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Microsoft Fabric MCP Server

Microsoft Fabric MCP Server

by Jasuni69
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

create_fabric_notebook

Creates a new Microsoft Fabric notebook in a specified workspace, using integration or streaming templates to set up optimized code structures for data workflows.

Instructions

Create a new notebook optimized for Microsoft Fabric using advanced templates.

Args:
    workspace: Name or ID of the workspace
    notebook_name: Name of the new notebook
    template_type: Type of Fabric template ('fabric_integration', 'streaming')
    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>",
      "notebook_name": "<notebook_name>"
    },
    "name": "create_fabric_notebook"
  }
}

Input Schema

NameRequiredDescriptionDefault
workspaceYes
notebook_nameYes
template_typeNofabric_integration

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It explicitly states a new notebook is created and that the return value is an ID or error message, which covers the immediate outcome. However, it does not explain what 'advanced templates' do, whether the operation is idempotent, or what permissions are required.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the main purpose, followed by a structured Args/Returns block. The inclusion of 'ctx' as an argument not present in the schema adds mild noise, but overall the text is efficient.

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?

For a create operation with no output schema and no annotations, the description covers the core parameters and return format. It is incomplete in that it does not explain how this tool relates to the generic create_notebook and create_pyspark_notebook siblings, nor the meaning of 'advanced templates'.

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

Parameters4/5

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

Schema description coverage is 0%, and the Args section compensates by explaining workspace as name or ID, notebook_name, and template_type with its allowed values. The mention of 'ctx' is confusing because it is not present in the input schema, but the other parameter meanings are genuinely clarified.

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 opens with a clear verb and resource: 'Create a new notebook optimized for Microsoft Fabric using advanced templates.' It states what the tool does but does not explicitly differentiate it from sibling tools like create_notebook or create_pyspark_notebook, so it misses the top score for sibling distinction.

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 such as create_notebook or create_pyspark_notebook. It lists arguments and return behavior but no context, prerequisites, or exclusions.

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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