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mcp-kaggle-tool

mcp-kaggle-tool

by MikeyBeez
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

kaggle_download_notebook_output

Download completed notebook outputs to a local directory using the notebook's kernel slug.

Instructions

Download the output of a completed notebook

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "kernelSlug": "<kernelSlug>"
    },
    "name": "kaggle_download_notebook_output"
  }
}

Input Schema

NameRequiredDescriptionDefault
kernelSlugYesNotebook identifier (username/notebook-slug)
outputPathNoLocal directory to save outputs./kaggle-outputs

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations present, and the description only states the basic action without disclosing behavioral details like requirements for notebook completion, authentication, 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.

Conciseness4/5

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

One concise sentence that efficiently states the purpose, though it could be slightly more informative without sacrificing brevity.

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

Completeness2/5

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

No output schema and no annotation; the description fails to mention important context such as what happens for incomplete notebooks or how output path is used. Incomplete for a download tool.

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

Parameters3/5

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

Input schema covers 100% of parameters with clear descriptions, so the description adds minimal value beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Download') and resource ('output of a completed notebook'), but does not differentiate from sibling tools like kaggle_get_notebook_status.

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 guidance on when to use this tool over alternatives; no context about prerequisites or exclusions provided.

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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