Name: Fabric Real-Time Intelligence MCP Server
Rating: 4.0 (1 reviews)
Author: Microsoft

🎯 Overview

A comprehensive Model Context Protocol (MCP) server implementation for Microsoft Fabric Real-Time Intelligence (RTI).
This server enables AI agents to interact with Fabric RTI services by providing tools through the MCP interface, allowing for seamless data querying, analysis, and streaming capabilities.

[!NOTE]
This project is in Public Preview and implementation may significantly change prior to General Availability.

🔍 How It Works

The Fabric RTI MCP Server acts as a bridge between AI agents and Microsoft Fabric RTI services:

🔄 MCP Protocol: Uses the Model Context Protocol to expose Fabric RTI capabilities as tools
🏗️ Natural Language to KQL: AI agents can translate natural language requests into KQL queries and Eventstream management
💡 Secure Authentication: Leverages Azure Identity for seamless, secure access to your resources
⚡ Real-time Data Access: Direct connection to Eventhouse and Eventstreams for live data analysis
📊 Unified Interface: For both analytics and streaming workloads with intelligent parameter suggestions

✨ Supported Services

Eventhouse (Kusto): Execute KQL queries against Microsoft Fabric RTI Eventhouse and Azure Data Explorer (ADX).

Eventstreams: Manage Microsoft Fabric Eventstreams for real-time data processing:

List Eventstreams in workspaces
Get Eventstream details and definitions
Create new Eventstreams
Update existing Eventstreams
Delete Eventstreams

Activator: Create and manage Microsoft Fabric Activator triggers for real-time alerting:

Create new triggers with KQL source monitoring
Set up email and Teams notifications when a condition occurs
List Activator artifacts in workspaces

Map: Create and manage Microsoft Fabric Map to visualize geospatial data:

Create a new map from a provided configuration
Visualize data on maps
List Map items in workspaces
Delete Map items

🚧 Coming soon

Other RTI items

🔍 Example Prompts

Eventhouse Analytics:

"Get databases in my Eventhouse"
"Sample 10 rows from table 'StormEvents' in Eventhouse"
"What can you tell me about StormEvents data?"
"Analyze the StormEvents to come up with trend analysis across past 10 years of data"
"Analyze the commands in 'CommandExecution' table and categorize them as low/medium/high risks"

Eventstream Management:

"List all Eventstreams in my workspace"
"Show me the details of my IoT data Eventstream"
"Create a new Eventstream for processing sensor data"
"Update my existing Eventstream to add a new destination"

Activator Alerts:

"Using the StormEvents table, notify me via email when there is a flood in Illinois"
"Create a teams alert to notify me when my success rate drops below 95%"
"List all Activator artifacts in my workspace"

Map Visualization::

"List all Map items in my workspace"
"Create a new Map and add LakeHouse with name 'MyLakeHouse' as a data source to Map item 'MyMap'"
"Delete a Map item with name 'MyMap' from my workspace"

Available tools

Eventhouse (Kusto) - 12 Tools:

kusto_known_services - List all available Kusto services configured in the MCP
kusto_query - Execute KQL queries on the specified database
kusto_command - Execute Kusto management commands (destructive operations)
kusto_list_databases - List all databases in the Kusto cluster
kusto_list_tables - List all tables in a specified database
kusto_get_entities_schema - Get schema information for all entities (tables, external tables, materialized views, functions) in a database
kusto_get_table_schema - Get detailed schema information for a specific table
kusto_get_function_schema - Get schema information for a specific function, including parameters and output schema
kusto_sample_table_data - Retrieve random sample records from a specified table
kusto_sample_function_data - Retrieve random sample records from the result of a function call
kusto_ingest_inline_into_table - Ingest inline CSV data into a specified table
kusto_get_shots - Retrieve semantically similar query examples from a shots table using AI embeddings

Eventstreams - 17 Tools:

Core Operations (6 tools):

eventstream_list - List all Eventstreams in your Fabric workspace
eventstream_get - Get detailed information about a specific Eventstream
eventstream_get_definition - Retrieve complete JSON definition of an Eventstream
eventstream_create - Create new Eventstreams with custom configuration (auto-includes default stream)
eventstream_update - Modify existing Eventstream settings and destinations
eventstream_delete - Remove Eventstreams and associated resources

Builder Tools (11 tools):

Session Management: eventstream_start_definition, eventstream_get_current_definition, eventstream_clear_definition
Sources: eventstream_add_sample_data_source, eventstream_add_custom_endpoint_source
Streams: eventstream_add_derived_stream
Destinations: eventstream_add_eventhouse_destination, eventstream_add_custom_endpoint_destination
Validation: eventstream_validate_definition, eventstream_create_from_definition, eventstream_list_available_components

💡 Pro Tip: All tools work with natural language! Just describe what you want to do and the AI agent will use the appropriate tools automatically.

