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mcp-server-jupyter

mcp-server-jupyter

by ihrpr
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

add_cell

Insert a new cell into a Jupyter notebook at a specified position, with support for custom source code and cell type.

Instructions

Add a new cell to the notebook at the specified position.

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>",
      "source": "<source>"
    },
    "name": "add_cell"
  }
}

Input Schema

NameRequiredDescriptionDefault
sourceYes
positionNo
cell_typeNo
notebook_pathYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.9

TDQS

B3.1/5.0
Behavior2/5

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

No annotations are present, so the description must carry the behavioral disclosure burden. It only states that a cell is added at a position, but does not mention side effects, default cell_type when omitted, behavior when position is omitted, or whether the notebook needs to be open.

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 a single, front-loaded sentence with no filler. All words contribute meaning, making it very easy to parse and remember.

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?

For a mutating tool with four parameters and no annotations or output schema, this description is too sparse to support correct invocation. It omits parameter semantics, defaults, and side effects, leaving the agent to guess how to supply 'source' and 'cell_type'.

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 coverage is 0%, so the description must compensate for missing parameter explanations. It only clarifies the 'position' parameter ('at the specified position'), but leaves 'source', 'cell_type', and 'notebook_path' semantically unexplained.

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 uses the specific verb 'Add' and names the resource 'cell' and 'notebook', clearly distinguishing it from sibling tools like edit_cell and execute_cell. The phrase 'at the specified position' directly ties to the position parameter, making the tool's function unambiguous.

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 is provided about when to use this tool versus edit_cell or execute_cell, and no exclusions or prerequisites are mentioned. The description only states the action, leaving the agent to infer the appropriate use case.

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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