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Jupyter Notebook MCP Server

Jupyter Notebook MCP Server

by shwetalsoni
OverviewSchemaSourceRelated ServersDiscussionsAdmin
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get_notebook_info

Retrieve metadata and statistics from a Jupyter notebook by providing its absolute file path. Get details like cell counts and kernel info.

Instructions

Get basic information about a Jupyter notebook.

Args:
    notebook_path: Absolute path to the .ipynb file

Returns:
    Notebook metadata and statistics

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": {
      "notebook_path": "<notebook_path>"
    },
    "name": "get_notebook_info"
  }
}

Input Schema

NameRequiredDescriptionDefault
notebook_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description must carry full burden of behavioral transparency. It fails to disclose traits such as read-only nature, required permissions, potential errors, or whether the info is always available. The docstring simply restates the purpose without behavioral implications.

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 extremely concise, consisting of one clear sentence for purpose and a brief docstring. No extraneous information. It is well-structured and front-loaded with the main purpose.

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?

The description is minimally adequate given the tool's simplicity (1 param, no output schema). It states the return value as 'Notebook metadata and statistics', which is vague but sufficient. More details about what specific metadata is returned would improve completeness for an agent.

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 description adds meaning to the parameter beyond the input schema: it specifies that notebook_path is an 'Absolute path to the .ipynb file'. This is helpful, but still lacks details like path format, required permissions, or handling of invalid paths. Schema coverage is 0%, so the description provides minimal compensation.

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: 'Get basic information about a Jupyter notebook.' It uses a specific verb 'get' and a resource 'basic information about a Jupyter notebook', distinguishing it from sibling tools like add_cell_to_notebook or execute_notebook_cell which perform different actions.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention scenarios where getting basic info is preferable over reading cells or executing the notebook. The docstring only describes the tool's own function without context of sibling tools.

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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