Crawlora MCP

formula1_json_meeting_datasets

Read-only

Get Formula 1 session datasets for one meeting, from the JSON API. Returns one meeting's dataset dropdown: each dataset's label, its relative path (with the meeting or session parameters), whether it is a session result, whether it is available and the editorial session type. This is the discovery surface for the dataset values formula1-json-results accepts for that meeting; a sprint dataset appears only on sprint weekends.

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": {
      "season": "<season>",
      "meeting": "<meeting>"
    },
    "name": "formula1_json_meeting_datasets"
  }
}

Input Schema

Name	Required	Description	Default
`season`	Yes	Required four-digit championship year.
`meeting`	Yes	Required numeric meeting id from formula1-json-meetings.

Output Schema

Name	Required	Description	Default
`data`	Yes	The tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 11, 2026

TDQS

A3.9/5.0

Behavior3/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds one valuable domain caveat — a sprint dataset appears only on sprint weekends — but says nothing about auth, rate limits, or freshness/staleness of the dropdown.

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?

Two sentences, front-loaded with what is returned and ending with the operational caveat. The enumeration of returned fields is somewhat redundant given an output schema exists, but it remains tight and readable.

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 an output schema present and 100% schema coverage, the description need only convey purpose, ordering role, and traps — the sprint-weekend caveat is the key one and it is included. Only minor gaps remain, such as whether season and meeting must correspond.

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 coverage is 100%, so both season and meeting are already documented, including provenance from formula1-json-meetings. The description adds only a loose reference to "the meeting or session parameters" embedded in returned paths, not new semantics for the inputs themselves, so baseline 3 applies.

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?

States a specific verb and resource ("Get Formula 1 session datasets for one meeting") plus its ecosystem role as the discovery surface for dataset values consumed by formula1-json-results. An agent can distinguish this from the results tool and from formula1_json_meetings without opening a schema.

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?

Provides explicit context for when to use it: to discover valid dataset values before calling the results tool for that meeting. It does not state when to skip it (e.g., if the dataset value is already known) or name alternative tools directly, but the call-ordering intent is unambiguous.

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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