mcp-f1

Get Stints

get_stints

Retrieve Formula 1 tyre stints from OpenF1 by session, driver, stint number, compound, or lap range to analyze pit strategy and stint performance.

Instructions

Fetch tyre stints (periods of continuous driving) from OpenF1.

Input Schema

TableJSON Schema

Name	Required	Description
`compound`	No	str — optional, 1-20 chars, e.g., 'SOFT', 'MEDIUM', 'HARD'. Normalized to uppercase.
`lap_end_max`	No
`lap_end_min`	No
`session_key`	No	int \| str — required in practice, positive int or 'latest'. Session identifier; use get_sessions to discover it.
`stint_number`	No	int — optional, >= 1. Sequential stint number.
`driver_number`	No	int — optional, 1-99. Driver number for the season.
`lap_start_max`	No
`lap_start_min`	No
`tyre_age_at_start_max`	No
`tyre_age_at_start_min`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 29, 2026

TDQS

C2.6/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. 'Fetch' implies a read-only operation but the description says nothing about pagination, result limits, ordering, or the practical requirement of a session_key.

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

Conciseness3/5

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

A single short sentence with no wasted words and the resource is front-loaded. It is appropriately terse but that terseness comes at the cost of substance rather than being efficiently informative.

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?

For a 10-parameter tool with no annotations, 40% schema coverage, and range filters whose semantics are undocumented, this is far too thin. The existence of an output schema covers return values, but nothing covers filtering behavior or how to scope a query.

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

Parameters2/5

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

Ten parameters with only 40% schema description coverage, and the description adds zero parameter meaning. Six of the ten params (all the *_min/*_max range filters) have no documentation in either the schema or the description, so an agent cannot tell how they combine.

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?

States a specific verb (Fetch) and resource (tyre stints) and helpfully defines the term as 'periods of continuous driving'. However it does nothing to distinguish this from closely related siblings like get_pit_stops or get_laps, so an agent must infer the boundary itself.

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?

There is no when-to-use guidance, no mention of prerequisites, and no naming of alternatives. With 20 sibling data-fetch tools including pit stops and laps that overlap conceptually, the absence of routing guidance is a significant gap.

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