Skip to main content
Glama
qtalen

jupyter-kernel-mcp

by qtalen

use_notebook

Open or create a Jupyter notebook file and attach it to the session. Optionally specify a kernel name.

Instructions

Open or create a notebook file and attach it to the session.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
kernel_nameNopython3

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided; description fails to disclose conditions (e.g., behavior when file exists vs. new), side effects, or permissions required. Vague about 'attach to session' implications.

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?

Single sentence of 10 words, front-loaded with action and object. Efficient but omits necessary detail; could be expanded without losing conciseness.

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?

Given output schema exists and sibling tools, description fails to explain return values or how this tool fits into notebook workflow. Missing essential context for a tool with 2 parameters and no schema descriptions.

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

Parameters2/5

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

Schema has 0% coverage and description does not explain 'path' (e.g., format, required extension) or 'kernel_name' (e.g., allowed kernels). No added semantic value beyond raw schema.

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?

Description clearly states verb ('open or create') and object ('notebook file') with result ('attach to session'), distinguishing it from sibling tools like 'read_notebook' or 'execute_cell'.

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 vs. alternatives (e.g., 'connect_to_jupyter', 'read_notebook'). Missing context for decision-making.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/qtalen/jupyter-kernel-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server