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Kaggle MCP Server

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competition_top_kernels

List public kernels and notebooks for a Kaggle competition, sorted by public score, votes, or other metrics.

Instructions

List top public kernels/notebooks for a competition, sorted by public score.

    Note: Kaggle API does not return the score value for active competitions,
    but DOES sort by score. Scores shown are extracted from notebook titles
    (e.g. '[44/50]', '[0.371]') where authors include them.

    Args:
        competition: Competition URL suffix (e.g. 'titanic').
        sort_by: Sort order — scoreDescending (default), scoreAscending,
                 voteCount, hotness, dateCreated, dateRun, commentCount.
        page_size: Number of results (max 100).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sort_byNoscoreDescending
page_sizeNo
competitionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.4/5.0
Behavior4/5

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

No annotations provided. The description discloses important behavioral details: the API does not return scores for active competitions, and scores shown are extracted from notebook titles. This informs the user about potential missing data.

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?

Extremely concise: a clear one-line purpose followed by a succinct numbered list of parameters. No wasted words, front-loaded with the key action.

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 complexity, parameter count, and lack of annotations/output schema details, the description covers the purpose, parameters, and a key behavioral nuance (missing scores for active competitions). It is complete for a list-oriented tool.

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?

Adds significant meaning beyond the schema: explains competition as 'Competition URL suffix' with example, lists all possible sort_by values, and gives page_size with max limit. With 0% schema coverage, the description fully compensates.

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 lists top public kernels for a competition sorted by public score, distinguishing it from sibling tools like competition_leaderboard or kernels_list.

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?

Provides some usage context by noting that the API doesn't return score values for active competitions but still sorts by score. However, it does not explicitly compare to alternatives like competition_leaderboard or kernels_list.

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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