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treasury-fiscaldata-mcp-server

by io.github.cyanheads

List Treasury Fiscal Data Datasets

treasury_list_datasets
Read-onlyIdempotent

Browse the curated catalog of US Treasury Fiscal Data API endpoints. Returns endpoint paths, field names, descriptions, and update cadence for each dataset. Use this tool before treasury_query_dataset to discover the correct endpoint path and field names — a typo in either causes a 400 error from the API. The catalog is a curated subset of the full API — pass any endpoint path directly to treasury_query_dataset to query datasets not listed here. The catalog covers debt, interest rates, exchange rates, revenue/spending, savings bonds, and securities datasets.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNoKeyword filter against dataset name and description (case-insensitive substring match). Useful for narrowing results when the category is uncertain.
categoryNoFilter by category. Omit to list all datasets. Options: debt, interest_rates, exchange_rates, revenue_spending, savings_bonds, securities, other.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent when the call failed. Absent on success.
totalNoTotal matching datasets.
datasetsNoMatching datasets.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered without description help. The description adds meaningful context beyond that: the catalog is a curated subset (so omission is expected behavior, not a bug), and the 400-error failure mode from upstream. It does not contradict the 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?

Four sentences, each earning its place: purpose and return content, then usage guidance, then the curated-subset caveat. Front-loaded with the most important information and zero filler or repetition of the schema/annotations.

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?

The tool is simple (2 optional params, 0 required, both fully documented) and has an output schema, so return values need no elaboration. The description covers what it returns, when to use it, the important incompleteness caveat, and failure behavior — nothing an agent needs to call it correctly is missing.

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% — both 'search' (case-insensitive substring match) and 'category' (enumerated options, omit to list all) are fully documented in the schema. The description adds no parameter-specific detail beyond the schema, so it rests at the baseline 3 rather than compensating for any coverage gap.

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?

Uses a specific verb ('Browse') with a clear resource ('curated catalog of US Treasury Fiscal Data API endpoints') and details the return content: endpoint paths, field names, descriptions, and update cadence. It explicitly differentiates itself from treasury_query_dataset as the listing vs. querying counterpart, so an agent can distinguish it from all six siblings without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

States explicitly to use this tool before treasury_query_dataset to discover correct endpoint paths and field names, warning that a typo in either causes a 400 error. It also gives a when-not condition: since the catalog is curated/subset, pass endpoint paths directly to treasury_query_dataset for unlisted datasets. Both the primary use and the alternative path are spelled out.

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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TDQS

A4.7/5.0
Disambiguation4/5

The tools are mostly distinct: each specialized getter (debt, exchange rates, interest rates) targets a specific dataset, while the generic query tool and list tool serve discovery and ad-hoc queries. There is some overlap between the generic treasury_query_dataset and the specialized getters, but the descriptions clearly differentiate their intended use (specialized modes vs. raw endpoint queries).

Naming Consistency5/5

All tools follow a consistent treasury_verb_noun pattern with snake_case (e.g., treasury_get_debt, treasury_list_datasets, treasury_dataframe_query). The verbs (get, list, query, describe) are consistent in style and each noun is plural or singular appropriately, making the naming uniform and predictable.

Tool Count5/5

With 7 tools, the server is well-scoped for its purpose of accessing Treasury fiscal data. It offers dedicated tools for common datasets, a generic query tool for flexibility, and DataFrame staging/query utilities, with no redundancy or overwhelming number of tools.

Completeness5/5

The tool surface covers essential workflows: discovering available datasets (list_datasets), querying any endpoint (query_dataset), retrieving common datasets with convenience modes (debt, exchange rates, interest rates), and handling large result sets via DataCanvas staging (describe/query). No obvious gaps exist; even less common datasets are accessible through the generic query tool.

Resources