Microsoft Fabric Development Expert

Expert guidance for Microsoft Fabric using the Fabric MCP Server. Access comprehensive API specifications, item definitions, best practices, and OneLake management capabilities - all running locally without connecting to live environments.

Core Capabilities

1. API Discovery - Enumerate and access Fabric workload APIs
2. Schema Access - Get JSON schemas for item definitions
3. Best Practices - Access guidance and examples
4. OneLake Management - File and item operations
5. Local-First - All tools run locally for reference and development

Quick Reference - MCP Tools

API Access Tools

Tool	Purpose
publicapis_list	List all Fabric workload types
publicapis_get	Get OpenAPI spec for workload
publicapis_platform_get	Get platform API specs
publicapis_bestpractices_get	Get best practices documentation
publicapis_bestpractices_examples_get	Get API request/response examples
publicapis_bestpractices_itemdefinition_get	Get item schema definitions

OneLake Tools

Tool	Purpose
onelake download file	Download files from OneLake
onelake upload file	Upload files to OneLake
onelake file list	List files in OneLake
onelake file delete	Delete files from OneLake
onelake directory create	Create directories
onelake directory delete	Delete directories
onelake item list	List workspace items
onelake item list-data	List items via DFS endpoint
onelake item create	Create new Fabric items

API Discovery Tools

publicapis_list

List all Microsoft Fabric workload types that have public API specifications.

When to use:

• Starting Fabric development
• Exploring available workloads
• Finding workload-specific APIs

Workload Types Include:

• Lakehouses
• Data Pipelines
• Semantic Models (Power BI)
• Notebooks
• Spark Job Definitions
• Warehouses
• KQL Databases
• Eventhouse
• Real-Time Intelligence
• ML Models
• ML Experiments

publicapis_get

Retrieve complete OpenAPI/Swagger specification for a specific workload.

Parameters:

Parameter	Type	Required	Description
workload	string	Yes	Workload type name

Workload Examples:

• DataPipeline
• Lakehouse
• SemanticModel
• Notebook
• SparkJobDefinition
• Warehouse
• KQLDatabase

publicapis_platform_get

Access OpenAPI specifications for Microsoft Fabric platform-level APIs.

Platform APIs Include:

• Workspace management
• Item management (generic)
• Permission management
• Capacity operations
• Deployment pipelines
• Git integration

publicapis_bestpractices_get

Get embedded best practice documentation for Fabric development.

Parameters:

Parameter	Type	Required	Description
topic	string	Yes	Best practice topic

Topics Include:

• Pagination patterns
• Error handling
• Retry/backoff strategies
• Authentication
• Rate limiting
• API versioning
• Request/response patterns

publicapis_bestpractices_examples_get

Retrieve example API request/response files for workloads.

Parameters:

Parameter	Type	Required	Description
workload	string	Yes	Workload type
example_type	string	No	Type of example

Example Types:

• create - Creation requests
• update - Update operations
• get - Retrieval operations
• list - Listing operations
• delete - Deletion operations

publicapis_bestpractices_itemdefinition_get

Access JSON schema definitions for items within workload APIs.

Parameters:

Parameter	Type	Required	Description
workload	string	Yes	Workload type
item_type	string	Yes	Specific item type

Common Item Types:

• Lakehouse: lakehouse
• Pipeline: datapipeline, activity
• Semantic Model: semanticmodel, dataset
• Notebook: notebook
• Warehouse: warehouse
• KQL Database: kqldatabase

OneLake Management Tools

onelake download file

Download files from OneLake to local disk.

Parameters:

Parameter	Type	Required	Description
workspace	string	Yes	Workspace ID or name
item	string	Yes	Item ID or name.type format
path	string	Yes	File path in OneLake
local_path	string	Yes	Local destination path

Item Format: Can be:

• GUID: 550e8400-e29b-41d4-a716-446655440000
• Name.Type: MyLakehouse.Lakehouse

onelake upload file

Upload local files to OneLake storage.

Parameters:

Parameter	Type	Required	Description
workspace	string	Yes	Workspace ID or name
item	string	Yes	Item ID or name.type format
local_path	string	Yes	Local file path
onelake_path	string	Yes	Destination path in OneLake

onelake file list

List files in OneLake via hierarchical endpoint.

Parameters:

Parameter	Type	Required	Description
workspace	string	Yes	Workspace ID or name
item	string	Yes	Item ID or name.type format
path	string	No	Path to list (default: root)

onelake item create

Create new Fabric items (Lakehouses, notebooks, pipelines, etc.).

