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FDIC BankFind MCP Server

by jflamb

Search Annual Financial Summary Data

fdic_search_summary
Read-onlyIdempotent

Search annual financial summaries for FDIC-insured banks to track growth, analyze performance metrics, and compare institutions over time using filters like year, assets, and profitability.

Instructions

Search aggregate financial and structure summary data subtotaled by year for FDIC-insured institutions.

Returns annual snapshots of key financial metrics — useful for tracking an institution's growth over time.

Common filter examples:

  • Annual history for a bank: CERT:3511

  • Specific year: YEAR:2022

  • Year range: YEAR:[2010 TO 2020]

  • Large banks in 2022: YEAR:2022 AND ASSET:[10000000 TO *]

  • Profitable in 2023: YEAR:2023 AND ROE:[10 TO *]

Key returned fields:

  • CERT: FDIC Certificate Number

  • YEAR: Report year

  • ASSET: Total assets ($thousands)

  • DEP: Total deposits ($thousands)

  • NETINC: Net income ($thousands)

  • ROA: Return on assets (%)

  • ROE: Return on equity (%)

  • OFFICES: Number of branch offices

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

Args:

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

  • year (number, optional): Filter by specific year (1934-present)

  • 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 (e.g., YEAR, ASSET)

  • 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 annual summary 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
yearNoFilter by specific year (e.g., 2022)

Implementation Reference

  • The handler function for fdic_search_summary, which queries the FDIC summary endpoint and formats the results.
    async ({ cert, year, ...params }) => {
      try {
        const response = await queryEndpoint(ENDPOINTS.SUMMARY, {
          ...params,
          filters: buildFilterString({
            cert,
            dateField: "YEAR",
            dateValue: year,
            rawFilters: params.filters,
          }),
        });
        const records = extractRecords(response);
        const pagination = buildPaginationInfo(
          response.meta.total,
          params.offset ?? 0,
          records.length,
        );
        const output = { ...pagination, summary: records };
        const text = truncateIfNeeded(
          formatSearchResultText("annual summary records", records, pagination, [
            "CERT",
            "YEAR",
            "ASSET",
            "DEP",
            "NETINC",
  • Registration of the fdic_search_summary tool within the MCP server.
      server.registerTool(
        "fdic_search_summary",
        {
          title: "Search Annual Financial Summary Data",
          description: `Search aggregate financial and structure summary data subtotaled by year for FDIC-insured institutions.
    
    Returns annual snapshots of key financial metrics — useful for tracking an institution's growth over time.
    
    Common filter examples:
      - Annual history for a bank: CERT:3511
      - Specific year: YEAR:2022
      - Year range: YEAR:[2010 TO 2020]
      - Large banks in 2022: YEAR:2022 AND ASSET:[10000000 TO *]
      - Profitable in 2023: YEAR:2023 AND ROE:[10 TO *]
    
    Key returned fields:
      - CERT: FDIC Certificate Number
      - YEAR: Report year
      - ASSET: Total assets ($thousands)
      - DEP: Total deposits ($thousands)
      - NETINC: Net income ($thousands)
      - ROA: Return on assets (%)
      - ROE: Return on equity (%)
      - OFFICES: Number of branch offices
      - REPDTE: Report Date — the last day of the reporting period (YYYYMMDD)
    
    Args:
      - cert (number, optional): Filter by institution CERT number
      - year (number, optional): Filter by specific year (1934-present)
      - 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 (e.g., YEAR, ASSET)
      - 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 annual summary records.`,
          inputSchema: SummaryQuerySchema,
          annotations: {
            readOnlyHint: true,
            destructiveHint: false,
            idempotentHint: true,
            openWorldHint: true,
          },
        },
  • Zod schema definition for the fdic_search_summary tool's input arguments.
    const SummaryQuerySchema = CommonQuerySchema.extend({
      cert: z
        .number()
        .int()
        .positive()
        .optional()
        .describe("Filter by FDIC Certificate Number"),
      year: z
        .number()
        .int()
        .min(1934)
        .optional()
        .describe("Filter by specific year (e.g., 2022)"),
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, covering safety and idempotency. The description adds valuable context about return format ('annual snapshots of key financial metrics'), common use cases with filter examples, and output guidance ('Prefer concise human-readable summaries or tables'). However, it doesn't mention rate limits or authentication requirements.

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 statement, usage context, filter examples, returned fields, parameters, and output guidance. It's appropriately sized for the tool's complexity, though the parameter listing could be more concise given the comprehensive schema coverage.

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

Completeness5/5

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 excellent context: clear purpose, usage guidelines, detailed filter examples, key returned fields, and output format guidance. The annotations cover behavioral aspects, and the description complements them well without needing to explain return values in detail.

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?

Schema description coverage is 100%, so the schema already documents all 8 parameters thoroughly. The description lists parameters in the 'Args' section but adds minimal semantic value beyond what's in the schema. It does provide context about filter syntax through examples, but this is largely redundant with schema descriptions.

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's purpose: 'Search aggregate financial and structure summary data subtotaled by year for FDIC-insured institutions.' It specifies the verb ('search'), resource ('annual financial summary data'), and scope ('FDIC-insured institutions'), distinguishing it from siblings like fdic_search_financials or fdic_search_institutions by focusing on annual snapshots.

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

Usage Guidelines5/5

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

The description explicitly provides usage context: 'useful for tracking an institution's growth over time' and includes common filter examples that illustrate when to use this tool. It also distinguishes from siblings by mentioning 'annual snapshots' versus other tools that might handle different data types or timeframes.

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

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