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fred-macro-mcp

fred-macro-mcp

by kevinkda
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_series

Retrieve observation series for FRED economic data, such as GDP or CPI, with optional date range and limit.

Instructions

Return the observation series for a FRED economic data series.

series_id is a FRED identifier (e.g. GDP, CPIAUCSL, UNRATE, DGS10). start / end optionally bound the window as ISO YYYY-MM-DD dates.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "series_id": "<series_id>"
    },
    "name": "get_series"
  }
}

Input Schema

NameRequiredDescriptionDefault
endNo
limitNo
startNo
series_idYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It explains parameters and return type (observation series), but does not disclose behavior like pagination, error handling, rate limits, or the effect of the limit parameter on results.

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?

Three concise sentences with a clear structure: core purpose, then parameter details. No unnecessary information.

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

Completeness3/5

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

Output schema exists (context shows has_output_schema=true), so return values are covered. However, missing details about limit parameter behavior and potential data truncation limit completeness. Also no mention of how the series data is structured (e.g., frequency, units).

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?

With 0% schema description coverage, the description must explain all parameters. It covers series_id (with examples), start/end (ISO format), but omits the limit parameter. This leaves ambiguity about its purpose and default behavior.

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 returns observation series for a FRED economic data series, with examples of series IDs. However, it does not explicitly differentiate from siblings like get_series_latest or search_series.

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

Usage Guidelines2/5

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

The description explains that series_id is required and start/end are optional, but it lacks guidance on when to use this tool versus alternatives like get_series_latest or search_series. No when-not or context for selecting this tool.

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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