run_text_eval · Azure AI Agent Service MCP Server MCP

WHAT IT DOES

What run_text_eval does on Azure AI Agent Service MCP Server

AI agents invoke run_text_eval to trigger actions in Azure AI Agent Service MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

THE RISK

High Risk

Why run_text_eval needs a policy

Despite the empty description reducing confidence, the tool name 'run_text_eval' and its position among execution-oriented siblings (execute_dynamic_swagger_action, agent_query_and_evaluate) indicates it executes evaluation logic on text data. This is an Execute-category action—it triggers external operations whose effects depend on the evaluated content.

From the tool's definition Tool name 'run_text_eval' indicates execution of evaluation logic. Empty description limits certainty, but the context of an AI Agent Service platform combined with sibling tools like 'agent_query_and_evaluate', 'execute_dynamic_swagger_action', and…

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

POLICY

How to control run_text_eval

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 run_text_eval:

policy.json

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

run_text_eval 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 Azure AI Agent Service 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.

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EXPLORE

Related tools and policies

More Azure AI Agent Service MCP Server tools

Execute deploy_model_on_ai_services deploy_model_on_ai_services Execute execute_dynamic_swagger_action Execute a dynamically generated tool from the Swagger specification. Args: Execute run_agent_eval Run agent evaluation on agent data. Accepts both plain text and JSON strings. Paramet Execute agent_query_and_evaluate Query an agent and evaluate its response in a single operation. Parameters: - age Execute query_default_agent Send a query to the default configured Azure AI Agent. Parameters: - query: Text Execute connect_agent Connect to a specific Azure AI Agent and run a query. Parameters: - agent_id: ID Write create_azure_ai_services_account create_azure_ai_services_account Write create_foundry_project create_foundry_project

All 28 Azure AI Agent Service MCP Server tools →

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Go deeper

High-risk tools in Azure AI Agent Service 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 run_text_eval

What does the run_text_eval tool do? +

run_text_eval. It is categorised as a Execute tool in the Azure AI Agent Service 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 run_text_eval? +

Register the Azure AI Agent Service MCP Server MCP server in PolicyLayer and add a rule for run_text_eval: 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 run_text_eval? +

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

Can I rate-limit run_text_eval? +

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

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

run_text_eval 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.