fred-mcp-server

geofred_series_data

Access cross-sectional regional data for a geographic FRED series by specifying a series ID and optional date or date range.

Instructions

Get cross-sectional regional data for a geographic FRED series.

Args: series_id: FRED series ID (e.g., "WIPCPI"). date: Observation date (YYYY-MM-DD). Returns data for this specific date. start_date: Start of date range (YYYY-MM-DD). Returns data from this date onward.

Returns: dict with keys 'meta' and 'data'.

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": "geofred_series_data"
  }
}

Input Schema

Name	Required	Description	Default
`series_id`	Yes
`date`	No
`start_date`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.2May 29, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations provided. The description does not disclose behavioral traits such as read-only nature, potential rate limits, or data freshness. It only states return format, missing safety or performance context.

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?

The description is concise with a clear purpose statement followed by structured Args and Returns. It is well-organized and front-loaded, though slightly verbose with full parameter descriptions.

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?

Given the output schema existence, the description adequately covers purpose and parameters. However, it lacks behavioral notes and usage context, making it marginally complete for a tool with many siblings.

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 description coverage is 0%, so the description's parameter docs add value by explaining date format and behavior. However, it does not specify what happens if both date and start_date are provided, leaving ambiguity.

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 'Get cross-sectional regional data for a geographic FRED series', specifying the action and resource. It distinguishes from time-series tools like fred_series_observations, but is less distinct from geofred_regional_data.

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?

No guidance on when to use this tool versus siblings. The description does not mention when to prefer this over geofred_regional_data or related tools, nor any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.