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io.github.jinsim/f1verse

PYPI · F1VERSE

Formula 1 race data with the domain rules applied: stints, tyre wear, publish-safety. Zero deps.

Available components

0 this week 81 Trust /100

Last scanned (4 hours ago)

Scores higher than 82% of PyPI servers

Category Entertainment and Games

Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security50
  • Malware scan not yet available for this package.Unverified
  • No known CVEs affecting this package version or its production dependencies.Pass
  • Runs setuptools.build_meta at install time, a recognised build step with no custom scripting around it. View diagnostics → Pass
  • No production dependencies, so there is no dependency health to assess. View diagnostics → Pass
Provenance & Transparency100
  • Source repository is publicly reachable at the declared URL. View diagnostics → Pass
  • Cryptographically verified build provenance (signed, bound to jinsim/f1verse). View diagnostics → Pass
  • Clear OSI-approved license (Apache-2.0).Pass
  • Actively maintained (last published 66 days ago).Pass
  • Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability76
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 2668 tokens (~127/item across 21 items; 21 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management100
  • No destabilizing schema changes in the last 30 days.Pass
Tool Coverage100
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 100% of tool parameters carry a description.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 21 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 22 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.Pass
What we tested

Checks we ran (15)

  • Known CVEs
  • Install scripts
  • Dependency health
  • Source repository
  • Provenance
  • License
  • Maintenance
  • Security disclosure
  • Schema quality
  • Stability
  • Tool coverage
  • Injection markers
  • Destructive annotations
  • Judged manipulation
  • MCP protocol

Checks we could not complete (1)

These are gaps on our side, not findings about this package. We only credit what we can confirm, so a category made up entirely of them scores 0.

  • Malware scan in Supply Chain SecurityMalware scan not yet available for this package.

Does not apply to this package (2)

  • Endpoint SecurityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.
  • Transport & ReachabilityScored on hosted endpoints only. A package has no live endpoint of its own for us to probe.

The score does not measure everything. What the score does not measure →

Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 6 Nov 26 +1
    • Stability: 0.97 → pass security
  • 5 Nov 26 −15
    • Malware scan: pass → unverified ▼ security
  • 4 Nov 26 −1
    • Stability: pass → 0.93 functional
  • 3 Nov 26 +15
    • Malware scan: unverified → pass ▲ security
  • 2 Nov 26 −15
    • Malware scan: pass → unverified ▼ security
  • 1 Nov 26 +15
    • Malware scan: unverified → pass ▲ security
  • 30 Oct 26 −15
    • Malware scan: pass → unverified ▼ security
  • 29 Oct 26 +16
    • Malware scan: unverified → pass ▲ security
    • Stability: 0.97 → pass security
Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 6 Nov 2026 · Analysed pypi/f1verse@0.14.0

Provenance Verified

A signed build attestation was found and verified, binding this exact artifact to the source repository it claims to come from.

Result Verified
Ecosystem pypi
Reason Verified
Discovered via Registry attestation endpoint
Source repo jinsim/f1verse
Certificate issuer https://token.actions.githubusercontent.com
Certificate SAN https://github.com/jinsim/f1verse/.github/workflows/publish.yml@refs/tags/v0.14.0
Rekor log index 2669890195
Predicate type PyPI publish attestation https://docs.pypi.org/attestations/publish/v1
Subject digest sha256:fb410c7059b830fab5bc9b86e0643b15f9be0df73f1cba1097fe60ee000f9c33

Background: How many MCP packages publish verified provenance →

Install scripts 1 script
Hook Tier Command
build_backend Known build tool setuptools.build_meta

Background: Why install scripts are a supply-chain risk →

Dependencies 0 packages
Packages resolved 0
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 21 exposed · ~2,572 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
f1_archive_race ~147

A race from 1996-2022, before the live-timing feeds. Results, lap-by-lap running order, lead changes and laps led for the seasons the modern feeds do not cover. Pit stops are included from 2011. The reply carries a 'coverage' block naming exactly what that era does and does not hold, so an absent field is never mistaken for a zero. Use f1_race_story for 2023 onward — it knows strictly more.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_battles ~113

Pairs that ran nose-to-tail, and for how long. Every stretch where two cars held consecutive positions within 1.5 seconds for at least three laps, with the closest the gap got. Finds the fights a results table hides — a scrap for eighth that ran twenty laps never shows up in the standings.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_circuit_directory ~88

Every Formula 1 venue recorded in the historical results. A source-labelled directory of circuit ids, names, cities, countries and coordinates from 1950 to today. This is the discovery call for a historic venue; pass its id to f1_circuit_history for results, and use f1_circuit_profile with a year and round when the question needs that event's specific layout.

