fabric-mcp

name	fabric-mcp
description	Microsoft Fabric MCP Server setup and usage — provides AI agents with access to Fabric public APIs, item definitions, OneLake data operations, and best-practice guidance. Use when configuring the Fabric MCP Server for Claude Code or other AI clients.
allowed-tools	Bash(npx *), Bash(dotnet *), Bash(cat *), Bash(grep *), Read, Write, Edit, Glob
user-invocable	false
metadata	{"author":"accelerate-data"}

Fabric MCP Server

The Fabric MCP Server is a local-first Model Context Protocol server that provides AI agents with access to Microsoft Fabric's public APIs, item definitions, and best practices. It runs locally on your machine.

What It Provides

API Documentation & Best Practices Tools

Tool	Purpose
docs_workloads	Lists available Fabric workload types with public API specs
docs_workload-api-spec	Retrieves OpenAPI specs for specific workloads
docs_platform-api-spec	Returns core Fabric platform API specifications
docs_item-definitions	JSON schema definitions for Fabric items (Lakehouse, Notebook, Pipeline, etc.)
docs_best-practices	Best practice documentation — pagination, error handling, throttling
docs_api-examples	Example API request/response files

OneLake Data Operations Tools

Tool	Purpose
onelake_list_workspaces	Lists available workspaces
onelake_list_items	Lists workspace items with metadata
onelake_list_files	Hierarchical file listing within items
onelake_download_file	Download files from OneLake
onelake_upload_file	Upload files to OneLake
onelake_delete_file	Delete OneLake files
onelake_create_directory	Create directories via DFS endpoint
onelake_delete_directory	Delete directories (optionally recursive)
onelake_get_table_config	Table API configuration for items
onelake_list_table_namespaces	List table schemas/namespaces
onelake_get_table_namespace	Retrieve namespace metadata
onelake_list_tables	List tables within a namespace
onelake_get_table	Get specific table definitions

Core Operations Tools

Tool	Purpose
core_create-item	Create new Fabric items (Lakehouses, Notebooks, etc.)

Installation

Option 1: Node.js / npx (Recommended)

Requirements: Node.js 20 LTS or later.

No install needed — npx downloads and runs it on demand.

Option 2: .NET Build from Source

Requirements: .NET 9 SDK or later.

git clone https://github.com/microsoft/mcp.git
cd mcp
dotnet build servers/Fabric.Mcp.Server/src/Fabric.Mcp.Server.csproj --configuration Release

Configuration

Claude Code — Project Config (.mcp.json)

{
  "mcpServers": {
    "fabric-mcp-server": {
      "command": "npx",
      "args": ["-y", "@microsoft/fabric-mcp@latest", "server", "start", "--mode", "all"],
      "type": "stdio"
    }
  }
}

Claude Code — User Config (~/.claude.json)

Same JSON structure, placed in the user-level config file.

Claude Desktop

macOS: ~/.claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "fabric-mcp-server": {
      "command": "npx",
      "args": ["-y", "@microsoft/fabric-mcp@latest", "server", "start", "--mode", "all"],
      "type": "stdio"
    }
  }
}

Cursor

~/.cursor/mcp.json or .cursor/mcp.json (project-level):

{
  "mcpServers": {
    "fabric-mcp-server": {
      "command": "npx",
      "args": ["-y", "@microsoft/fabric-mcp@latest", "server", "start", "--mode", "all"]
    }
  }
}

VS Code

.vscode/mcp.json (workspace) or user settings.json:

Install the Fabric MCP Server extension from the VS Code Marketplace for automatic setup.

.NET Build Config (if built from source)

{
  "mcpServers": {
    "Fabric MCP Server": {
      "command": "/path/to/repo/servers/Fabric.Mcp.Server/src/bin/Release/fabmcp",
      "args": ["server", "start"],
      "type": "stdio"
    }
  }
}

Platform notes:

• macOS/Linux: Use path as-is
• Windows: Use backslashes and .exe extension

Server Modes

The --mode flag controls which tools are available:

Mode	Tools Available
all	All tools (docs + OneLake + core)
docs	Documentation tools only (no data access)
onelake	OneLake data operations only

Example Prompts

After setup, use these prompts with your AI client:

Workload & API questions:

• "What Fabric workload types are available?"
• "Show me OpenAPI operations for 'notebook' with sample creation body"

Schema & definitions:

• "Create a Lakehouse resource definition with string and datetime columns"
• "Show JSON schema for a Data Pipeline item definition"

Best practices:

• "Show best practices for handling API throttling in Fabric"
• "What pagination patterns exist for Fabric REST APIs?"

