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jupyter-notebook-mcp

jupyter-notebook-mcp

by g0g5
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

load_notebook

Load and validate a Jupyter notebook from disk, return markdown blocks, and autosave the currently open notebook before switching.

Instructions

Load and validate a notebook from disk, then return markdown blocks.

Autosaves the currently open notebook before switching.

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": {
      "path": "<path>"
    },
    "name": "load_notebook"
  }
}

Input Schema

NameRequiredDescriptionDefault
pathYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose two non-obvious traits: the load performs validation, and it autosaves the currently open notebook before switching (an implicit mutation side effect). It omits failure/error behavior when validation fails and any permission requirements.

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?

Two short sentences with zero filler; the core action is front-loaded and the side effect is a separate, well-placed clause.

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

Completeness4/5

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

An output schema exists so return values need not be explained further, and the mutation side effect is called out. Only edge-case behavior (invalid notebook, missing file) is left unspecified for this one-parameter 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?

Schema coverage is 0% and the single 'path' parameter is undocumented in the schema. 'From disk' adds meaningful context that this is a filesystem path rather than a notebook identifier, but format details (absolute vs relative, extensions) are absent.

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?

States a specific verb+resource: 'Load and validate a notebook from disk,' plus the return shape ('markdown blocks'). The verb 'load' clearly contrasts with the sibling save_notebook, though no sibling is named explicitly.

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 when-to-use or when-not guidance, and no routing against plausible alternatives such as from_markdown or read_cell. The only contextual sentence concerns a side effect, not selection criteria.

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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