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fred-mcp

by mcpwright
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Get release calendar

get_release_calendar
Read-only

Find upcoming FRED economic data release dates (e.g., jobs report, CPI) for a specified look-ahead period, returning each release name and scheduled date, soonest first.

Instructions

Upcoming data-release dates ("when is the next jobs report / CPI?").

`days`: how far ahead to look (1-90, default 14). Returns each release's
name and date, soonest first. Dates are the SCHEDULED dates FRED knows
about; not every release publishes a schedule.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
endYesWindow end (YYYY-MM-DD)
startYesWindow start (YYYY-MM-DD)
releasesYesRelease dates in the window, soonest first
truncatedNoTrue if more release dates exist in the window than were returned — an absent release is NOT proof nothing is scheduled; narrow `days`
Install Server

TDQS

A4.6/5.0
Behavior4/5

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

Description adds context beyond annotations by noting dates are scheduled and not all releases publish a schedule. This informs about data completeness, complementing the readOnlyHint and openWorldHint annotations.

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?

Description is extremely concise: two sentences and a parameter note. Front-loaded with purpose, no redundant text.

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?

Given the presence of an output schema, the description covers what the tool returns (name and date sorted soonest first) and the sole parameter. This is complete for a simple listing tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% coverage, but description fully explains the days parameter: valid range (1-90), default (14), and behavior. This compensates entirely for the schema gap.

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?

Description clearly states the tool returns upcoming data-release dates with examples like jobs report or CPI. It distinguishes from sibling tools that deal with series data, not calendar events.

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

Usage Guidelines4/5

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

Description provides example usage ('when is the next jobs report / CPI?') and explains the days parameter range. It implies usage for calendar queries but does not explicitly contrast with alternatives like get_series.

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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