Activator - 2 Tools:

activator_list_artifacts - List all Activator artifacts in a Fabric workspace
activator_create_trigger - Create new Activator triggers with KQL source monitoring and email/Teams alerts

Map - 7 Tools:

map_list - List all Map items in your Fabric workspace
map_get - Get detailed information about a specific Map item
map_get_definition - Retrieve the full JSON definition of a Map item
map_create - Create a new Map item from a provided configuration
map_update_definition - Replace the full JSON definition of an existing Map item
map_update - Partially update properties of an existing Map item
map_delete - Delete a Map item and its associated configuration

Getting Started

Prerequisites

Install either the stable or Insiders release of VS Code:
- 💫 Stable release
- 🔮 Insiders release
Install the GitHub Copilot and GitHub Copilot Chat extensions
Install uv

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

or, check here for other install options

Open VS Code in an empty folder

Install from PyPI (Pip)

The Fabric RTI MCP Server is available on PyPI, so you can install it using pip. This is the easiest way to install the server.

From VS Code

1. Open the command palette (Ctrl+Shift+P) and run the command `MCP: Add Server`
2. Select install from Pip
3. When prompted, enter the package name `microsoft-fabric-rti-mcp`
4. Follow the prompts to install the package and add it to your settings.json or your mcp.json file

The process should end with the below settings in your settings.json or your mcp.json file.

settings.json

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

Note: All environment variables are optional. The KUSTO_SERVICE_URI and KUSTO_SERVICE_DEFAULT_DB provide default cluster and database settings. The AZ_OPENAI_EMBEDDING_ENDPOINT is only needed for semantic search functionality in the kusto_get_shots tool.

From GitHub Copilot CLI

Use the interactive command within a GitHub Copilot CLI session:

/mcp add

Or manually add to your ~/.copilot/mcp-config.json:

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

For more information, see the GitHub Copilot CLI documentation.

🔧 Manual Install (Install from source)

Make sure you have Python 3.10+ installed properly and added to your PATH.
Clone the repository
Install the dependencies (pip install . or uv tool install .)
Add the settings below into your vscode settings.json or your mcp.json file.
Modify the path to match the repo location on your machine.
Modify the cluster uri in the settings to match your cluster.
Modify the cluster default database in the settings to match your database.
Modify the embeddings endpoint in the settings to match yours. This step is optional and needed only in case you supply a shots table

{
    "mcp": {
        "servers": {
            "fabric-rti-mcp": {
                "command": "uv",
                "args": [
                    "--directory",
                    "C:/path/to/fabric-rti-mcp/",
                    "run",
                    "-m",
                    "fabric_rti_mcp.server"
                ],
                "env": {
                    "KUSTO_SERVICE_URI": "https://help.kusto.windows.net/",
                    "KUSTO_SERVICE_DEFAULT_DB": "Samples",
                    "FABRIC_API_BASE_URL": "https://api.fabric.microsoft.com/v1"
                }
            }
        }
    }
}

🐛 Debugging the MCP Server locally

Assuming you have python installed and the repo cloned:

Install locally

pip install -e ".[dev]"

Configure

Follow the Manual Install instructions.

Attach the debugger

Use the Python: Attach configuration in your launch.json to attach to the running server.
Once VS Code picks up the server and starts it, navigate to its output:

Open command palette (Ctrl+Shift+P) and run the command MCP: List Servers
Navigate to fabric-rti-mcp and select Show Output
Pick up the process ID (PID) of the server from the output
Run the Python: Attach configuration in your launch.json file, and paste the PID of the server in the prompt
The debugger will attach to the server process, and you can start debugging

🧪 Test the MCP Server

Via GitHub Copilot

Open GitHub Copilot in VS Code and switch to Agent mode
You should see the Fabric RTI MCP Server in the list of tools
Try prompts that tell the agent to use the RTI tools, such as:
- Eventhouse: "List my Kusto tables" or "Show me a sample from the StormEvents table"
- Eventstreams: "List all Eventstreams in my workspace" or "Show me details of my data processing Eventstream"
The agent should be able use the Fabric RTI MCP Server tools to complete your query

Via VS Code Client Tool

For direct testing and development, use the included VS Code client:

# Interactive mode with menu
python eventstream_test/vscode_mcp_client.py

# Natural language commands
python eventstream_test/vscode_mcp_client.py "list eventstreams in workspace abc-123 with interactive auth"
python eventstream_test/vscode_mcp_client.py "query cluster https://example.kusto.windows.net: MyTable | take 10"
python eventstream_test/vscode_mcp_client.py "get fabric api base url"

The VS Code client includes:

🔐 Interactive authentication - Browser-based Microsoft sign-in
🗣️ Natural language prompts - English commands for MCP operations
⚙️ API configuration - Runtime control of Fabric API endpoints
📊 JSON output - Formatted results for analysis

Fabric Real-Time Intelligence MCP Server