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OpenF1 MCP Server

OpenF1 MCP Server

by ragulhari

Meetings (Grand Prix weekends)

get_meetings
Read-onlyIdempotent

Find Formula 1 Grand Prix or testing weekends and retrieve the meeting_key required for session, lap, and telemetry queries. Filter by year, location, country, or circuit; data starts in 2023.

Instructions

Find meetings (Grand Prix or testing weekends). Use this first to get a meeting_key. Data starts in 2023.

Input Schema

NameRequiredDescriptionDefault
yearNoSeason year, e.g. 2025.
limitNoMaximum number of records to return (default 200, max 1000). A summary is added when the result is larger.
fieldsNoReturn only these attributes. Use this to make large results smaller.
filtersNoExtra comparison filters, e.g. [{"field":"lap_duration","op":"<","value":90}]. Allowed fields: circuit_key, circuit_info_url, circuit_image, circuit_short_name, circuit_type, country_code, country_flag, country_key, country_name, date_end, date_start, gmt_offset, is_cancelled, location, meeting_key, meeting_name, meeting_official_name, year. Array fields cannot be filtered.
locationNoCity or location, e.g. "São Paulo", "Monza".
meeting_keyNoMeeting (Grand Prix weekend) identifier. Use "latest" for the current or most recent meeting.
country_nameNoCountry name in English, e.g. "Brazil", "Singapore".
circuit_short_nameNoCircuit short name, e.g. "Interlagos".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely non-obvious context: the corpus starts in 2023 and the tool is the gateway for meeting_key, which is the key behavioral fact an agent needs. Return shape and result-size behavior are left to the schema.

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 short sentences, zero filler, with the core purpose and the workflow directive front-loaded. Every clause (weekend types, meeting_key, 2023 cutoff) carries information an agent would otherwise have to discover by trial.

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?

With no output schema, the description could ideally say what a meeting record contains (meeting_key, name, date_start/end, circuit, country) since those are the fields an agent will pass downstream. Still, it covers the essential discovery role, the data horizon, and the optional-parameter nature is clear from the schema's zero required params.

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 100% across all 8 parameters, including filterable fields, limit semantics and the "latest" enum for meeting_key, so the schema carries the parameter burden. The description adds nothing beyond the implicit point that this is where a meeting_key comes from, which is baseline-3 territory.

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 and resource ("Find meetings") and narrows scope to Grand Prix or testing weekends, which distinguishes it from the session/lap/telemetry siblings. It stops short of naming the nearest sibling (get_sessions) as an alternative, so differentiation is implied by workflow rather than explicit.

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?

"Use this first to get a meeting_key" gives a clear entry-point ordering that tells an agent when to reach for this tool versus the downstream data tools. It lacks any when-not condition (e.g., when you already have a meeting_key, skip this), so it falls short of full routing guidance.

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