semantic_model_optimization_recommendations

THE RISK

High Risk

Why semantic_model_optimization_recommendations needs a policy

The tool actively connects to a live Fabric Semantic Model and executes DAX queries against it. This constitutes running external operations (query execution) against a live system, placing it in the Execute category.

From the tool's definition LIVE SCAN: Connects to a Fabric Semantic Model and executes DAX queries (COLUMNSTATISTICS)

Documented attack patterns abuse exactly the kind of access semantic_model_optimization_recommendations gives an agent:

POLICY

How to control semantic_model_optimization_recommendations

PolicyLayer is an MCP gateway — it sits between your AI agents and Force Fabric MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for semantic_model_optimization_recommendations:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "semantic_model_optimization_recommendations": {
      "limits": [
        {
          "counter": "semantic_model_optimization_recommendations_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

semantic_model_optimization_recommendations stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

Create a free account and register Force Fabric MCP Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

RATE-LIMIT THIS TOOL →

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EXPLORE

Related tools and policies

More Force Fabric MCP Server tools

Destructive auth_logout Logout from Microsoft Fabric and clear cached credentials. Execute lakehouse_run_table_maintenance Run table maintenance (OPTIMIZE with V-Order, Z-ORDER, VACUUM) on a Fabric Lakehouse. Execute eventhouse_auto_optimize AUTO-OPTIMIZE: Scans a Fabric Eventhouse for all fixable issues across all KQL databases a Execute eventhouse_fix AUTO-FIX: Applies fixes to a Fabric Eventhouse. Execute eventhouse_fix_materialized_views AUTO-FIX: Diagnoses and repairs broken materialized views in a Fabric Eventhouse. Execute gateway_fix AUTO-FIX: Applies fixes to gateway and connection issues. Execute lakehouse_auto_optimize AUTO-OPTIMIZE: Discovers ALL Delta tables in a Lakehouse and applies fixes to every table Execute lakehouse_fix AUTO-FIX: Applies Spark SQL fixes to a Lakehouse via Livy API (no notebooks needed).

All 33 Force Fabric MCP Server tools →

Execute tools on other servers

Android Forensics ADB MCP Server adb_shell_command EMBA-MCP run_emba_scan Frida Game Hacking MCP remove_breakpoint Procmon request_elevation

Go deeper

High-risk tools in Force Fabric MCP Server → Every high-risk tool this server exposes, in one view.
All high-risk MCP tools → Every high-risk tool across the catalogue, and the policy pattern that contains them.
The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Agent sandbox → Bounding what an agent can execute and where the boundary should sit.
Least privilege for MCP → Granting agents the minimum tool surface the task needs.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about semantic_model_optimization_recommendations

What does the semantic_model_optimization_recommendations tool do? +

LIVE SCAN: Connects to a Fabric Semantic Model and executes DAX queries (COLUMNSTATISTICS). It is categorised as a Execute tool in the Force Fabric MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on semantic_model_optimization_recommendations? +

Register the Force Fabric MCP Server MCP server in PolicyLayer and add a rule for semantic_model_optimization_recommendations: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Force Fabric MCP Server. Nothing to install.

What risk level is semantic_model_optimization_recommendations? +

semantic_model_optimization_recommendations is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit semantic_model_optimization_recommendations? +

Yes. Add a rate_limit block to the semantic_model_optimization_recommendations rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.

How do I block semantic_model_optimization_recommendations completely? +

Set action: deny in the PolicyLayer policy for semantic_model_optimization_recommendations. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.

What MCP server provides semantic_model_optimization_recommendations? +

semantic_model_optimization_recommendations is provided by the Force Fabric MCP Server MCP server (tmdaidevs/force-fabric-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Force Fabric MCP Server tool call.

Start from Force Fabric MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →