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fabric-dw-mcp-cli

by sdebruyn
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Python
Remote

load_table_from_url

Load data into a Microsoft Fabric Data Warehouse table from a remote URL using COPY INTO. Supports CSV and Parquet files with optional credentials for secured URLs.

Instructions

Load data into a Data Warehouse table via COPY INTO from a remote URL.

Supported file types: CSV, PARQUET. JSON remote URLs require downloading and converting locally first; use the CLI tables load command for local files (including JSON).

For OneLake or same-tenant URLs, no credential is needed. For secured external URLs (Azure Blob Storage SAS, etc.), supply credential_type and the appropriate secret/identity values.

CAUTION: This operation loads data into the target table. Confirm the source URL and target table before calling.

Note: secret / identity values are accepted but are NEVER logged or included in any debug output.

Args: workspace: Workspace name or GUID. item: Warehouse name or GUID. SQL Analytics Endpoints are rejected. qualified_name: Dot-separated qualified table name, e.g. dbo.sales. url: Source URL (OneLake DFS URL or external Azure Blob URL). file_type: CSV or PARQUET. credential_type: Credential type for the source URL. secret: Credential secret (not logged). identity: Identity for managed-identity or service-principal. delimiter: CSV column delimiter. has_header: Whether the CSV file has a header row. encoding: CSV file encoding. field_quote: CSV field-quote character. row_terminator: CSV row terminator. max_errors: Maximum errors before aborting. rejected_row_location: URL for rejected-row output.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
workspaceYes
itemYes
qualified_nameYes
urlYes
file_typeYesFile type to load. JSON is not supported for remote URLs; download and convert locally first.
credential_typeNoCredential type for secured external URLs. Use 'none' for OneLake or public URLs.none
secretNoCredential secret (SAS token, client secret, or account key). NEVER log or echo this value.
identityNoIdentity value for managed-identity or service-principal credential types.
delimiterNoCSV column delimiter (e.g. ',', '\t').
has_headerNoWhen True, the first CSV row is a header and is skipped.
encodingNoCSV file encoding (e.g. 'UTF8', 'UTF8BOM').
field_quoteNoCSV field-quote character.
row_terminatorNoCSV row terminator (e.g. '\n', '\r\n').
max_errorsNoMaximum number of errors before aborting.
rejected_row_locationNoURL to write rejected rows to.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the operation loads data (caution) and that secret/identity are never logged. However, it does not specify whether the operation appends or overwrites, or any other side effects like schema changes.

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 clear paragraphs and technical terms formatted with backticks. It is front-loaded with the main action and keeps sentences purposeful. It is concise yet comprehensive.

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 the tool's complexity (15 parameters, credential handling, multiple file types), the description covers the key aspects: purpose, supported types, credential guidance, and parameter explanations. Since an output schema exists, return values are not required. It lacks details on error handling but is sufficient for typical use.

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

Parameters3/5

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

Schema coverage is 73%, and the description adds context for several parameters (e.g., credential_type, secret not logged, item rejection of SQL Analytics Endpoints). Some descriptions overlap with schema descriptions, but overall it adds meaning beyond the schema.

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 clearly states the tool loads data into a Data Warehouse table via COPY INTO from a remote URL. It specifies supported file types (CSV, PARQUET) and notes JSON requires local conversion. However, it does not explicitly differentiate from the sibling 'import_table_from_url' tool, though it mentions an alternative for local files.

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 when to use (remote URLs) and when not to (local files, JSON). It gives an alternative (CLI tables load command) and explains credential requirements. It includes a caution, which aids decision-making.

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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