Skip to main content
Glama
cyntrica

Gov Data MCP

by cyntrica

cfpb_complaint_trends

Read-only

Track consumer complaint trends over time using CFPB data. Aggregate by month, quarter, or year, and filter by product, issue, company, or state for detailed insights.

Instructions

Get complaint trends over time using the CFPB Trends API. Uses dedicated /trends endpoint with lens-based aggregation. REQUIRED: trend_interval ('month', 'quarter', or 'year') — the API rejects requests without it. Lens options: 'overview' (total counts), 'product' (by product), 'issue' (by issue), 'tags' (by tag). Sub-lens allows drilling into sub-categories within the lens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lensNoTrend lens (default: overview)
focusNoFocus charts on a specific product or company name
issueNoIssue type filter
stateNoTwo-letter state code: 'CA', 'TX', 'NY'
companyNoCompany name: 'Wells Fargo', 'Equifax', etc.
productNoFinancial product: 'Mortgage', 'Debt collection', etc.
sub_lensNoSub-lens drill-down
sub_lens_depthNoTop N sub-aggregations to return (default 10)
trend_intervalYesTime bucket size for trend aggregation: 'month', 'quarter', or 'year'
date_received_maxNoEnd date (YYYY-MM-DD)
date_received_minNoStart date (YYYY-MM-DD)
Behavior4/5

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

The readOnlyHint annotation already establishes the non-destructive nature. The description adds a valuable behavioral detail: the API rejects requests without trend_interval. It also explains sub-lens behavior. This goes beyond annotations but does not cover all potential edge cases or rate limits.

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 concise and well-structured: four sentences that front-load the purpose, then detail the endpoint, required parameter, lens options, and sub-lens. No filler or redundant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the description covers the core concept and required parameter, it does not describe the return format or how filters (date range, state, company) affect the output. With no output schema, the agent might not know what to expect. The tool has 11 parameters, so a bit more contextual detail would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so parameters are already documented. The description adds semantic meaning by explaining the lens options (overview, product, issue, tags) and how sub_lens drills down into sub-categories, which is not fully captured in the schema's enum lists. It also emphasizes the required trend_interval.

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 clearly states the tool's purpose: 'Get complaint trends over time using the CFPB Trends API.' It specifies the resource (complaint trends), the verb (get), and distinguishes from siblings (e.g., cfpb_complaint_detail, cfpb_complaint_aggregations) by emphasizing time-series and lens-based aggregation.

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 provides clear context for when to use the tool (for trends over time) and highlights the required trend_interval. However, it does not explicitly mention alternative CFPB tools or when not to use this one, so it stops short of full usage guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/cyntrica/gov-data-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server