f1verse MCP Server

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The stretches of a race worth watching.

f1_highlights

Read-onlyIdempotent

Find race stretches worth watching by ranking clustered timing-feed passing signals for a specified Formula 1 season and round.

Instructions

The stretches of a race worth watching. Windows where the timing feed's own passing signals cluster, ranked by density. An editing index rather than a verdict — it says where cars were changing state, not that a pass completed. 2023 onward.

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_highlights"
  }
}

Input Schema

Name	Required	Description	Default
`year`	Yes	Season year, e.g. 2026. Race data 2023+.
`round`	Yes	Round number within the season, 1-based.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed3 schema fields changedv0.15.0Nov 9, 2026

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

A3.7/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, openWorld), so the bar is lower, yet the description adds genuine behavioral context: results are derived from clustered timing-feed passing signals, are ranked by density, and are explicitly not verified completed passes. It also states the 2023-onward data boundary, which affects what an agent can ask for. It does not say how many windows are returned or how density is normalized, so not a 5.

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 short and front-loaded, with the caveat placed immediately after the definition where it matters most. The opening sentence duplicates the title verbatim, which is the one line that does not earn its place.

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?

An output schema exists, so return shape need not be explained, and the description covers what the tool computes, how it is ranked, its interpretive limits, and its data range. The remaining gap is scale — expected number of windows and whether the ranking is relative within a race — which an agent would want before deciding between this and f1_turning_points.

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% and both parameters (year, round) are fully documented in the schema, including the 2023+ constraint and 1-based round numbering. The description's '2023 onward' merely restates the year field's existing note and adds nothing about the round parameter. Baseline 3 applies.

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 concrete resource and its construction: windows where the timing feed's own passing signals cluster, ranked by density. The line 'an editing index rather than a verdict — it says where cars were changing state, not that a pass completed' implicitly separates it from a true pass/battle counter. It stops short of naming the sibling tools (f1_battles, f1_turning_points, f1_race_events) that an agent would otherwise confuse it with.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no explicit when-to-use or when-not statement and no sibling is named as an alternative. The framing as 'an editing index' implies the intended use (picking replay/highlight segments) and warns against using it as a factual overtake count, but the agent must infer that routing decision rather than being told.

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