f1verse MCP Server

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How fast each set of tyres degraded, stint by stint.

f1_tyre_wear

Read-onlyIdempotent

Measure per-stint tyre degradation from clean lap-time trends and optional fuel-corrected wear, including exclusions, sample sizes, and sensitivity for a season round.

Instructions

How fast each set of tyres degraded, stint by stint. Raw clean-stint lap-time trends and fuel-scenario corrected degradation, with exclusions, sample sizes and sensitivity. 2026+ corrected wear requires an explicit fuel_model; without it only raw trends are available. Earlier default coefficients are illustrative assumptions, not measured fuel. Circuit abrasion is a scenario index, not a measured surface property.

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": {
      "year": "<year>",
      "round": "<round>"
    },
    "name": "f1_tyre_wear"
  }
}

Input Schema

Name	Required	Description
`year`	Yes	Season year, e.g. 2026. Race data 2023+.
`round`	Yes	Round number within the season, 1-based.
`fuel_model`	No	Optional caller fuel scenario, not measured fuel. Required for 2026+ corrected wear.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv0.15.0Nov 9, 2026

addedInput schema / properties / fuel_model

Added value: +{
+  "additionalProperties": false,
+  "description": "Optional caller fuel scenario, not measured fuel. Required for 2026+ corrected wear.",
+  "properties": {
+    "burn_kg_per_lap": {
+      "description": "Assumed fuel burned per lap, kg.",
+      "minimum": 0,
+      "type": "number"
+    },
+    "cost_s_per_kg": {
+      "description": "Assumed lap-time cost per kg, seconds.",
+      "minimum": 0,
+      "type": "number"
+    },
+    "start_kg": {
+      "description": "Assumed starting fuel mass, kg.",
+      "minimum": 0,
+      "type": "number"
+    }
+  },
+  "required": [
+    "start_kg",
+    "burn_kg_per_lap",
+    "cost_s_per_kg"
+  ],
+  "type": "object"
+}

addedInput schema / properties / round / minimum
```
Added value: +1
```
addedInput schema / properties / year / minimum
```
Added value: +1950
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": false,
+  "properties": {
+    "result": {
+      "type": "object"
+    }
+  },
+  "required": [
+    "result"
+  ],
+  "type": "object"
+}

First observedv0.1.0Nov 6, 2026

TDQS

A3.9/5.0

Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior, so the bar is lower; the description still adds real disclosure about output composition (exclusions, sample sizes, sensitivity) and caveats that circuit abrasion is a scenario index rather than a measured surface property. It does not discuss rate limits or data-availability windows, but those are minor here.

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 core purpose is front-loaded in the first sentence, followed by what is returned and then the caveats. It is dense but nearly every clause carries information; the closing disclaimer about circuit abrasion is slightly tangential to a tyre-wear tool.

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, the description need not explain return values, and it correctly focuses on the one thing that changes behavior: the fuel_model requirement for 2026+ corrected wear. Coverage of the raw-vs-corrected distinction and the illustrative-assumption caveat makes it sufficient for correct invocation.

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%, so the baseline is 3. The description does add meaning beyond the schema by tying fuel_model specifically to 2026+ corrected wear and warning that earlier default coefficients are illustrative rather than measured, which is useful context the nested schema does not state.

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?

The description names a specific resource (per-stint tyre degradation) and enumerates what is returned: clean-stint lap-time trends, fuel-corrected degradation, exclusions, sample sizes, sensitivity. That is far more specific than the title alone. It stops short of naming a sibling it differs from (e.g. f1_pace_changes), so an agent must infer the boundary from the sibling list.

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 gives a concrete conditional: for 2026+ corrected wear an explicit fuel_model is required, otherwise only raw trends are available. That tells the agent when the call degrades to partial output. It does not say when to prefer this over related pace/story tools, so the alternative-selection guidance is absent.

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