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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

generate_dbt_profile

Generate dbt project files for Fabric Data Warehouse, including profiles, project config, sources, and dependencies. Handles authentication via Entra ID without exposing secrets.

Instructions

Generate dbt-fabric project file contents for a Fabric Data Warehouse.

Returns the generated file contents as text strings. Because the MCP server cannot write to the caller's local filesystem, it is the caller's responsibility to write the returned strings to the appropriate files.

Authentication note: dbt-fabric is Entra-only. ServicePrincipal mode emits {{ env_var(...) }} placeholders for tenant_id / client_id / client_secret — no literal secrets are included in the output.

Args: workspace: Workspace name or GUID. item: Warehouse name or GUID. project_name: dbt project name (default: sanitized warehouse name). profile_name: dbt profile name (default: same as project_name). schema: Default schema (default: dbo). target: dbt output target name (default: dev). threads: Number of dbt threads (default: 4). authentication: dbt-fabric authentication string — auto (DefaultAzureCredential), CLI (interactive), or ServicePrincipal. Defaults to the server's auth mode. with_sources: When True, generate a _sources.yml from the warehouse's actual schemas and tables.

Returns: A dict with keys: - profiles_yml: content for profiles.yml. - dbt_project_yml: content for dbt_project.yml. - sources_yml: content for models/staging/_sources.yml. - requirements_txt: content for requirements.txt. - gitignore: content for .gitignore.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceYes
itemYes
project_nameNo
profile_nameNo
schemaNodbo
targetNodev
threadsNo
authenticationNo
with_sourcesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully discloses behavioral traits: it does not write to filesystem, returns file contents as text strings, and explains how secrets are handled (placeholders in ServicePrincipal mode). It also lists the exact return keys.

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 well-structured with an intro, authentication note, Args, and Returns sections. However, it is slightly verbose, repeating some default values already present in the schema, but overall clear and organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 9 parameters, 2 required, and 0% schema coverage, the description covers all parameters and explains the output structure (dict with keys profiles_yml, dbt_project_yml, etc.). The output schema exists, but the description adds value by listing keys.

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?

The input schema has 0% description coverage, but the description's 'Args' section thoroughly explains each parameter with meaning, default values, and special notes (e.g., authentication options: 'auto','CLI','ServicePrincipal'). 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?

The description explicitly states the tool's purpose: 'Generate dbt-fabric project file contents for a Fabric Data Warehouse.' It clearly specifies the verb 'generate' and the resource 'dbt-fabric project file contents,' distinguishing it from sibling tools that perform direct database operations.

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

Usage Guidelines4/5

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

The description provides clear guidance on usage, such as the caller's responsibility to write files and the authentication note about Entra-only and placeholders. While it doesn't explicitly contrast with alternatives, the unique purpose makes usage context clear.

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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