run_agent_eval · Azure AI Foundry MCP Server MCP

WHAT IT DOES

What run_agent_eval does on Azure AI Foundry MCP Server

AI agents invoke run_agent_eval to trigger actions in Azure AI Foundry 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.

WHY IT NEEDS A POLICY

Why run_agent_eval needs a policy

run_agent_eval triggers real processes with real consequences. An agent gone sideways doesn't fire it once — it starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

run_agent_eval Rate-limited

run_agent_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.

View as policy code

policy.json

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

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches Azure AI Foundry MCP Server, so you can run agents against it safely.

FAQ

Questions about run_agent_eval

What does the run_agent_eval tool do? +

run_agent_eval. It is categorised as a Execute tool in the Azure AI Foundry 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_agent_eval? +

Register the Azure AI Foundry MCP Server MCP server in PolicyLayer and add a rule for run_agent_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 Foundry MCP Server. Nothing to install.

What risk level is run_agent_eval? +

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

Can I rate-limit run_agent_eval? +

Yes. Add a rate_limit block to the run_agent_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_agent_eval completely? +

Set action: deny in the PolicyLayer policy for run_agent_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_agent_eval? +

run_agent_eval is provided by the Azure AI Foundry MCP Server MCP server (youssef7788/mcp-foundry). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.