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FDIC BankFind MCP Server

Search Institution History / Structure Changes

fdic_search_history
Read-onlyIdempotent

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
certNoFilter by FDIC Certificate Number to get history for a specific institution
limitNoMaximum number of records to return (1-10000, default: 20)
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
offsetNoNumber of records to skip for pagination (default: 0)
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"
sort_byNoField name to sort results by. Example: ASSET, NAME, FAILDATE
sort_orderNoSort direction: ASC (ascending) or DESC (descending)ASC

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
totalYes
eventsYes
offsetYes
has_moreYes
truncatedNo
next_offsetNo

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by specifying the scope (structural changes) and the available filter dimensions, which helps set expectations. It does not describe pagination or rate limits, but that is less critical given the annotations.

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

Conciseness5/5

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

The description is two sentences. The first sentence front-loads the use case and filterable attributes; the second efficiently points to the full field catalog. There is zero wasted text.

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?

The description is sufficient for the tool's complexity. It covers purpose, key filter options, and provides a pointer to the field catalog. With a rich input schema, output schema, and annotations, nothing essential is missing for an AI agent to select and invoke the tool correctly.

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?

All 7 parameters have detailed descriptions in the schema (100% coverage), so the baseline is 3. The description mentions filter dimensions (CERT, type, change code, date range, state) but does not explain how to construct them beyond the schema's 'filters' parameter description. The added value is minimal.

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 explicitly states the tool is for retrieving structural-change events (mergers, acquisitions, name changes, charter conversions, failures) for FDIC-insured institutions. This clearly distinguishes it from sibling tools like fdic_search_failures (which focuses only on failures) and fdic_search_institutions (which covers general institution data).

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

Usage Guidelines4/5

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

It provides a clear when-to-use statement: 'Use this when the user wants structural-change events'. It also lists applicable filters (CERT, type, change code, date range, state) and references a schema for more detail. However, it does not explicitly state when NOT to use it or name alternative tools, so it lacks full exclusion/alternative guidance.

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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TDQS

A3.6/5.0
Disambiguation1/5

Several tools have overlapping purposes, including exact duplicates: fdic_fetch/fetch and fdic_search/search. Analytical tools also overlap (analyze_bank_health, ubpr_analysis, detect_risk_signals), making it hard for an agent to distinguish them.

Naming Consistency2/5

Most tools follow a fdic_verb_noun pattern, but two tools (fetch, search) lack the fdic_ prefix, breaking consistency. The verb style varies (get, search, analyze, compare, detect) but the prefix inconsistency is the main issue.

Tool Count2/5

At 29 tools, the server is over the typical limit and includes redundant pairs that inflate the count. The broad FDIC domain justifies many tools, but the duplicates indicate poor scoping.

Completeness4/5

The server covers all major FDIC data resources: institutions, failures, financials, branches, history, demographics, SOD, and summary, plus analytical tools. No major gaps are evident for its read-only data and analysis purpose.

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