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jflamb

FDIC BankFind MCP Server

by jflamb

Search FDIC BankFind

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Read-onlyIdempotent

Find FDIC-insured institutions, failed banks, branches, and schema documentation. Returns up to 8 cited results with titles and source URLs.

Instructions

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.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural-language search query.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv3.0.1
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • changedOutput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
  2. Addedv1.26.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already provide readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, which cover safety and side-effect behavior. The description adds value by specifying the result count limit ('up to 8 results') and the fields returned ('id, title, and source URL'), which is behavioral context not in annotations. No contradiction with annotations; the description emphasizes it is a read-only search, consistent with 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, front-loads the purpose and context, and every sentence adds useful information. No fluff or repetition of schema details. It is concise and well-structured.

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 has only one parameter, a simple safety profile (annotations), and an output schema that likely describes the result structure, the description is sufficient. It specifies the output format (id, title, URL) and result limit, which is complete for an agent to call it correctly. No additional complexity requires more 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%, as the 'query' parameter is well-described in the schema with 'Natural-language search query.' The description adds minimal value beyond that, only implying the search is natural-language. Since coverage is high, the baseline is 3, and the description doesn't need to add more.

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 states a specific verb ('Search'), a specific resource ('FDIC BankFind'), and the types of results ('institutions, failed banks, branches, or schema documentation'). It also mentions the purpose ('citation-friendly') which distinguishes it from generic search tools. This clearly differentiates it from siblings like 'fetch' or the many analysis tools.

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 says 'Use this when the model needs citation-friendly FDIC BankFind search results', which gives a clear context for use. However, it does not explicitly state when not to use it or mention alternatives like 'fetch' or the specific search siblings (e.g., fdic_search_institutions). The guidance is decent but lacks explicit exclusions or comparisons to alternatives.

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