Get macroeconomic indicators from FRED (Federal Reserve). GDP, Fed funds rate, Treasury yields, housing starts, retail sales.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Data points to return | |
| series | No | gdp, fed_funds_rate (default), treasury_10y, treasury_2y, yield_curve, housing_starts, retail_sales, consumer_sentiment | fed_funds_rate |
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 only states it retrieves data from FRED but does not mention any behavioral traits such as API rate limits, authentication needs, potential latency, or any side effects. The tool is a read operation, but this isn't explicitly confirmed.
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, concise sentence that immediately states the tool's purpose and lists key indicators. Every word serves a purpose with no redundancy.
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?
Despite the tool being a data retrieval tool with no output schema, the description fails to explain what the output looks like (e.g., time series, values, dates). It also does not mention pagination or any limits on the returned data. This is a significant gap for an agent to use the tool correctly.
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 baseline is 3. The description lists the series options, mirroring the schema's enum values, but does not add new meaning beyond what the schema already provides. No additional context on parameter usage or expected format is given.
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 it retrieves macroeconomic indicators from FRED and lists example series, making the purpose clear. However, it does not explicitly differentiate from sibling tools like get_inflation or get_treasury, which are more specific, so a slight deduction for lacking sibling distinction.
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?
No guidance is provided on when to use this tool versus the more specialized siblings (e.g., get_inflation, get_energy). There is no mention of use cases, prerequisites, or when not to use it. The description simply states what it does without usage context.
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.
Each tool targets a distinct economic domain (e.g., demographics, inflation, jobs) with no overlap. The descriptions clearly differentiate the data sources and use cases.
All tools follow a consistent `get_<topic>` pattern using snake_case, making the naming predictable and easy to navigate.
With 7 tools, the server provides a focused yet comprehensive set of macroeconomic indicators without being overwhelming. Each tool serves a clear purpose.
Covers major macroeconomic areas (employment, inflation, GDP, demographics, energy, treasury) but lacks minor categories like trade or consumer confidence. Gaps are slight.