Input schema present but exposes no named parameters.

No output schema declared.

No examples provided.

f1_circuit_history ~119

A Formula 1 venue's winners, pole conversion and records. Historical results at one circuit: every event count, recent winners and their starting positions, pole-to-win conversion, and the most successful drivers. Use f1_circuit_directory first to discover the stable circuit id; this is results history, so it does not assign a modern map to an older layout.

NameTypeReqDescription
circuit_idstringyesStable circuit id from f1_circuit_directory, e.g. 'monza', 'spa' or 'nurburgring'.

No output schema declared.

No examples provided.

f1_circuit_profile ~138

A circuit's layout, pit-loss economics and historical record. Geometry, corner-by-corner lap position and local heading change, mini-sector and marshal-sector boundaries, pit loss under green/SC/VSC, a reference lap, and historical outcomes in one evidence-labelled profile. Coordinate length is explicitly not presented as surveyed metres; absent elevation, width and DRS geometry are named rather than guessed. Use this for a race-preview track explainer.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_circuit_survey ~201

The circuit measured from the cars that drove it. What no public circuit map carries, measured from telemetry instead: the height profile with gradients and total climb; where overtakes actually happen, clustered into zones and merged across the timing line; how much of the lap is spent at full throttle and where the braking zones are, with entry and minimum speeds; the width of road the field used and the camber of it. DRS zones are included for seasons that had DRS and reported as a regulation change, not a weather excuse, for those that do not. Every figure names the laps and drivers behind it and declines rather than guesses when the samples cannot support it. Use for track explainers and previews that need real numbers, not an outline.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_closest_titles ~81

Championships ranked by how close they finished. The smallest title margins in history, measured both in points and relative to what a win was worth that season — the only way seasons decades apart compare honestly, since two points in 1958 is most of a win and two points today is not.

NameTypeReqDescription
topinteger–How many seasons to return.

No output schema declared.

No examples provided.

f1_data_quality ~164

Is this session's data complete, current and safe to publish? Completeness per field, how old the fetched copy is, whether the classification is still provisional (stewards rewrite results hours after the flag), corrections observed so far, agreement between independent sources, and a single 'publishable' verdict. Call this before stating a result as final, especially within a few hours of a session ending.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
sessionstring–Session name as the calendar spells it: Race, Qualifying, Sprint, Sprint Qualifying, Practice 1-3. Defaults to Race.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_deleted_laps ~155

Lap times the stewards struck out, with reinstatements. Every lap-time deletion race control announced in a session, with the car, the time, the stated reason, and whether the deletion still stands — a reinstated lap is reported with the reversal visible rather than silently dropped. Use before treating a fastest lap or a qualifying position as settled.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
sessionstring–Session name as the calendar spells it: Race, Qualifying, Sprint, Sprint Qualifying, Practice 1-3. Defaults to Race.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_driver_career ~107

A driver's career totals, 1950 to today. Starts, wins, podiums, poles and points for one driver across all of F1 history, plus the next round-number milestones they are approaching. Takes an Ergast-style driver id such as 'max_verstappen', 'hamilton' or 'leclerc'.

NameTypeReqDescription
driver_idstringyesErgast/Jolpica driver id, e.g. 'max_verstappen', 'hamilton'.

No output schema declared.

No examples provided.

f1_highlights ~99

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.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_race_brief ~107

A short factual race summary in plain English. A publishable prose summary of a race, built from templates only — every number in it comes from the data, so it is safe to quote verbatim. Use when the user wants a readable recap rather than fields to compute with.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_race_story ~131

Everything that happened in one race, as structured JSON. The whole race in one call: final results with broadcast-convention gaps, lead changes, laps led per driver, the event timeline, tyre stints, median race pace (pit/SC/VSC laps excluded), and safety-car interruptions. Use this first for any 'what happened in race X' question — it is one request instead of six.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_running_order ~109

Who was where at the end of every lap. The order on track lap by lap, plus how much each lap churned and who made the biggest single gain. This is the data behind any position-change chart; use it for 'how did the race unfold' rather than fetching results and guessing.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_season_shape ~86

How a championship unfolded, round by round. Each contender's running points total, who led after every round, and where the lead changed hands. Two seasons can end on the same margin and look nothing alike; this is what tells a procession from a fight.

