Skip to main content
Glama
sdebruyn

fabric-dw-mcp-cli

by sdebruyn

create_function

Create a new T-SQL user-defined function in a Microsoft Fabric warehouse or SQL Analytics endpoint using DDL.

Instructions

Create a new T-SQL user-defined function.

Scalar UDFs and inline TVFs are preview features on Fabric DW as of mid-2026. Function DDL is supported on both Data Warehouses and SQL Analytics Endpoints.

CAUTION: body is executed verbatim as DDL. Ensure the body matches the user's intent before calling this tool.

The body should include the parameter list, RETURNS clause, and function body (everything that follows CREATE FUNCTION [schema].[name]).

Args: workspace: Workspace name or GUID. item: Warehouse or SQL Analytics Endpoint name or GUID. qualified_name: Dot-separated qualified function name, e.g. dbo.fn_clean_input. body: The function body (parameter list, RETURNS clause, and implementation).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceYes
itemYes
qualified_nameYes
bodyYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations present, so the description carries full burden. It discloses that 'body' is executed verbatim as DDL and explains what the body should include. This is critical behavioral context. However, it omits prerequisites (e.g., permissions) or error conditions like if function already exists.

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?

Description is well-structured: starts with purpose, then context about preview features, a CAUTION, and parameter details. The caution and example add value without excessive verbosity. Slightly dense but appropriate for the complexity.

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?

Given that an output schema exists, return values are not needed. The description covers what the tool does, behavioral warnings, and parameter semantics. It does not discuss error handling or confirmation, but for a creation tool this is adequate.

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%, but the description provides detailed explanations for all four parameters in the Args section. It includes examples (e.g., 'qualified_name' with 'dbo.fn_clean_input') and clarifies the content of 'body'. This fully compensates for the missing schema descriptions.

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?

Description clearly states 'Create a new T-SQL user-defined function' with specific verb and resource. It distinguishes from siblings like 'create_procedure' and 'create_view' by focusing on functions, and adds context about supported environments (Fabric DW, Data Warehouses, SQL Analytics Endpoints).

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?

Provides context about preview features and a CAUTION about executing DDL verbatim, but does not explicitly compare to similar creation tools (e.g., when to use create_procedure instead). No exclusion or alternative guidance is given.

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/sdebruyn/fabric-dw-mcp-cli'

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