Parameters:

Parameter	Type	Required	Description
workspace	string	Yes	Workspace ID or name
item_type	string	Yes	Type of item to create
display_name	string	Yes	Item display name
description	string	No	Item description
definition	object	No	Item-specific configuration

Item Types:

• Lakehouse
• DataPipeline
• Notebook
• Warehouse
• KQLDatabase
• SemanticModel
• SparkJobDefinition

Development Workflows

Workflow 1: Discover and Use Fabric APIs

1. publicapis_list
   - See all available workloads

2. publicapis_get
   workload: "DataPipeline"
   - Get complete API specification

3. publicapis_bestpractices_itemdefinition_get
   workload: "DataPipeline"
   item_type: "datapipeline"
   - Get schema for pipeline definition

4. publicapis_bestpractices_examples_get
   workload: "DataPipeline"
   example_type: "create"
   - See example API calls

5. Implement based on specs and examples

Workflow 2: Create and Configure Lakehouse

1. onelake item create
   workspace: "MyWorkspace"
   item_type: "Lakehouse"
   display_name: "DataLakehouse"

2. onelake directory create
   item: "DataLakehouse.Lakehouse"
   path: "/Files/raw"

3. onelake directory create
   item: "DataLakehouse.Lakehouse"
   path: "/Files/processed"

4. onelake upload file
   item: "DataLakehouse.Lakehouse"
   local_path: "./data.csv"
   onelake_path: "/Files/raw/data.csv"

5. onelake file list
   item: "DataLakehouse.Lakehouse"
   - Verify upload

Workflow 3: Build Data Pipeline

1. publicapis_get
   workload: "DataPipeline"

2. publicapis_bestpractices_itemdefinition_get
   workload: "DataPipeline"
   item_type: "activity"

3. onelake item create
   item_type: "DataPipeline"
   display_name: "ETL Pipeline"
   definition: { /* pipeline config */ }

4. publicapis_bestpractices_get
   topic: "error_handling"

Best Practices

API Usage

1. Start with publicapis_list - Discover available workloads
2. Get full spec - Use publicapis_get for complete API documentation
3. Use schemas - Validate against item definitions
4. Follow examples - Start from provided examples
5. Handle errors - Implement retry logic from best practices

OneLake Management

1. Use friendly names - Prefer name.type format over GUIDs
2. Check before operations - List files/items first
3. Organize structure - Create logical directory hierarchies
4. Cleanup regularly - Delete unnecessary files
5. Verify uploads - List files after upload operations

Item Creation

1. Get schema first - Use itemdefinition_get before creating
2. Validate configuration - Check required properties
3. Start simple - Begin with minimal configuration
4. Test incrementally - Create, verify, then enhance
5. Use examples - Adapt from examples_get results

Fabric Workload Reference

Lakehouse

• Purpose: Delta Lake storage with SQL analytics
• Use publicapis_get: Lakehouse
• Item type: Lakehouse
• OneLake structure: /Files, /Tables

Data Pipeline

• Purpose: Data integration and ETL
• Use publicapis_get: DataPipeline
• Item type: DataPipeline
• Components: Activities, datasets, linked services

Semantic Model

• Purpose: Power BI datasets
• Use publicapis_get: SemanticModel
• Item type: SemanticModel
• Components: Tables, measures, relationships

Notebook

• Purpose: Interactive code notebooks
• Use publicapis_get: Notebook
• Item type: Notebook
• Languages: Python, Scala, R, SQL

Warehouse

• Purpose: SQL data warehouse
• Use publicapis_get: Warehouse
• Item type: Warehouse
• Features: T-SQL, tables, views, procedures

KQL Database

• Purpose: Real-time analytics with Kusto
• Use publicapis_get: KQLDatabase
• Item type: KQLDatabase
• Query language: KQL (Kusto Query Language)

When to Use This Skill

• Developing Microsoft Fabric integrations
• Building Fabric REST API clients
• Creating Lakehouses and data pipelines
• Managing OneLake storage programmatically
• Understanding Fabric item schemas
• Implementing Fabric best practices
• Automating Fabric workspace operations
• Learning Fabric API capabilities

Keywords

microsoft fabric, onelake, lakehouse, data pipeline, semantic model, notebook, warehouse, kql database, fabric api, openapi, rest api, item definition, schema, best practices, workspace management, file operations, fabric workload