lakehouse_list_tables

THE RISK

Low Risk

Why lakehouse_list_tables needs a policy

This tool queries and returns information about existing tables in a Lakehouse without modifying, deleting, or executing operations on the data. It is a pure read operation that retrieves metadata about tables. The severity is low because listing tables poses minimal risk even if misused by an AI agent—it only exposes table structure and locations without enabling data modification or deletion.

From the tool's definition Tool name 'lakehouse_list_tables' and description 'List all tables in a Fabric Lakehouse with their type, format (Delta/Parquet), and location' indicate a retrieval operation with no side effects.

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

POLICY

How to control lakehouse_list_tables

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 lakehouse_list_tables:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "lakehouse_list_tables": {}
  }
}

lakehouse_list_tables is read-only, so it stays allowed — but 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.

CAP THIS TOOL →

Free to start. No card required.

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).

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about lakehouse_list_tables

What does the lakehouse_list_tables tool do? +

List all tables in a Fabric Lakehouse with their type, format (Delta/Parquet), and location. It is categorised as a Read tool in the Force Fabric MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on lakehouse_list_tables? +

Register the Force Fabric MCP Server MCP server in PolicyLayer and add a rule for lakehouse_list_tables: 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 lakehouse_list_tables? +

lakehouse_list_tables is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit lakehouse_list_tables? +

Yes. Add a rate_limit block to the lakehouse_list_tables 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 lakehouse_list_tables completely? +

Set action: deny in the PolicyLayer policy for lakehouse_list_tables. 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 lakehouse_list_tables? +

lakehouse_list_tables 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 →