional ElasticSearch query filters
      - fields (string, optional): Comma-separated field names
      - limit (number): Records to return (default: 20)
      - offset (number): Pagination offset (default: 0)
      - sort_by (string, optional): Field to sort by
      - sort_order ('ASC'|'DESC'): Sort direction (default: 'ASC')
    
    Prefer concise human-readable summaries or tables when answering users. Structured fields are available for totals, pagination, and demographic records.`,
          inputSchema: DemographicsQuerySchema,
          annotations: {
            readOnlyHint: true,
            destructiveHint: false,
            idempotentHint: true,
            openWorldHint: true,
          },
        },
        async ({ cert, repdte, ...params }) => {
          try {
            const response = await queryEndpoint(ENDPOINTS.DEMOGRAPHICS, {
              ...params,
              filters: buildFilterString({
                cert,
                dateField: "REPDTE",
                dateValue: repdte,
                rawFilters: params.filters,
              }),
            });
            const records = extractRecords(response);
            const pagination = buildPaginationInfo(
              response.meta.total,
              params.offset ?? 0,
              records.length,
            );
            const output = { ...pagination, demographics: records };
            const text = truncateIfNeeded(
              formatSearchResultText("demographic records", records, pagination, [
                "CERT",
                "REPDTE",
                "OFFTOT",
                "OFFSTATE",
                "METRO",
                "CBSANAME",
              ]),
              CHARACTER_LIMIT,
              "Request fewer fields, narrow your filters, or paginate with limit/offset.",
            );
            return {
              content: [{ type: "text", text }],
              structuredContent: output,
            };
          } catch (err) {
            return formatToolError(err);
          }
        },
      );
    }
  • The handler function for fdic_search_demographics, which calls the fdicClient to query demographic data.
    async ({ cert, repdte, ...params }) => {
      try {
        const response = await queryEndpoint(ENDPOINTS.DEMOGRAPHICS, {
          ...params,
          filters: buildFilterString({
            cert,
            dateField: "REPDTE",
            dateValue: repdte,
            rawFilters: params.filters,
          }),
        });
        const records = extractRecords(response);
        const pagination = buildPaginationInfo(
          response.meta.total,
          params.offset ?? 0,
          records.length,
        );
        const output = { ...pagination, demographics: records };
        const text = truncateIfNeeded(
          formatSearchResultText("demographic records", records, pagination, [
            "CERT",
            "REPDTE",
            "OFFTOT",
            "OFFSTATE",
            "METRO",
            "CBSANAME",
          ]),
          CHARACTER_LIMIT,
          "Request fewer fields, narrow your filters, or paginate with limit/offset.",
        );
        return {
          content: [{ type: "text", text }],
          structuredContent: output,
        };
      } catch (err) {
        return formatToolError(err);
      }
    },
  • Input schema (DemographicsQuerySchema) for fdic_search_demographics, validating cert and repdte parameters.
    const DemographicsQuerySchema = CommonQuerySchema.extend({
      cert: z
        .number()
        .int()
        .positive()
        .optional()
        .describe("Filter by FDIC Certificate Number"),
      repdte: z
        .string()
        .optional()
        .describe(
          "Filter by Report Date (REPDTE) in YYYYMMDD format. FDIC data is published quarterly on: March 31, June 30, September 30, and December 31. Example: 20251231 for Q4 2025. If omitted, returns all available dates.",
        ),
    });
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate this is a read-only, non-destructive, idempotent operation with open-world data. The description adds valuable context by specifying the data is 'quarterly' and providing concrete examples of what gets returned (office counts, territory assignments, geographic data). It also mentions pagination behavior through limit/offset parameters and suggests output format preferences ('prefer concise human-readable summaries or tables').

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (purpose, returns, examples, key fields, parameters, output guidance). While somewhat lengthy, each section serves a purpose. The front-loaded purpose statement is clear, and the information is organized efficiently without obvious redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (8 parameters, no output schema), the description provides substantial context about what data is returned, common usage patterns, and output preferences. With annotations covering safety aspects and schema covering parameters, the description fills important gaps about data characteristics (quarterly, demographic focus) and practical usage. The main gap is lack of explicit sibling tool differentiation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the schema already documents all 8 parameters thoroughly. The description adds minimal value beyond the schema - it lists parameters in the 'Args' section but provides less detail than the schema descriptions. The 'common filter examples' section does offer helpful usage patterns but doesn't significantly enhance parameter understanding beyond what's in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool searches 'BankFind demographics data for FDIC-insured institutions' and specifies it returns 'quarterly demographic and market-structure attributes.' This distinguishes it from sibling tools like fdic_search_financials or fdic_search_failures by focusing specifically on demographic data rather than financial metrics or failure information.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides implied usage through 'common filter examples' that suggest when to use certain parameters, but it doesn't explicitly state when to choose this tool over alternatives like fdic_search_institutions or fdic_get_institution. The guidance is practical but lacks direct comparison with sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jflamb/fdic-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server