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Fabric RTI MCP

Official

KQL queries, Eventstream management, and real-time alerts for Microsoft Fabric Real-Time Intelligence

GitHub source repository ↗

★ 129 Stars Category · Other Very popular Source revision df5e9cd9d612

65FMRS · C

Reliability

10/20

Security and permissions

13/20

Maintenance

15/20

Documentation

15/20

Setup experience

12/20

This is an official Microsoft MCP server that connects AI agents to Fabric RTI, offering a wide set of tools including KQL queries, event stream management, and map operations. It provides a natural language interface and is well-documented. However, it is in preview and requires careful permission management to use securely.

Read the FMRS scoring method →

The Fabric RTI MCP server is a comprehensive Model Context Protocol (MCP) server implementation for Microsoft Fabric Real-Time Intelligence (RTI). It enables AI agents to interact with Fabric RTI services by providing tools that allow for KQL queries against Eventhouse and Azure Data Explorer, management of Eventstreams, creation of Activator triggers, and visualization/manipulation of Map items. The server supports natural language to KQL conversion, secure authentication via Azure Identity, and real-time data access. It is currently in Public Preview.

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 (e.g., .show, .create, .alter, .drop).

kusto_list_entities

List entities (databases, tables, external tables, materialized views, functions, graphs) in a cluster or database.

kusto_describe_database

Get schema information for all entities in a database.

kusto_describe_database_entity

Get detailed schema for a specific entity (table, external table, materialized view, function, or graph).

kusto_graph_query

Execute graph queries using snapshots or transient graphs.

kusto_sample_entity

Retrieve sample records from a table, external table, materialized view, or function.

kusto_ingest_inline_into_table

Ingest inline CSV data into a specified table.

kusto_get_shots

Find semantically similar saved KQL queries using local SLM or Azure OpenAI embeddings.

kusto_deeplink_from_query

Generate a deeplink URL to open a KQL query in Azure Data Explorer Web Explorer or Microsoft Fabric query workbench.

kusto_show_queryplan

Retrieve the execution plan for a KQL query without running it. Returns planning stats, logical operator tree, and execution hints.

kusto_diagnostics

Run a best-effort suite of cluster diagnostic commands and return a unified summary.

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.

eventstream_update

Modify existing Eventstream settings and destinations.

eventstream_delete

Remove Eventstreams and associated resources.

eventstream_start_definition

Start a definition-building session for an Eventstream.

eventstream_get_current_definition

Get the current in-progress Eventstream definition.

eventstream_clear_definition

Clear the current Eventstream definition being built.

eventstream_add_sample_data_source

Add a sample data source to the Eventstream definition.

eventstream_add_custom_endpoint_source

Add a custom endpoint source to the Eventstream definition.

eventstream_add_derived_stream

Add a derived stream to the Eventstream definition.

eventstream_add_eventhouse_destination

Add an Eventhouse destination to the Eventstream definition.

eventstream_add_custom_endpoint_destination

Add a custom endpoint destination to the Eventstream definition.

eventstream_validate_definition

Validate an Eventstream definition.

eventstream_create_from_definition

Create an Eventstream from a definition.

eventstream_list_available_components

List components that can be used in an Eventstream.

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_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.

Setup

Install from PyPI:

Ensure UV and VS Code are installed.
Open VS Code and open the command palette (Ctrl+Shift+P).
Run MCP: Add Server, select "Install from Pip".
Enter the package name microsoft-fabric-rti-mcp and follow the prompts.
Add configuration to settings.json or mcp.json, e.g., using uvx command.

Alternatively, if GitHub Copilot CLI is enabled, run /mcp add in a session and select the package.

claude_desktop_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": "https://api.fabric.microsoft.com/v1"
      }
    }
  }
}

Generate and validate client config

Fit and risk

Best for

Teams using Microsoft Fabric RTI who want to interact with data via AI agents using natural language.
Data engineers needing to quickly analyze streaming data and generate KQL queries automatically.
Developers looking to automate real-time data monitoring and alerts, such as Activator triggers and Eventstream management.
Analysts needing to visualize geospatial data and interact with Map items.

Not for

Production deployments seeking a stable, GA MCP server (currently in Public Preview).
Users unfamiliar with Fabric RTI or KQL, as the server relies on existing knowledge to use effectively.
Organizations that do not wish to expose their data or workspaces to LLMs or third-party clients.
Use cases requiring advanced security for HTTP mode without additional configuration.

Required permissions

Access Microsoft Fabric workspaces, including Eventhouse, Eventstreams, Activator, and Map items.
Execute KQL queries and management commands, including ingesting data and modifying schemas.
Create, update, and delete Eventstreams and Map items.
Create Activator triggers and configure email or Teams notifications.
Authenticate using Azure Identity, which automatically uses environment credentials, Azure CLI, PowerShell, etc.

Risks and side effects

Public Preview: implementation may change significantly prior to General Availability.
MCP clients can perform destructive operations (e.g., deleting Eventstreams or Maps) if permissions are too broad.
Sharing data with third-party LLMs or clients may fall outside Fabric's compliance boundary; review carefully.
HTTP mode may expose endpoints beyond localhost; ensure a security boundary (e.g., Entra authentication) is placed in front.
Some tools, like kusto_get_shots, require additional configuration (e.g., embedding endpoints and table).

Troubleshooting

Check authentication: ensure you are logged in via Azure CLI, Visual Studio, Azure PowerShell, or browser, and have appropriate permissions.
Check environment variables: verify KUSTO_SERVICE_URI and KUSTO_SERVICE_DEFAULT_DB are set correctly.
Check permissions: assign the user the required Fabric RBAC roles to perform queries, creates, or deletes.
Check network: ensure the client can reach Fabric and Azure Data Explorer endpoints.
For remote deployments, verify HTTP mode configuration (e.g., FABRIC_RTI_HTTP_PORT) and authentication tokens.

Use cases

Query Eventhouse using natural language and analyze trends.

Manage Eventstreams: list, create, update, or delete real-time data streams.

Create Activator triggers to get email or Teams alerts when conditions are met or anomalies occur.

Create and manage Map items from JSON configurations to visualize geospatial data.

Supported clients

VS CodeFull support

GitHub CopilotFull support

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