FDIC BankFind MCP Server

Analyze Funding Profile

fdic_analyze_funding_profile

Read-onlyIdempotent

Analyze deposit composition, wholesale funding reliance, and funding risk for FDIC-insured institutions. Returns structured JSON with risk signals based on supervisory thresholds.

Instructions

Analyze deposit composition, wholesale funding reliance, and funding risk for an FDIC-insured institution.

Output includes:

Deposit composition (core, brokered, foreign deposit shares)
Wholesale funding reliance and FHLB advances relative to assets
Cash ratio for near-term liquidity
Funding risk signals based on supervisory thresholds
Structured JSON for programmatic consumption

NOTE: This is an analytical tool based on public financial data.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`cert`	Yes	FDIC Certificate Number
`repdte`	No	Report date (YYYYMMDD). Defaults to most recent quarter.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv3.0.1Sep 22, 2026

changedInput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

addedInput schema / properties / cert / maximum
```
Added value: +9007199254740991
```

changedOutput schema / $schema

Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"

changedOutput schema / additionalProperties
```
Previous value: -trueNew value: +{}
```

Addedv1.26.0May 1, 2026

TDQS

A4/5.0

Behavior4/5

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

Annotations already establish readOnlyHint, idempotentHint, and non-destructive behavior, lowering the burden on the description. The description adds useful context by stating this is an analytical tool based on public financial data and that it produces derived risk signals based on supervisory thresholds.

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 compact and front-loaded with the core purpose, followed by a scannable bulleted output list and a brief note about data provenance. Every line contributes useful information without 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 output schema, annotations, and complete parameter schema, the description covers the essential context: what the tool analyzes, what it returns, and that it uses public data. Minor gaps like explicit threshold caveats or data vintage are not critical for correct invocation.

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 cert and repdte are already fully documented. The description does not add further parameter-level meaning, but it also does not need to; baseline 3 is appropriate.

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 uses a specific verb ('Analyze') with a clear resource ('funding profile') and enumerates concrete outputs such as deposit composition, wholesale funding reliance, and FHLB advances. This differentiates it from sibling analysis tools like fdic_analyze_securities_portfolio or fdic_analyze_credit_concentration.

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 implies the tool should be used when funding composition and funding risk are the focus, but it does not explicitly state when to choose this over sibling analytical tools. No exclusions or alternative routing are provided, so the usage context is only implicit.

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