Skip to main content
Glama
Surya96t

fastf1-mcp-server

get_driver_standings

Retrieve Formula 1 driver championship standings for any season from 1950 to present, including positions, points, wins, and team affiliations.

Instructions

Get driver championship standings.

Data source: Ergast API (via FastF1) Coverage: 1950-present

Args: year: Season year after_round: Standings after specific round (default: latest)

Returns: Ordered list of drivers with: position, driver code, full name, team, points, wins

Example: get_driver_standings(2024) → [ {"position": 1, "code": "VER", "name": "Max Verstappen", "team": "Red Bull", "points": 575, "wins": 19}, ... ]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
after_roundNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool returns (ordered list with specific fields) and includes an example output, adding valuable context beyond the input schema. However, it lacks details on potential limitations like rate limits or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose, followed by data source, parameters, returns, and an example. Every sentence earns its place by providing necessary information without redundancy, making it efficient and easy to parse.

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?

Given the tool's moderate complexity (2 parameters, no annotations, but with an output schema), the description is complete enough. It covers purpose, data source, parameters, return format, and includes an example, compensating for the lack of annotations and low schema coverage while leveraging the output schema for return value details.

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?

The schema description coverage is 0%, so the description must compensate fully. It explicitly documents both parameters ('year' and 'after_round') with clear semantics, including the default value for 'after_round' and the fact that 'year' is required, adding essential meaning not present in 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?

The description clearly states the tool's purpose with a specific verb ('Get') and resource ('driver championship standings'), and it distinguishes this tool from siblings like 'get_constructor_standings' and 'list_drivers' by specifying it returns championship standings rather than basic driver lists or constructor data.

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?

The description provides clear context for usage by specifying the data source (Ergast API via FastF1) and coverage (1950-present), which helps determine when this tool is appropriate. However, it does not explicitly state when to use alternatives like 'get_constructor_standings' or 'list_drivers' beyond the implied differentiation in purpose.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Surya96t/fastf1-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server