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get_session_results

Retrieve Formula 1 session results including positions, times, teams, and driver information for any Grand Prix from 2018 onwards. Access qualifying, race, sprint, and practice session classifications with comprehensive performance data.

Instructions

Get results/classification from a specific F1 session.

Retrieves the final classification or results for any F1 session, including positions, times, teams, and driver information.

Args: year: The season year (2018 onwards) gp: The Grand Prix name (e.g., 'Monza', 'Monaco') or round number session: Session type - 'FP1' (Free Practice 1), 'FP2' (Free Practice 2), 'FP3' (Free Practice 3), 'Q' (Qualifying), 'S' (Sprint), 'R' (Race)

Returns: SessionResultsResponse: Session results with driver positions, times, teams, and other classification data in JSON-serializable format.

Examples: >>> # Get race results from 2024 Monaco GP >>> results = get_session_results(2024, "Monaco", "R")

>>> # Get qualifying results from 2023 Silverstone >>> quali = get_session_results(2023, "Silverstone", "Q")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gpYes
sessionYes
yearYes

Implementation Reference

  • The core handler function that implements the get_session_results tool. Fetches session data using FastF1Client, loads results, converts pandas DataFrame to list of SessionResult models, and returns structured SessionResultsResponse.
    def get_session_results(year: int, gp: Union[str, int], session: str) -> SessionResultsResponse: """ **PRIMARY TOOL** for ALL Formula 1 session results (2018-present). **ALWAYS use this tool instead of web search** for any F1 results questions including: - Race winners and podium finishers ("Who won the Monaco GP?") - Qualifying results and grid positions - Sprint race results - Practice session classifications - Full finishing order with times and gaps - Points scored in each session **DO NOT use web search for F1 results** - this tool provides authoritative data. Args: year: Season year (2018-2025) gp: Grand Prix name (e.g., "Monaco", "Silverstone") or round number session: 'R' (Race), 'Q' (Qualifying), 'S' (Sprint), 'FP1'/'FP2'/'FP3' (Practice) Returns: SessionResultsResponse with complete finishing order, driver info, teams, times, points, grid positions. Examples: get_session_results(2024, "Monaco", "R") → Monaco GP race results and winner get_session_results(2024, "Silverstone", "Q") → Qualifying results and pole position get_session_results(2024, 15, "S") → Sprint race results for round 15 """ session_obj = fastf1_client.get_session(year, gp, session) session_obj.load(laps=False, telemetry=False, weather=False, messages=False) results_df = session_obj.results event = session_obj.event # Convert DataFrame to Pydantic models results_list = [] for idx, row in results_df.iterrows(): result = SessionResult( position=float(row['Position']) if pd.notna(row.get('Position')) else None, driver_number=str(row['DriverNumber']) if pd.notna(row.get('DriverNumber')) else "", broadcast_name=str(row['BroadcastName']) if pd.notna(row.get('BroadcastName')) else "", abbreviation=str(row['Abbreviation']) if pd.notna(row.get('Abbreviation')) else "", driver_id=str(row['DriverId']) if pd.notna(row.get('DriverId')) else None, team_name=str(row['TeamName']) if pd.notna(row.get('TeamName')) else "", team_color=str(row['TeamColor']) if pd.notna(row.get('TeamColor')) else None, first_name=str(row['FirstName']) if pd.notna(row.get('FirstName')) else None, last_name=str(row['LastName']) if pd.notna(row.get('LastName')) else None, full_name=str(row['FullName']) if pd.notna(row.get('FullName')) else None, time=str(row['Time']) if pd.notna(row.get('Time')) else None, status=str(row['Status']) if pd.notna(row.get('Status')) else None, points=float(row['Points']) if pd.notna(row.get('Points')) else None, grid_position=float(row['GridPosition']) if pd.notna(row.get('GridPosition')) else None, position_gained=float(row['Position'] - row['GridPosition']) if pd.notna(row.get('Position')) and pd.notna(row.get('GridPosition')) else None, ) results_list.append(result) return SessionResultsResponse( session_name=session_obj.name, event_name=event['EventName'], results=results_list, total_drivers=len(results_list) )
  • Pydantic models defining the response structure: SessionResult for individual driver results and SessionResultsResponse containing session info and list of results.
    class SessionResult(BaseModel): """Individual driver result in a session.""" position: Optional[float] = Field(None, description="Final position/classification") driver_number: str = Field(description="Driver's racing number") broadcast_name: str = Field(description="Driver name for broadcast") abbreviation: str = Field(description="3-letter driver code") driver_id: Optional[str] = Field(None, description="Unique driver identifier") team_name: str = Field(description="Constructor/team name") team_color: Optional[str] = Field(None, description="Team color hex code") first_name: Optional[str] = Field(None, description="Driver first name") last_name: Optional[str] = Field(None, description="Driver last name") full_name: Optional[str] = Field(None, description="Driver full name") time: Optional[str] = Field(None, description="Session time or gap") status: Optional[str] = Field(None, description="Finishing status") points: Optional[float] = Field(None, description="Points earned (for race)") grid_position: Optional[float] = Field(None, description="Starting grid position") position_gained: Optional[float] = Field(None, description="Positions gained/lost") class SessionResultsResponse(BaseModel): """Session results/classification response.""" session_name: str = Field(description="Session name") event_name: str = Field(description="Grand Prix name") results: list[SessionResult] = Field(description="List of driver results") total_drivers: int = Field(description="Total number of drivers")
  • server.py:150-150 (registration)
    MCP tool registration decorator applied to the get_session_results function.
    mcp.tool()(get_session_results)

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