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stefanoamorelli

Federal Reserve Economic Data (FRED) MCP Server

Get FRED series data

fred_get_series

Retrieve economic data for any FRED series by ID, with options for transformations, frequency changes, and date ranges. Get the observations you need for indicators like GDP or unemployment.

Instructions

Retrieve data for any FRED series by its ID. Supports data transformations, frequency changes, and date ranges.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of observations to return
unitsNoData transformation: lin=levels, chg=change, pch=percent change, log=natural log
offsetNoNumber of observations to skip
frequencyNoFrequency aggregation: d=daily, w=weekly, m=monthly, q=quarterly, a=annual
series_idYesThe FRED series ID to retrieve data for (e.g., 'GDP', 'UNRATE', 'CPIAUCSL')
sort_orderNoSort order of observations by date
output_typeNoOutput format: 1=observations, 2=observations by vintage, 3=observations by release, 4=initial release only
vintage_datesNoVintage date or dates in YYYY-MM-DD format
observation_endNoEnd date for observations in YYYY-MM-DD format
observation_startNoStart date for observations in YYYY-MM-DD format
aggregation_methodNoAggregation method: avg=average, sum=sum, eop=end of period

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.0.1
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observed

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavior. It simply says 'Retrieve data' without stating side effects, limitations, rate limits, output structure, or error conditions. For a read operation, it's not harmful but inadequately informative about what to expect.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences, no redundant phrasing. Every word earns its place, but it is perhaps too sparse (under-specified) rather than genuinely concise—still, it is well-structured and front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 11 parameters, several with enums, and no output schema. The description provides no information about return formats, required fields beyond the implied series_id, or how to interpret transformations/frequencies. This is insufficient for an agent to confidently select and use the tool without relying heavily on the schema.

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 coverage is 100%, and the schema already describes each parameter in detail. The description mentions transformations, frequency, and date ranges, which loosely map to units, frequency, and observation_start/end, but adds no new meaning beyond what the schema provides. The baseline of 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it retrieves data for a FRED series by its ID, which is a specific verb and resource. It does not explicitly differentiate from siblings (fred_browse, fred_search), but the intent is unambiguous—getting the actual data series rather than browsing or searching.

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?

The description implies usage—use this to get series data—but provides no explicit guidance on when to choose this over fred_browse or fred_search, nor any exclusions or prerequisites. The mention of supported options (transformations, frequency, date ranges) gives some context but no decision framework.

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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