Low Risk

get_text_evaluator_requirements

Get the required input fields for a specific text evaluator or all text evaluators. Parameters: - evaluator_name: Optional name of evaluator. If None, returns requirements for all evaluators.

How to control get_text_evaluator_requirements ↓

What get_text_evaluator_requirements does on Azure AI Agent Service MCP Server

AI agents call get_text_evaluator_requirements to retrieve information from Azure AI Agent Service MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Low Risk

Why get_text_evaluator_requirements needs a policy

This tool queries and retrieves information about text evaluator requirements without modifying, deleting, or executing any operations. It is purely informational, making it a Read category tool with low severity risk.

From the tool's definition The tool description states it 'Get[s] the required input fields for a specific text evaluator or all text evaluators.' This is a retrieval operation with no side effects. It takes an optional evaluator_name parameter and returns metadata about requirements.

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

How to control get_text_evaluator_requirements

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

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_text_evaluator_requirements": {}
  }
}

get_text_evaluator_requirements is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

  1. Create a free account and register Azure AI Agent Service MCP Server — nothing to install.
  2. Add this policy — paste it, or build it visually.
  3. Point your MCP client (Claude, Cursor, anything) at your gateway URL.
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Related tools and policies

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Questions about get_text_evaluator_requirements

What does the get_text_evaluator_requirements tool do? +

Get the required input fields for a specific text evaluator or all text evaluators. Parameters: - evaluator_name: Optional name of evaluator. If None, returns requirements for all evaluators. It is categorised as a Read tool in the Azure AI Agent Service MCP Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_text_evaluator_requirements? +

Register the Azure AI Agent Service MCP Server MCP server in PolicyLayer and add a rule for get_text_evaluator_requirements: 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 Azure AI Agent Service MCP Server. Nothing to install.

What risk level is get_text_evaluator_requirements? +

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

Can I rate-limit get_text_evaluator_requirements? +

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

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

get_text_evaluator_requirements is provided by the Azure AI Agent Service MCP Server MCP server (microsoft-foundry/mcp-foundry). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Azure AI Agent Service MCP Server tool call.

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

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28 Azure AI Agent Service MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.

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