Skip to main content
Glama

read_notebook

Read and convert a Mathematica notebook to markdown, Wolfram, outline, JSON, or plain text. Filter specific cell types and include or exclude outputs.

Instructions

[PRIMARY] Read a Mathematica notebook with backend-aware dispatch.

Prefer this over read_notebook_content, convert_notebook, get_notebook_outline, parse_notebook_python, and get_notebook_cell unless you need a specific legacy backend or narrow low-level operation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
output_formatNomarkdown
cell_typesNo
include_outputsNo
backendNo
viewNosemantic
include_alternatesNo
truncation_thresholdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

Mentions 'backend-aware dispatch' as a key behavior, but does not elaborate on side effects, permissions, or other behavioral traits. With no annotations, this is a moderate disclosure.

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 sentences, each with a distinct purpose, front-loaded with primary function and followed by usage guidelines. No superfluous text.

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?

While the output schema exists, the description does not explain the various output formats or other parameters, making it less complete for a tool with 8 parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description provides no explanation of the 8 parameters, leaving the agent to rely solely on parameter names and schema enums.

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?

Clearly states it reads a notebook with backend-aware dispatch, and explicitly names sibling tools to differentiate.

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

Usage Guidelines5/5

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

Provides explicit guidance on when to prefer this tool over specific alternatives, and when not to use it.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AbhiRawat4841/mathematica-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server