NameTypeReqDescription
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_season_status ~98

Where the season stands right now and what is next. The latest completed race, sessions that have finished and settled, the next session and how many hours until it starts. Use this to answer 'when is the next race' or to resolve 'the last race' into a concrete round number before calling the other tools.

NameTypeReqDescription
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_session_results ~149

Classification for any session of a weekend. Results for one session, classified the way that kind of session actually is: races give position and gap (lapped cars as '+1 LAP'), qualifying gives per-segment times with gaps to that segment's fastest and where each driver was eliminated, practice gives a best-lap table.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
sessionstring–Session name as the calendar spells it: Race, Qualifying, Sprint, Sprint Qualifying, Practice 1-3. Defaults to Race.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_standings ~78

Championship standings after the latest completed round. Drivers' or constructors' championship table, with points and wins, as of the most recent round that has been scored.

NameTypeReqDescription
kindstring–Which championship table to return.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_title_race ~179

Championship win probability, and who is still mathematically alive. Two answers to 'who wins the title', kept deliberately apart. First the arithmetic: maximum points still available, and who is therefore out for certain — a fact, not a forecast. Then the projection: the rest of the season simulated thousands of times, resampling each driver from the positions they have actually finished in, with retirements at their measured rate. Every run first re-draws the driver's own level, so a short season widens the answer rather than hiding inside it. Returns the assumptions and sample sizes it stands on; the same seed returns the same numbers.

NameTypeReqDescription
runsinteger–Simulated seasons. More is steadier and slower.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_tyre_wear ~124

How fast each set of tyres degraded, stint by stint. Per-stint degradation in seconds per lap, computed on fuel-normalised clean laps only (pit, safety-car and traffic laps excluded), plus a circuit abrasion verdict relative to an ordinary surface. Every rate reports how many clean laps it stands on; stints too short to judge say so instead of guessing.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

f1_weekend_sessions ~99

Which sessions a given round has, in order. Lists the sessions of a race weekend with start and end times — the valid inputs for the 'session' argument of the other tools. Call this when unsure whether a round was a sprint weekend.

NameTypeReqDescription
roundintegeryesRound number within the season, 1-based.
yearintegeryesSeason year, e.g. 2026. Race data 2023+.

No output schema declared.

No examples provided.

Install

How do I install the io.github.jinsim/f1verse MCP server?

io.github.jinsim/f1verse runs locally as a PyPI package, launched with uvx --from f1verse f1verse. The registry lists runner options for this package that are not in this command (they are not ones we reproduce, or they name another package). Check the registry entry before relying on it. Ready-made configuration for Claude, Cursor, VS Code, Codex and 3 more is on this page, copied from each client's own documentation.

pypi · f1verse

# add to Claude Code
claude mcp add jinsim-f1verse -- uvx --from f1verse f1verse

The registry lists runner options for this package that are not in this command (they are not ones we reproduce, or they name another package). Check the registry entry before relying on it.

Common questions

What is the io.github.jinsim/f1verse MCP server?

io.github.jinsim/f1verse is an MCP server listed in the public MCP registry as io.github.jinsim/f1verse. Formula 1 race data with the domain rules applied: stints, tyre wear, publish-safety. Zero deps. This page covers its PyPI package (f1verse).

Is the io.github.jinsim/f1verse MCP server safe to use?

io.github.jinsim/f1verse scores 81 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 6 November 2026. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the io.github.jinsim/f1verse MCP server expose?

io.github.jinsim/f1verse exposes 21 tools: f1_race_story, f1_race_brief, f1_session_results, f1_weekend_sessions, f1_season_status, and 16 more. Their descriptions and schemas cost roughly 2,572 tokens of context every time the server is loaded.

Is the io.github.jinsim/f1verse MCP server still maintained?

io.github.jinsim/f1verse is still listed as active in the MCP registry. We last reached this channel on 6 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

What licence is the io.github.jinsim/f1verse MCP server under?

io.github.jinsim/f1verse declares the Apache-2.0 licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

What did VerifyMCP test on the io.github.jinsim/f1verse MCP server?

VerifyMCP ran 15 checks on io.github.jinsim/f1verse, covering Known CVEs, Install scripts, Dependency health, Source repository and 11 more. One item could not be completed, a gap on our side rather than a finding about io.github.jinsim/f1verse: Malware scan. Endpoint Security and Transport & Reachability do not apply to a PyPI package, so they were not tested. The score does not measure everything, and the scoring documentation lists what it leaves out.