market-research-mcp

get_macro_series

Fetch FRED macroeconomic time series observations with units, frequency, and last-updated dates for up to 10 series per call to support economic analysis.

Instructions

Fetch FRED macro time series (e.g. DGS10, CPIAUCSL, UNRATE, FEDFUNDS).

Returns, per series: title, units, frequency, last_updated and observations
(date, value; missing values are null) oldest to newest, the last `limit` points
on or after `start` (YYYY-MM-DD). `as_of` is the date of the last observation.
Up to 10 series per call. Source: FRED, Federal Reserve Bank of St. Louis.

Input Schema

Name	Required	Description	Default
`limit`	No
`start`	No
`series_ids`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 24, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden and does well: it explains return fields, missing-value handling, observation ordering, limit/start filtering, as_of, the 10-series cap, and the FRED source. It does not mention permissions, rate limits, or error behavior, so it stops short of fully transparent.

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 purpose is front-loaded in the first sentence, followed by return semantics and constraints with no filler. Every sentence contributes useful operational detail.

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?

For a three-parameter read tool with an output schema and no annotations, the description supplies enough operational context to invoke it correctly: it covers series examples, the cap per call, limit/start semantics, and return behavior.

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 description coverage is 0%, so the description must compensate. It explains limit ('last limit points'), start ('YYYY-MM-DD'), and series IDs through examples plus the 'Up to 10 series per call' constraint, though it does not explicitly restate that series_ids is a required array.

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 states a specific verb and resource: 'Fetch FRED macro time series' with concrete series examples. The resource is clearly distinct from the sibling tools, which cover prices, filings, fundamentals, and earnings rather than macro time series.

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

Usage Guidelines3/5

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

Usage is implied by the domain-specific purpose and examples such as DGS10 and CPIAUCSL, but the description does not explicitly say when to use this tool versus alternatives or when not to use it. No sibling routing guidance is provided.

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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