Microsoft Fabric RTI Expert

Expert guidance for Microsoft Fabric Real-Time Intelligence using the Fabric RTI MCP Server. Work with Eventhouse databases, Eventstreams, Activators, and Maps through natural language.

Core Capabilities

1. Eventhouse/KQL (12 tools) - Query data, manage schemas, sample data
2. Eventstreams (17 tools) - Build real-time streaming pipelines
3. Activator (2 tools) - Create triggers and alerts
4. Map (7 tools) - Manage data visualizations

Quick Reference

Eventhouse Tools

• kusto_query - Execute KQL queries
• kusto_list_tables - List tables in database
• kusto_get_table_schema - Get table schema
• kusto_sample_table_data - Sample table records
• kusto_ingest_inline_into_table - Ingest CSV data

Eventstream Tools

• eventstream_list - List Eventstreams
• eventstream_create - Create new Eventstream
• eventstream_add_sample_data_source - Add sample data source
• eventstream_add_eventhouse_destination - Add Eventhouse destination
• eventstream_validate_definition - Validate configuration

Activator Tools

• activator_list_artifacts - List triggers
• activator_create_trigger - Create alert trigger

Map Tools

• map_list - List Maps
• map_create - Create new Map
• map_get_definition - Get Map configuration

Instructions

Querying Data with KQL

kusto_query Execute KQL queries against Eventhouse databases.

Parameters:

• database (string) - Target database name
• query (string) - KQL query text

Example:

StormEvents
| where State == "ILLINOIS" and EventType == "Flood"
| summarize Count=count() by StartTime
| order by StartTime desc

kusto_sample_table_data Get sample records from a table.

Parameters:

• table_name (string)
• sample_count (number, default: 10)

Managing Eventstreams

eventstream_create Create a new Eventstream for real-time data processing.

Parameters:

• workspace_id (string)
• display_name (string)
• description (string, optional)

eventstream_add_sample_data_source Add sample data source to Eventstream.

eventstream_add_eventhouse_destination Route data to Eventhouse for analytics.

Parameters:

• eventhouse_id (string)
• kql_database_id (string)
• table_name (string)
• input_serialization_type (string) - "Json", "Csv", etc.

Workflow:

1. eventstream_start_definition
2. eventstream_add_sample_data_source
3. eventstream_add_eventhouse_destination
4. eventstream_validate_definition
5. eventstream_create_from_definition

Creating Activator Triggers

activator_create_trigger Create triggers for real-time alerting.

Parameters:

• workspace_id (string)
• display_name (string)
• description (string)
• eventhouse_id (string)
• kql_database_id (string)
• query (string) - KQL query for monitoring
• notification_type (string) - "Email", "Teams"
• recipients (array) - Email addresses or Teams webhooks

Example: Monitor for floods and send email alert

Query: StormEvents | where EventType == "Flood" and State == "ILLINOIS"
Notification: Email to admin@company.com

Common Scenarios

Query Analysis

1. kusto_list_databases - Find databases
2. kusto_list_tables - Find tables
3. kusto_get_table_schema - Understand structure
4. kusto_query - Run analysis query

Real-Time Pipeline

1. eventstream_create - Create pipeline
2. eventstream_add_custom_endpoint_source - Add data source
3. eventstream_add_derived_stream - Transform data
4. eventstream_add_eventhouse_destination - Save to database
5. eventstream_validate_definition - Check config

Alerting Setup

1. kusto_query - Test alert condition
2. activator_create_trigger - Create alert
3. Monitor for notifications

When to Use This Skill

• Querying Fabric Eventhouse with KQL
• Building real-time data streaming pipelines
• Creating data-driven alerts and triggers
• Managing real-time analytics workloads
• Working with time-series and event data
• Implementing event-driven architectures

Keywords

microsoft fabric, real-time intelligence, rti, eventhouse, kql, kusto, eventstream, activator, map, real-time analytics, streaming data, event-driven, triggers, alerts, time-series data