// SCAN REPORT

Fabric-Analytics-MCP

83 tools. 33 can modify or destroy data without limits.

4 destructive tools with no built-in limits. Policy required.

Last updated:

33 can modify or destroy data
50 read-only
83 tools total

Community server · catalogue entry verified 11/06/2026

How to control Fabric-Analytics-MCP ↓

TOOL MAP

Read (50) Write / Execute (29) Destructive / Financial (4)

MOST DANGEROUS TOOLS

Critical Risk
Destructive · High delete-fabric-dataflow This tool performs an irreversible deletion of a Fabric dataflow artifact. Destructive · High delete-fabric-item This tool permanently removes items from a Microsoft Fabric workspace with no apparent undo mechanism. Destructive · High delete-fabric-notebook The tool performs an irreversible deletion operation on a Fabric workspace artifact (notebook). Destructive · High delete-livy-session Deleting a Livy session terminates an active Apache Spark session, which irreversibly destroys the session state, running computations, and any intermediate results not persisted.

33 of Fabric-Analytics-MCP's 83 tools can modify, destroy, or commit something on every call — and an agent calls them with no built-in limits.

HOW TO CONTROL FABRIC-ANALYTICS-MCP

PolicyLayer is an MCP gateway — it sits between your AI agents and Fabric-Analytics-MCP, and nothing reaches the server without passing your rules. These are the rules we recommend:

Deny destructive operations
{
  "delete-fabric-dataflow": {
    "deny_if": [
      {
        "conditions": [],
        "on_deny": "Blocked by default. Requires approval."
      }
    ]
  }
}

Destructive tools should never be available to autonomous agents without human approval.

Rate limit write operations
{
  "fabric_provision_notebooks": {
    "limits": [
      {
        "counter": "fabric_provision_notebooks_per_hour",
        "window": "hour",
        "max": 30,
        "scope": "grant"
      }
    ]
  }
}

Prevents bulk unintended modifications from agents caught in loops.

Cap read operations
{
  "analyze-fabric-model": {
    "limits": [
      {
        "counter": "analyze-fabric-model_per_minute",
        "window": "minute",
        "max": 60,
        "scope": "grant"
      }
    ]
  }
}

Controls API costs and prevents retry loops from exhausting upstream rate limits.

  1. Create a free account and register Fabric-Analytics-MCP — nothing to install.
  2. Add these rules — paste them, or build them visually. Tune the limits to your setup.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
ENFORCE POLICY ON FABRIC-ANALYTICS-MCP →

Free to start. No card required.

