Search FDA drug labels by brand/generic name or ingredient. Source: openFDA (public-domain US FDA data). Disclaimer: not validated for clinical/production use.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max results (1-20, default 5) | |
| query | Yes | Search query (e.g. aspirin, brand name, ingredient) |
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 burden of disclosing behavioral traits. It adds context by noting the source ('openFDA (public-domain US FDA data)') and includes a disclaimer ('not validated for clinical/production use'), which is valuable. However, it does not explicitly state that the operation is read-only, nor does it describe response formatting or pagination, leaving some behavioral aspects unclear.
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 two sentences long: the first states the core function, and the second adds source and disclaimer. Every sentence earns its place, with no filler. It is front-loaded with the most important information and appropriately sized for a tool with two simple parameters.
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?
For a simple search tool with two parameters and no output schema, the description is mostly complete. It covers the search scope, data source, and a critical caveat. It does not explicitly describe the return format, but given the tool's simplicity and the presence of the disclaimer, the missing details are minor and unlikely to cause misuse.
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%, so the baseline is 3. The description's mention of 'brand/generic name or ingredient' largely repeats what the query parameter schema already provides ('e.g. aspirin, brand name, ingredient'). It does not add meaningful new information about parameter usage beyond the schema.
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 clearly states the tool's function: 'Search FDA drug labels by brand/generic name or ingredient.' It uses a specific verb and resource, and the scope (by name/ingredient) distinguishes it from sibling tools like fda_recalls, which search a different FDA dataset.
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 provides no guidance on when to use this tool versus alternatives such as fda_recalls or other search tools. There is no mention of exclusions, prerequisites, or scenarios where another tool would be more appropriate. The intended usage is implied by the name but not explicitly contrasted with siblings.
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.