Jupyter MCP Server is a Model Context Protocol server that lets AI agents connect to and manage Jupyter notebooks in real time. It supports notebooks running locally or on hosted platforms, and its catalogue add-ons provide commands and skills for working with those notebooks.
Borrowing it
Nothing to install: this file belongs to datalayer/jupyter-mcp-server. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/datalayer/jupyter-mcp-server/main/.github/skills/code-review/SKILL.mdgit clone --depth 1 https://github.com/datalayer/jupyter-mcp-serverWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/datalayer/jupyter-mcp-server/code-review)<a href="https://agentmods.dev/skills/datalayer/jupyter-mcp-server/code-review"><img src="https://agentmods.dev/badge/skills/datalayer/jupyter-mcp-server/code-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/datalayer/jupyter-mcp-server/code-review"><img src="https://agentmods.dev/badge/skills/datalayer/jupyter-mcp-server/code-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00062 | $0.01774 |
| Opus 5.5 | $0.00025 | $0.00710 |
| Sonnet 5.5 | $0.00012 | $0.00355 |
| Haiku 4.5 | $0.00006 | $0.00177 |
Grade A, and why
code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reviewing a change to Jupyter MCP Server
This server is what an agent talks to when it reads and runs somebody's notebooks. Most of what goes wrong here is quiet: a test that passes without exercising its subject, a tool that answers an empty list instead of an error, a page that documents a flag nothing reads. None of it fails loudly, and all of it has happened.
Review for those first. Ordinary bugs are usually caught by the suite.
Start here: does the test exercise its subject?
The most common defect in this repository is not broken code — it is a test that passes for a reason other than the one it claims. Two real examples:
test_an_expired_task_is_gone…calledstore.get()beforestore.list().get()deletes the expired record itself, so by the timelist()ran there was nothing left to sweep and the sweep never executed.list()was iterating a dictionary while popping from it — a guaranteedRuntimeError— and the test named after that path was green.tests/test_mcpb_version_sync.pynever ran at all. It importsscripts.sync_mcpb_version,scripts/had no__init__.py, and the module failed at collection. The suite was green and the version drift it guards was unguarded.
So for every new or changed test, ask:
- Would it fail if the behaviour were removed? If you cannot say yes, delete the assertion or strengthen it. Say so in the review.
- Does an earlier line already do the work? A setup call that cleans up, caches, or short-circuits leaves the code under test unreached.
- Does it assert a cell, or a substring of everything?
assert "no" in outputpasses on almost any English. Pull the row or the field apart. - Does it signal by raising inside a
try? Several functions here catchExceptiondeliberately — a test that raises to signal gets swallowed and asserts nothing. Record into a list and assert the list. - Does it set an environment variable that was already read at import?
config-style modules read once. Patch the attribute, not the environment.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 154 lines · 62 tokens per session scan A 2a80e33d9d7b
code-review is a skill published in the GitHub repository datalayer/jupyter-mcp-server (1,315 stars, last pushed 2d ago), licensed BSD-3-Clause. It adds 62 tokens to every session and 1,774 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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m1nd-first
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