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universal-notebook-mcp

universal-notebook-mcp

by am-3
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

notebook_list_active_kernels

List all notebooks with active running kernels in the current session, returning their absolute paths.

Instructions

List notebooks that currently have a running kernel in this session.

Returns the absolute resolved paths of notebooks with live kernels.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "notebook_list_active_kernels"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior3/5

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

With no annotations provided, the description carries full burden. It mentions the output (absolute paths) but does not disclose any behavioral traits like side effects, performance, or whether it is read-only. For a 0-parameter list operation, this is adequate but not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description consists of two concise, front-loaded sentences. Every sentence adds value: the first explains the purpose, the second details the return format.

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

Completeness5/5

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

Given the tool has 0 parameters and an output schema exists, the description is sufficiently complete. It clearly defines what the tool does and what it returns, leaving no major 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?

There are 0 parameters, so baseline is 4. The description does not need to add parameter information; it correctly focuses on the tool's behavior.

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 clearly states the verb 'list', the resource 'notebooks with running kernels', and the scope 'in this session'. It also specifies the return value (absolute resolved paths), which distinguishes it from siblings like notebook_list_kernels.

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

Usage Guidelines3/5

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

The description implies usage when needing to find notebooks with active kernels, but does not explicitly state when to use this tool versus alternatives such as notebook_list_kernels. No guidance on when-not-to-use is 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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