Kaggle (Seif-Sameh) MCP Server
mcp-server-kaggle
PyPI
v0.1.1
Published by seif-sameh — no publish provenance, so origin is unverified, but the source is public: the repository link below is self-declared yet readable, so you can inspect the code before adopting it.
A Model Context Protocol (MCP) server for the Kaggle API
The grade answers one question — how safe is this server for you to adopt — so it is computed in two auditable stages. Nothing below is an opinion or an LLM's guess; every line is a real term the deterministic engine applied, and the same input always yields the same number.
1. Threat score — 100 − 0 = 100. What the published surface and source actually contain:
The deterministic scan raised no scored threat in the surface it inspected — the threat score stayed at 100. Capability observations and advisory notes are recorded but never lower it.
2. Client adoption risk — 100 − 4 = 96. Three small, subtract-only factors that reflect your risk in adopting it — a clean scan proves less on a powerful, unverified or barely-inspectable package, so the grade says so plainly:
| Points | Adoption-risk factor |
|---|---|
| −3 | capability blast radius (moderate) — client exposure if the model is manipulated |
| −1 | publisher verification (public source) — no provenance, but the source is public and inspectable |
Capability observations and info notes are shown under Findings but never scored.
Open any row's finding below for the file, line and evidence behind a deduction.
Findings 0
Tools 39
Each tool and what it can reach — statically extracted from the published source.
competition_download_fileingests untrusted inputcompetition_download_filesingests untrusted inputcompetition_leaderboard_downloadingests untrusted inputcompetition_list_filesreads sensitive datadataset_download_fileingests untrusted inputdataset_download_filesingests untrusted inputdataset_list_filesreads sensitive datadataset_metadataingests untrusted inputkernel_list_filesreads sensitive datakernel_outputingests untrusted input
Show 29 more tools ↓
kernel_pullingests untrusted inputmodel_instance_version_downloadingests untrusted inputcompetition_leaderboard_viewno sensitive capabilitycompetition_submissionsno sensitive capabilitycompetition_submitno sensitive capabilitycompetitions_listno sensitive capabilitydataset_createno sensitive capabilitydataset_create_versionno sensitive capabilitydataset_initializeno sensitive capabilitydataset_statusno sensitive capabilitydatasets_listno sensitive capabilitykernel_initializeno sensitive capabilitykernel_pushno sensitive capabilitykernel_statusno sensitive capabilitykernels_listno sensitive capabilitymodel_createno sensitive capabilitymodel_deleteno sensitive capabilitymodel_getno sensitive capabilitymodel_initializeno sensitive capabilitymodel_instance_createno sensitive capabilitymodel_instance_deleteno sensitive capabilitymodel_instance_getno sensitive capabilitymodel_instance_initializeno sensitive capabilitymodel_instance_updateno sensitive capabilitymodel_instance_version_createno sensitive capabilitymodel_instance_version_deleteno sensitive capabilitymodel_instance_version_filesno sensitive capabilitymodel_updateno sensitive capabilitymodels_listno sensitive capability
What this scan could not see
- Tools were statically extracted from the published source (39 recovered), not enumerated from a running server. Tool-poisoning, Unicode-smuggling, capability and toxic-flow analysis ran on this inferred surface, but a mis-parsed registration could be missed or mis-attributed, so tool-derived findings are capped below “confirmed”. To grade the real runtime surface, scan the running server: --command "npx -y <package>".
Versions 1
Scan history per published version. The engine is deterministic — the same version always yields the same score, so a changed score means the package itself changed.
| Version | Score | Findings | Engine | Scanned |
|---|---|---|---|---|
v0.1.1 latest |
A 96/100 | 0 | 1.13.0 | 2026-08-25 |
Embed this score
Show this server's live Trust Score in your README, docs or website. The badge is served straight from the registry and updates automatically after every rescan — no API key needed. It links back to this page, so anyone who sees the grade can also read the findings behind it instead of taking a number on faith.
Verify this score yourself
The score above is reproducible: the same package version always yields the same result. Run it locally or over the free API — no account, no LLM, fully deterministic.
npx mcptrustchecker scan mcp-server-kaggle --online --registry pypiOther implementations of Kaggle 2
Independent packages implementing the same tool, scanned with the same engine. Compare all 3 side by side →
A full-featured MCP server wrapping the Kaggle API — 52 tools across competitions, datasets, kernels, models, benchmarks, and discussions
A MCP server for kaggle apis
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