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Surya96t

fastf1-mcp-server

get_lap_telemetry

Retrieve sampled telemetry data for a specific F1 lap, including speed, throttle, brake, gear, and DRS. Optionally export to CSV for analysis.

Instructions

Get telemetry data for a specific lap.

Data source: FastF1 Live Timing Coverage: 2018-present

Set export_path=True when the user mentions data analysis, notebooks, pandas, ML, "plot the telemetry", "save the trace", or downstream processing — the sampled per-distance trace is written to CSV. Telemetry responses with the default 200 sample points also auto-export so the user always gets a real file path in the project.

Args: year: Season year (2018+) event: Race name or round number session: Session type (R, Q, S, FP1, FP2, FP3) driver: Driver code (e.g., "VER") lap: Lap number or "fastest" (default) sample_size: Number of telemetry points to return (default 200, max 500) export_path: If True, write the sampled data array to a CSV in the configured export directory (default ./fastf1-exports/, override via FASTF1_MCP_EXPORT_DIR) and omit data from the response. Pass a string for a custom directory or .csv file path. The server also auto-exports when data would exceed FASTF1_MCP_AUTO_EXPORT_ROWS rows (default 50). Use a larger sample_size if you want more detail in the exported file.

Returns: { "driver": "VER", "lapNumber": 42, "lapTime": "0:01:23.456", "summary": { "samplePoints": 200, "maxSpeedKph": 327.5, "minSpeedKph": 80.2, "avgSpeedKph": 218.1, "maxGear": 8, "brakingZones": 7, "fullThrottlePct": 64.5 }, "data": [ {"distance": 0.0, "speed": 280.0, "throttle": 95.0, "brake": false, "gear": 7, "drs": 0}, ... ] }

Example: get_lap_telemetry(2024, "Monaco", "Q", "VER") → fastest Q lap telemetry get_lap_telemetry(2024, "Monaco", "R", "VER", lap=45) → lap 45 telemetry

Note: Raw telemetry has 5000+ points per lap. Response is sampled to sample_size evenly-spaced distance points (capped at 500). summary lets a caller answer top-speed / braking-zone questions without parsing the full per-distance array.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
eventYes
sessionYes
driverYes
lapNofastest
sample_sizeNo
export_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations provided, so description carries full burden. Discloses data source, coverage, sampling behavior, export side effects, and response structure changes. No contradictions.

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?

Well-structured with clear sections (purpose, data source, Args, Returns, Example, Note). Slightly verbose in some sentences but overall efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Fully covers the tool's behavior including sampling, export, summary, and response format. Comprehensive given complexity, 7 parameters, and output schema present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description's Args section explains each parameter, including defaults, types, and usage examples, adding significant meaning beyond the bare schema.

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?

Clearly states 'Get telemetry data for a specific lap' with specific verb and resource. Distinguishes from siblings like compare_telemetry and get_fastest_laps by focusing on single lap telemetry.

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 guidance on when to use export_path (data analysis, plotting, etc.) and mentions auto-export thresholds. Could more directly compare with siblings.

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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