Get the daily U.S. debt series (penny-level) over a date range. Source: U.S. Treasury Fiscal Data (public domain, no key).
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | End date YYYY-MM-DD (optional) | |
| from | No | Start date YYYY-MM-DD (optional) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does add useful context about the source (U.S. Treasury Fiscal Data) and authentication (no key, public domain). However, it does not mention rate limits, return format, or any constraints on the date range, leaving significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, dense sentence followed by a brief source/auth note. It wastes no words and front-loads the core purpose. This is exemplary conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is moderately simple (a date-range query returning a time series). The description covers the what, the source, and the auth, but without an output schema it leaves some ambiguity about the exact fields in the response (e.g., total debt vs. components). This is a minor gap, so a 4 is appropriate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for both parameters ('from' and 'to' with clear date descriptions). The description adds the context 'over a date range' but provides no additional parameter-level detail beyond the schema. This matches the baseline expectation for full coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and names the exact resource ('daily U.S. debt series') with clear modifiers ('penny-level', 'over a date range'). This distinguishes it from siblings like us_debt_current (current snapshot) and treasury_debt (likely a related treasury endpoint). The source and auth note add further clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies usage for retrieving a historical daily debt series over a specified date range, which distinguishes it from tools like us_debt_current that likely give just the latest value. However, it does not explicitly name alternative tools or state when not to use it, so it falls short of a top score.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tool groups have overlapping purposes: fda_drug_labels vs health_drug_search, fda_recalls vs health_recalls, fx_official_rates vs treasury_fx_rates, treasury_debt vs us_debt_current, and get_gdp vs get_bea_gdp. These near-duplicates create real ambiguity for an agent deciding which tool to call.
Names mix verb-led styles (get_, search_, compare_, screen_) with domain-led styles (fx_, treasury_, uk_, health_, eurostat_, datausa_). Within the same domain, similar actions use different patterns (get_gdp vs eurostat_gdp vs imf_indicator), making the set feel inconsistent and hard to predict.
75 tools is extreme for any MCP server, especially when many tools are redundant or cover unrelated domains (weather, earthquakes, scholarly search, air quality) outside the stated SEC/economics/demographics/FX focus. This overwhelms agents and burdens context windows.
Core domains like SEC financials, major economic indicators, basic demographics, and current FX rates are well covered. However, gaps remain: no historical FX rates, no stock price/quote tool, limited demographic breakdowns, and no ability to fetch full SEC filing text. Some operations end in dead ends.