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Microsoft Fabric MCP Server

Microsoft Fabric MCP Server

by Jasuni69
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

create_notebook

Create a new notebook in a Microsoft Fabric workspace. Use provided JSON content, or get a basic Hello Fabric notebook when content is omitted.

Instructions

Create a new notebook in a Fabric workspace.

Args:
    workspace: Name or ID of the workspace
    notebook_name: Name of the new notebook
    content: Content of the notebook (in JSON format). If not provided, creates a basic Hello Fabric notebook.
    ctx: Context object containing client information
Returns:
    A string containing the ID of the created notebook or an error message.

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": {
      "workspace": "<workspace>"
    },
    "name": "create_notebook"
  }
}

Input Schema

NameRequiredDescriptionDefault
contentNo
workspaceYes
notebook_nameNonew_notebook

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It usefully reveals that omitting content creates a basic Hello Fabric notebook and that the return value is a string ID or error message. However, it does not disclose behavior on name collisions, permission requirements, or side effects beyond creation, which matters for a mutating tool.

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 well structured with a one-line purpose, then compact Args and Returns sections. Every sentence adds value needed for invocation, and there is no filler. It is appropriately sized for a tool with three parameters.

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?

For a simple creation tool, the description covers the required workspace parameter, optional defaults, and the return format. It is missing guidance on distinguishing this tool from notebook-creation siblings and on what the JSON content structure should look like, but an agent can still make a valid minimal call using only the required workspace parameter.

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

Parameters5/5

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

Schema description coverage is 0%, so the description must compensate, and it does. It explains workspace as a name or ID, notebook_name as the name, content as JSON with a default fallback, and even documents ctx. This gives an agent enough meaning to invoke the tool correctly without relying on the bare property names.

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?

The description states a clear verb and resource: 'Create a new notebook in a Fabric workspace.' It is unambiguous about the core action, and the mention of Fabric workspace provides useful scope. However, it does not differentiate from sibling tools like create_fabric_notebook or create_pyspark_notebook, leaving potential selection ambiguity.

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?

There is no explicit guidance on when to use this tool versus alternatives. The description does not mention that create_fabric_notebook or create_pyspark_notebook might be more appropriate for framework-specific notebooks, nor does it state any conditions that should route an agent to this tool. The optional content behavior is noted, but not framed as a usage decision.

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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