microsoft/fabric-rti-mcp

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
🧠 Copilot Skills
This repository includes a **KQL Copilot Skill** (.github/skills/kql/) that gives AI agents deep KQL expertise when writing, debugging, or reviewing Kusto queries. The skill covers:
- Syntax gotchas and self-correction patterns for common KQL errors
- Dynamic type discipline, join patterns, datetime pitfalls
- Memory-safe query patterns and result-size discipline
- Advanced functions: graph queries, vector similarity, geospatial operations, time series
- Query templates for deduplication, top-N, sessionization, pivoting, and more
- Full error-to-fix mapping for rapid recovery
The skill references the Fabric RTI MCP tools (kusto_query, kusto_command, kusto_sample_entity, etc.) so agents know how to execute queries through this MCP server.
🚧 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"
- "Before running this query, check the execution plan and tell me if it's expensive"
- "Compare these two query approaches and tell me which is more efficient"
- "Check the cluster health — do we have enough capacity for a heavy analytics job?"
**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) - 13 Tools + 1 Optional:
- **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 (.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