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sdebruyn

fabric-dw-mcp-cli

by sdebruyn

import_table_from_url

Load data from a remote URL into an existing Microsoft Fabric Data Warehouse table using COPY INTO. Supports CSV and Parquet files with configurable handling for existing tables.

Instructions

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

The target table must already exist and have a compatible schema. For auto-create with schema inference from local files, use the CLI tables load --file --create command instead.

if_exists controls behaviour when the table already exists:

  • "fail" (default): raise an error if the table already exists.

  • "append": load rows into the existing table without modification.

  • "truncate": TRUNCATE the existing table first, then load. Requires FABRIC_MCP_ALLOW_DESTRUCTIVE=1. Raises an error if the table does not exist.

  • "replace": not supported for remote URLs (schema inference requires downloading the file). Use "truncate" to keep the current schema, or download locally and use the CLI with --create --if-exists replace.

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 supply credential_type and the appropriate secret/identity values.

CAUTION: truncate is permanently destructive. 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. if_exists: Policy when the target table already exists. 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. JSON is not supported for remote URLs; download and convert locally first.
if_existsNoWhat to do when the target table already exists. 'fail': error (default). 'append': load into existing table. 'truncate': TRUNCATE then load (destructive). 'replace': DROP + recreate from inferred schema, then load (destructive).fail
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

Behavior4/5

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

With no annotations, the description covers key behaviors: destructive truncate requiring an environment variable, secret never logged, JSON not supported for remote URLs, and rejection of SQL Analytics Endpoints. Lacks explicit details on error handling or timeouts, but output schema helps.

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?

Front-loaded with the main action, then detailed sections. Slightly verbose with CLI references and extensive if_exists breakdown, but well-organized and each sentence adds value.

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 16 parameters and 5 required, the description covers prerequisites, file types, credentials, destructive behavior, and unsupported operations. Lacks mention of performance or timeouts, but output schema exists and overall it's thorough.

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 coverage is high (75%), so baseline is 3. The description adds value for key parameters like if_exists (detailed policy explanations), file_type (JSON exclusion), and credential_type/secret (logging behavior). Some CSV parameters are not further explained beyond schema.

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 clearly states the tool loads data into an existing Data Warehouse table via COPY INTO from a remote URL. It distinguishes from siblings by specifying the method and noting alternative CLI commands for auto-create with 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 Guidelines5/5

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

Explicitly states target table must exist, compatible schema required, and provides when-to-use vs alternatives. Details if_exists behavior, supported file types (CSV, PARQUET), unsupported JSON, credential requirements, and a caution about destructive truncate.

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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