ALL 83 FABRIC-ANALYTICS-MCP TOOLS

DESTRUCTIVE 4 tools
Destructive delete-fabric-dataflow Delete a Dataflow Gen2 from workspace Destructive delete-fabric-item Delete an item from Microsoft Fabric workspace Destructive delete-fabric-notebook Delete a notebook from Microsoft Fabric workspace Destructive delete-livy-session Delete a Livy session
EXECUTE 15 tools
Execute cancel-spark-application Cancel a running Spark application Execute execute-fabric-notebook Execute a notebook in Microsoft Fabric workspace Execute execute-livy-statement Execute a statement in a Livy session Execute execute-spark-job-definition Execute a Spark Job Definition with execution data Execute fabric_transform_notebooks fabric_transform_notebooks Execute run-fabric-notebook Execute/run a notebook in Microsoft Fabric workspace Execute start-continuous-dataflow-monitoring Start continuous monitoring session with real-time health checks and alerts Execute stop-monitoring-session Stop a specific monitoring session Execute query-fabric-dataset Execute a query against a Microsoft Fabric dataset Execute create-livy-batch Create a Livy batch job Execute create-livy-session Create a new Livy session for interactive Spark execution Execute create-spark-job-instance Create a Spark job instance from a Spark Job Definition Execute fabric_migrate_spark_pools_to_fabric fabric_migrate_spark_pools_to_fabric Execute fabric_migrate_synapse_to_fabric fabric_migrate_synapse_to_fabric Execute submit-spark-job Submit a Spark job to run on a Lakehouse
WRITE 14 tools
Write fabric_provision_notebooks fabric_provision_notebooks Write fabric_unassign_workspace_from_capacity Unassign a workspace from its capacity (move to shared capacity) Write create-fabric-dataflow Create a new Dataflow Gen2 in Microsoft Fabric workspace Write create-fabric-item Create a new item in Microsoft Fabric workspace Write create-fabric-notebook Create a new notebook in Microsoft Fabric workspace using the official API Write fabric_assign_capacity fabric_assign_capacity Write fabric_assign_workspace_to_capacity Assign a workspace to a dedicated Fabric capacity Write fabric_create_fabric_spark_pools fabric_create_fabric_spark_pools Write fabric_create_lakehouse fabric_create_lakehouse Write fabric_create_workspace Create a new workspace Write generate-fabric-report Generate a comprehensive analytics report for Microsoft Fabric workspace Write update-fabric-dataflow Update Dataflow Gen2 name or description Write update-fabric-item Update an existing item in Microsoft Fabric workspace Write update-fabric-notebook Update an existing notebook in Microsoft Fabric workspace
READ 50 tools
Read analyze-fabric-model Analyze a Microsoft Fabric data model and get optimization recommendations Read analyze-fabric-run-performance Perform detailed performance analysis on a specific run Read analyze-livy-execution-history Analyze historical Livy execution patterns with trend analysis and performance insights Read analyze-livy-session-logs Analyze Livy session logs with LLM-powered performance insights and recommendations Read analyze-livy-statement-performance Analyze Livy statement execution with detailed performance metrics and LLM-powered optimization recommendation Read check-fabric-auth-status Check current authentication status and configuration Read fabric_discover_synapse_workspace fabric_discover_synapse_workspace Read fabric_find_workspace Find workspace by name and get its ID for use in other operations Read fabric_get_synapse_spark_pools fabric_get_synapse_spark_pools Read fabric_list_capacities List all available Fabric capacities Read fabric_list_capacity_workspaces List all workspaces assigned to a specific capacity Read fabric_list_synapse_workspaces fabric_list_synapse_workspaces Read fabric_list_workspaces List all workspaces accessible to the user Read fabric_recommend_fabric_capacity fabric_recommend_fabric_capacity Read fabric_synapse_compute_spend fabric_synapse_compute_spend Read fabric_synapse_workspace_details fabric_synapse_workspace_details Read get-fabric-dataflow Get details of a specific Dataflow Gen2 Read get-fabric-item Get detailed information about a specific Microsoft Fabric item Read get-fabric-item-run Get detailed information about a specific Fabric item run Read get-fabric-metrics Retrieve analytics metrics for Microsoft Fabric items Read get-fabric-notebook Get details of a specific notebook in Microsoft Fabric workspace Read get-fabric-notebook-definition Get the definition/content of a notebook in Microsoft Fabric workspace Read get-job-status Get the status of a running job Read get-lakehouse-spark-applications Get all Spark applications/sessions for a specific lakehouse Read get-livy-batch Get the status of a Livy batch job Read get-livy-session Get the status of a Livy session Read get-livy-statement Get the result of a statement execution Read get-livy-statement-enhanced Get Livy statement status with enhanced performance analysis and recommendations Read get-monitoring-session-status Get detailed status of a specific monitoring session Read get-notebook-spark-application-details Get detailed information about a specific Spark application from a notebook session Read get-notebook-spark-application-jobs Get jobs for a specific Spark application from a notebook session Read get-notebook-spark-applications Get all Spark applications/sessions for a specific notebook Read get-spark-application-details Get detailed information about a specific Spark application Read get-spark-job-definition-applications Get all Spark applications/sessions for a specific Spark job definition Read get-spark-job-instance-status Get the status of a Spark job instance Read get-spark-monitoring-dashboard Get comprehensive Spark monitoring dashboard for workspace Read get-workspace-spark-applications Get all Spark applications in a workspace for monitoring Read list-fabric-dataflows List all Dataflow Gen2 in Microsoft Fabric workspace Read list-fabric-item-runs List all runs for a specific Fabric item with analysis Read list-fabric-items List items in a Microsoft Fabric workspace Read list-fabric-notebooks List all notebooks in a Microsoft Fabric workspace Read list-fabric-run-subactivities List subactivities for a specific Fabric item run with analysis Read list-livy-sessions List all Livy sessions for a lakehouse Read list-monitoring-sessions List all active monitoring sessions Read monitor-dataflow-status Get comprehensive dataflow status with health monitoring and performance metrics Read monitor-fabric-runs-dashboard Get comprehensive monitoring dashboard for recent runs across workspace Read monitor-workspace-dataflows Get monitoring overview of all dataflows in workspace with health scoring Read perform-dataflow-health-check Perform comprehensive health check with scoring, analysis, and recommendations Read test-function Test function to verify registration Read generate-dataflow-monitoring-report Generate comprehensive monitoring report with insights and recommendations

RELATED SERVERS

Other MCP servers with similar tools — same risk classification, starter policies for each.

BNB Chain MCP 1240 tools
adminautomation
Binance MCP Server 734 tools
adminautomation
Nodebench 724 tools
adminautomation
GoHighLevel MCP Server 566 tools
adminautomation
UnClick 451 tools
adminautomation
NowAIKit — ServiceNow AI Toolkit 446 tools
adminautomation
Mcp Windows 441 tools
adminautomation
0nmcp 407 tools
adminautomation

FAQ

Can an AI agent delete data through the Fabric-Analytics- MCP server? +

Yes. The Fabric-Analytics-MCP server exposes 4 destructive tools including delete-fabric-dataflow, delete-fabric-item, delete-fabric-notebook. These permanently remove resources with no undo. PolicyLayer blocks destructive tools by default so they never reach the upstream server.

How do I prevent bulk modifications through Fabric-Analytics-MCP? +

The Fabric-Analytics-MCP server has 14 write tools including fabric_provision_notebooks, fabric_unassign_workspace_from_capacity, create-fabric-dataflow. Set a rate limit in your policy -- for example, 10 calls per hour prevents an agent from making more than 10 modifications per hour. PolicyLayer enforces this at the gateway, before calls reach Fabric-Analytics-MCP.

How many tools does the Fabric-Analytics- MCP server expose? +

83 tools across 4 categories: Destructive, Execute, Read, Write. 50 are read-only. 33 can modify, create, or delete data.

How do I enforce a policy on Fabric-Analytics-MCP? +

Register the Fabric-Analytics- MCP server in PolicyLayer, apply the suggested rules above (adjust the limits to your use case), and point your AI client at the PolicyLayer proxy URL instead of the server directly. Your agents keep the same tools; PolicyLayer evaluates every call against policy before it executes. Nothing to install, live in minutes.

Enforce policy on every Fabric-Analytics-MCP tool call.

Deterministic rules across all 83 Fabric-Analytics-MCP tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

ENFORCE POLICY ON FABRIC-ANALYTICS-MCP →

Free to start. No card required.

83 Fabric-Analytics-MCP tools catalogued and risk-classified — across an index of 42,500+ MCP servers.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.