Development:

• "Help me scaffold a Fabric workspace with Lakehouse and notebooks"
• "Generate a data pipeline configuration with sample data sources"

Community: ms-fabric-mcp-server (Live CRUD Operations)

A community-maintained MCP server that exposes actual Fabric CRUD operations against live environments. 60 tools covering workspaces, items, notebooks, pipelines, lakehouses, Livy Spark, semantic models, and SQL.

Repository: github.com/bablulawrence/ms-fabric-mcp-server PyPI: ms-fabric-mcp-server

Setup

{
  "mcpServers": {
    "fabric-ops": {
      "command": "uvx",
      "args": ["ms-fabric-mcp-server"],
      "env": {
        "FABRIC_BASE_URL": "https://api.fabric.microsoft.com/v1",
        "MCP_LOG_LEVEL": "INFO"
      }
    }
  }
}

Authentication: Uses DefaultAzureCredential — works with az login, environment variables (AZURE_CLIENT_ID, AZURE_TENANT_ID, AZURE_CLIENT_SECRET), VS Code credentials, or Managed Identity.

Key Tool Categories (60 tools)

Category	Count	Examples
Workspace	1	list_workspaces
Item	9	list_items, get_item, create_folder, delete_item, rename_item
Lakehouse	4	create_lakehouse, list_lakehouse_files, upload_lakehouse_file, delete_lakehouse_file
Notebook	6	create_notebook, get_notebook_definition, update_notebook_definition, get_notebook_run_details
Job	4	run_on_demand_job, get_job_status
Livy Spark	8	livy_create_session, livy_run_statement, livy_get_session_status
Pipeline	11	create_pipeline, add_copy_activity_to_pipeline, add_notebook_activity_to_pipeline
Dataflow	3	create_dataflow, get_dataflow_definition, run_dataflow
Semantic Model	9	create_semantic_model, add_table_to_semantic_model, execute_dax_query
SQL (optional)	3	get_sql_endpoint, execute_sql_query, execute_sql_statement

Environment Variables

Variable	Default	Purpose
FABRIC_BASE_URL	https://api.fabric.microsoft.com/v1	Fabric API base URL
FABRIC_API_CALL_TIMEOUT	30	API timeout (seconds)
FABRIC_MAX_RETRIES	3	Max retry attempts
LIVY_API_CALL_TIMEOUT	120	Livy timeout (seconds)
LIVY_SESSION_WAIT_TIMEOUT	240	Livy session wait (seconds)

Warning: This server includes destructive operations (delete items, etc.) — use in development environments only.

Fabric RTI MCP Server (Real-Time Intelligence)

Official Microsoft MCP server for Real-Time Intelligence / Eventhouse / Azure Data Explorer. 38 tools.

Repository: github.com/microsoft/fabric-rti-mcp PyPI: microsoft-fabric-rti-mcp

Setup

{
  "mcpServers": {
    "fabric-rti-mcp": {
      "command": "uvx",
      "args": ["microsoft-fabric-rti-mcp"],
      "env": {
        "KUSTO_SERVICE_URI": "https://your-cluster.kusto.windows.net/",
        "KUSTO_SERVICE_DEFAULT_DB": "YourDatabase",
        "FABRIC_API_BASE_URL": "https://api.fabric.microsoft.com/v1"
      }
    }
  }
}

Capabilities

• KQL query execution against Eventhouse/ADX
• Natural language to KQL (NL2KQL) translation
• Schema discovery for KQL databases
• Eventstream management (17 tools)
• Activator alerts (2 tools)
• Map visualization (7 tools)

Recommended Combined Config

For full Fabric coverage in Claude Code .mcp.json:

{
  "mcpServers": {
    "fabric-mcp-server": {
      "command": "npx",
      "args": ["-y", "@microsoft/fabric-mcp@latest", "server", "start", "--mode", "all"]
    },
    "fabric-ops": {
      "command": "uvx",
      "args": ["ms-fabric-mcp-server"]
    }
  }
}

Prerequisites: Node.js 20+ (official server), Python 3.10+ with uv/uvx (community server), Azure auth (az login).

Relationship to fabric-cli

The fab CLI (ms-fabric-cli on PyPI) is a separate tool — a file-system-inspired command-line interface. It does not have MCP support. The MCP servers are independent projects for AI agent integration, while fab is for interactive/scripted terminal use.

Security Notes

• The official Fabric MCP Server runs locally — documentation tools do not connect to live Fabric
• OneLake tools (official) and the community server do connect to your Fabric tenant
• Microsoft telemetry can be disabled per the repo documentation

Resources

• Fabric MCP Server README
• Fabric MCP Blog Post
• ms-fabric-mcp-server (community)
• Fabric RTI MCP Repo
• Microsoft MCP Catalog
• NuGet Package