jupyter-editor-mcp

by jsamuel1

Overview Schema Source Related Servers Discussions Admin

Python

Local

ipynb_validate_notebooks_batch

Validate multiple Jupyter Notebooks in batch by providing filepaths, receiving validation status for each notebook.

Instructions

Validate multiple Jupyter Notebooks (.ipynb).

Args: ipynb_filepaths: List of notebook paths (absolute paths preferred)

Returns: Dict with 'results' mapping filepath to validation status

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": {
      "ipynb_filepaths": "<ipynb_filepaths>"
    },
    "name": "ipynb_validate_notebooks_batch"
  }
}

Input Schema

Name	Required	Description	Default
`ipynb_filepaths`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.2Aug 7, 2026

TDQS

A3.5/5.0

Behavior2/5

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

With no annotations provided, the description carries full burden for disclosing behavior. It mentions the return format ('Dict with results mapping filepath to validation status') but does not clarify what validation entails, whether it makes modifications, or how errors are handled. This is minimal transparency for a tool with no safety metadata.

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 is very concise and well-structured: a clear one-line purpose followed by Args and Returns sections. Every sentence provides necessary information and nothing is wasted.

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

Completeness3/5

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

Given the tool's simplicity (one parameter, output schema exists), the description provides adequate structure but lacks detail on the validation status values or error behavior. It is complete enough for a straightforward batch operation but leaves several behavioral questions unanswered.

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?

The input schema has 0% description coverage, so the description must compensate. It explains the parameter 'ipynb_filepaths' as 'List of notebook paths' and adds the valuable hint 'absolute paths preferred'. This adds some meaning beyond the bare schema, though the parameter name already conveys most of the intent.

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 tool's function with a specific verb and resource: 'Validate multiple Jupyter Notebooks (.ipynb)'. The use of 'multiple' and 'batch' in the tool name distinguishes it from the sibling 'ipynb_validate_notebook', making the purpose unambiguous.

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 for validating multiple notebooks but does not explicitly state when to use this over the singular sibling alternative. There is no clear 'when-to-use' or 'use-cases' guidance beyond the general purpose, and no exclusions are mentioned.

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