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TypeScript
Remote

CFPB Consumer Complaint Volume Trends

cfpb-complaints.complaints.trends
Read-onlyIdempotent

Track CFPB consumer complaint volume over time by week, month, or year, filtered by product, company, or state, to spot spikes and breakdown trends.

Instructions

Get the time-series trend of CFPB consumer complaint volume — weekly, monthly, or yearly buckets — optionally filtered by product, company, or US state, and optionally broken down (e.g. by sub-product or issue when a lens is specified). Useful for spotting spikes in complaints against a company or product over time. Data: consumerfinance.gov (CFPB), no auth required.

Input Schema

NameRequiredDescriptionDefault
lensNoTrend breakdown dimension (default "overview" — total volume only, no `sub_lens` needed). "product"/"issue"/"company" require `sub_lens` to be set, or upstream returns a 422 listing the valid sub-lens choices for that lens.
stateNoTwo-letter US state or territory postal abbreviation (e.g. "CA", "NY", "PR").
companyNoExact registered company name as CFPB records it, typically uppercase with legal suffix (e.g. "EQUIFAX, INC.", "WELLS FARGO & COMPANY", "BANK OF AMERICA, NATIONAL ASSOCIATION"). A near-miss silently returns 0 results rather than an error.
productNoExact CFPB product category — must match verbatim, e.g. "Credit reporting or other personal consumer reports", "Debt collection", "Mortgage", "Checking or savings account", "Credit card", "Credit card or prepaid card", "Money transfer, virtual currency, or money service", "Student loan", "Vehicle loan or lease", "Payday loan, title loan, personal loan, or advance loan", "Prepaid card". A near-miss (e.g. wrong wording) silently returns 0 results rather than an error.
date_maxNoEnd of the date range, format YYYY-MM-DD.
date_minNoStart of the date range, format YYYY-MM-DD.
sub_lensNoSecondary breakdown required when `lens` is not "overview". Valid per lens: product→(sub_product, issue, company, tags); issue→(product, sub_issue, company, tags); company→(product, issue, tags).
trend_intervalNoTime bucket size for the trend series (default "month").

Output Schema

NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.2.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds data source and no-auth requirement, which is useful context but does not disclose other behaviors like pagination or silent zero-result handling (though those are mentioned in parameter descriptions).

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?

Two sentences plus a brief data-source note, all front-loaded with the core action and key options. No wasted words; the use case and authentication status are conveyed efficiently.

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?

With an output schema present and comprehensive parameter descriptions, the description covers the essential purpose, use case, data source, and auth requirement. It could more explicitly distinguish from sibling tools, but the provided context is sufficient 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 the schema fully documents all parameters. The description adds general context about optional filters and breakdowns but does not provide syntax or format details beyond what the schema already includes, meeting the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb 'Get' and resource 'time-series trend of CFPB consumer complaint volume', specifying buckets and optional filters. It differentiates from search and by_state tools by focusing on trends over time, though it does not explicitly name siblings.

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?

Provides a use case ('spotting spikes in complaints against a company or product over time') and mentions data source and auth. However, it does not explicitly state when to use this tool over alternatives like complaints.search or complaints.by_state, nor does it mention exclusions.

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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