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F1 Race Schedule

f1.races.schedule
Read-onlyIdempotent

Get the Formula 1 race calendar for any season from 1950 to the current year. Returns each Grand Prix with round number, race name, circuit, location, race date/time (UTC), qualifying date/time, and sprint date when applicable. Omit the season parameter to get the current season schedule. Data source: Jolpica F1 (Ergast-compatible API) — free, unlimited, no auth required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return (1–100, default 30).
offsetNoPagination offset — number of results to skip (default 0).
seasonNoSeason year (e.g. 2026, 2024, 2023). Omit for the current season.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
errorNoPresent only when the call failed. Includes error code, message, request_id, and any provider-specific extras.
resultNoTool response payload. Shape varies per tool — consult the tool description and inputSchema. May be an object, array, string, or number depending on the upstream provider response.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds valuable context beyond annotations: it specifies the exact fields returned (round, race name, circuit, etc.) and the data source (Jolpica F1) with free/unlimited/no-auth details. No contradictions.

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 moderately sized but every sentence adds value: purpose, return fields, default behavior, and data source. Front-loaded with the core purpose, and structured in a logical, readable manner.

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

Completeness4/5

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 and rich annotations, the description covers the essential points: what data is returned, how to get the current season, and the source/auth characteristics. It is complete enough for an agent to call the tool correctly without further clarification.

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 coverage is 100%, so all parameters are described. The description adds extra semantics by explaining that omitting the season parameter returns the current season, which is not obvious from the schema alone. Also clarifies the intended use of the season parameter.

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 clearly states the purpose: 'Get the Formula 1 race calendar for any season from 1950 to the current year.' It uses a specific verb and resource, and distinguishes from sibling F1 tools (results, standings) by focusing on the calendar and its fields.

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?

It provides clear usage context: omit the season parameter for the current season, and lists the return fields. However, it does not explicitly compare itself to siblings or state when not to use it, though the purpose is obvious from the name and description.

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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