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Kaggle MCP Server

by art-qalam-fr
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Python
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competitions_list

List and filter Kaggle competitions by search terms, category, deadlines, team counts, or recent updates to help users identify suitable data science challenges.

Instructions

Search and list Kaggle competitions.

    Args:
        search: Search term to filter competitions.
        category: Filter by category (e.g. featured, research, playground).
        sort_by: Sort order (latestDeadline, numberOfTeams, recentlyCreated).
        page: Page number for pagination.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
searchNo
sort_byNo
categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the operation (search/list) without mentioning that it is read-only, any rate limits, authentication needs, or pagination behavior beyond the page parameter.

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?

The description is brief and the parameter list is well-structured. It avoids extraneous text, but the parameter descriptions could be more concise (e.g., integrating hints about default values).

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

Completeness4/5

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

Given the tool's simplicity (4 parameters, no required fields, output schema exists), the description covers the main intent. However, it lacks information about pagination limits, error handling, or authentication, which are minor gaps.

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

Parameters4/5

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

The description compensates for 0% schema description coverage by providing plain-English explanations for each parameter: search term, category filter, sort order values, and page number. This adds useful meaning beyond the schema's default values and names.

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 uses a specific verb 'Search and list' with the resource 'Kaggle competitions', clearly indicating a filtered listing operation. It distinguishes from sibling tools like competition_get (single competition retrieval) and competition_submissions (list submissions).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives such as competition_get or the other competition list endpoints. The description implies usage for searching/filtering, but does not clarify exclusivity or when not to use it.

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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