FDIC BankFind MCP Server

Analyze Bank Health (CAMELS-Style)

fdic_analyze_bank_health

Read-onlyIdempotent

Assess a bank's financial health using public FDIC data, producing a CAMELS-style composite rating, component scores, trend analysis, and risk signals. Ideal for off-site monitoring without official ratings.

Instructions

Produce a CAMELS-style analytical assessment for a single FDIC-insured institution using the public off-site proxy model.

Scores five components — Capital (C), Asset Quality (A), Earnings (E), Liquidity (L), Sensitivity (S) — using published FDIC financial data and derives a weighted composite rating (1=Strong to 5=Unsatisfactory), plus a proxy model overall band (1.0–4.0 scale).

Output includes:

Composite and component ratings with individual metric scores
Proxy model overall assessment band with capital classification
Management overlay assessment (inferred from public data patterns)
Trend analysis across prior quarters for key metrics
Risk signals flagging critical and warning-level concerns
Structured JSON for programmatic consumption (legacy + proxy fields)

NOTE: Management (M) is omitted from component scoring — cannot be assessed from public data. Sensitivity (S) uses proxy metrics (NIM trend, securities concentration). This is a public off-site analytical proxy, not an official CAMELS rating.

Input Schema

TableJSON Schema

Name	Required	Description
`cert`	Yes	FDIC Certificate Number of the institution to analyze.
`repdte`	No	Report Date (YYYYMMDD). Defaults to the most recent quarter likely to have published data.
`quarters`	No	Number of prior quarters to fetch for trend analysis (default 8).

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

A4.4/5.0

Behavior5/5

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

Beyond the annotations (readOnlyHint, idempotentHint, destructiveHint=false), the description discloses that this is a public off-site proxy, not an official CAMELS rating, that Management (M) is omitted because it cannot be assessed from public data, and that Sensitivity uses proxy metrics. These caveats are crucial for setting expectations and are not present in annotations. No contradiction.

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 long but well-structured with bullet points, front-loading the main purpose and then listing outputs and caveats. Every sentence adds value—there is no filler. It could be slightly trimmed, but the length is justified given the analytical complexity.

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?

With an output schema present, the description appropriately lists the key outputs (composite ratings, risk signals, structured JSON) and clearly states limitations (proxy model, no M component). This is complete for an agent to decide whether to invoke the tool and to interpret the results.

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?

The input schema already provides descriptions for all three parameters (cert, repdte, quarters) with 100% coverage, so the description adds minimal new meaning. It does mention that quarters is for 'trend analysis' and that repdte defaults to the most recent quarter, which slightly reinforces the schema. This meets the baseline for full schema coverage.

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 ('Produce') and resource ('CAMELS-style analytical assessment') and details the five components (C, A, E, L, S) plus composite rating. This clearly distinguishes it from generic fetch tools and even from other analytic tools like fdic_detect_risk_signals or fdic_show_bank_deep_dive by naming the proprietary proxy model and scoring output.

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?

The description clearly states it applies to a single FDIC-insured institution and specifies the analytical approach (CAMELS-style proxy). It implicitly signals that it is the right choice when a comprehensive, component-wise health assessment is needed, but it does not explicitly list alternatives or conditions when not to use it. Still, the context is strong enough for an agent to infer usage.

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