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Jasuni69

Microsoft Fabric MCP Server

by Jasuni69

set_lakehouse

Sets the session's active lakehouse by providing its name or ID, so all subsequent Microsoft Fabric operations run against the correct data context.

Instructions

Set the current lakehouse for the session.

Args:
    lakehouse: Name or ID of the lakehouse
    ctx: Context object containing client information

Returns:
    A string confirming the lakehouse has been set.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lakehouseYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description carries the disclosure burden. It discloses that the operation is session-scoped and that a confirming string is returned, but it does not mention overwriting behavior, error conditions, or any permission requirements. This is adequate but minimal for a simple stateful setter.

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 well-structured with a purpose statement, Args, and Returns sections. The main call to action is front-loaded, and there is little wasted text, though the undocumented 'ctx' parameter introduces slight noise.

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 one-parameter setter with no output schema, the description is reasonably complete: it explains what the tool does, what the parameter means, and what the return value is. It does not provide usage guidance or behavioral edge cases, but the low complexity keeps the missing information minor.

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?

The input schema only defines 'lakehouse' as a string, and the description adds useful semantics by stating it accepts a 'Name or ID.' This fills a real gap at 0% schema description coverage. However, the description also lists 'ctx' as an argument, which is not present in the input schema and adds minor confusion.

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 states a clear verb and resource: 'Set the current lakehouse for the session.' This distinguishes the tool from sibling setters like set_workspace, set_warehouse, and set_table by explicitly naming the lakehouse as the target.

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

Usage Guidelines3/5

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

The phrase 'for the session' implies a stateful context and suggests this tool is used when the agent needs a default lakehouse for subsequent operations. However, it does not explicitly state when to use this tool versus alternatives like set_workspace or set_warehouse, and provides no 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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