deep_research_heavy · Openai MCP: Risk & Policy

WHAT IT DOES

What deep_research_heavy does on Openai

AI agents invoke deep_research_heavy to trigger actions in Openai. 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 deep_research_heavy needs a policy

The sibling tool 'deep_research' and the server description mention 'deep research' as an external operation triggered via ChatGPT Plus/Pro account. 'deep_research_heavy' likely triggers a more intensive version of that operation. With no description, confidence is low, but by analogy to the sibling tool it most plausibly executes an external research process rather than simply reading local data.

From the tool's definition Tool name 'deep_research_heavy' on a server that includes 'deep_research' among sibling tools; description is empty.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

deep_research_heavy Rate-limited

deep_research_heavy 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": {
    "deep_research_heavy": {
      "limits": [
        {
          "counter": "deep_research_heavy_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 Openai, so you can run agents against it safely.

FAQ

Questions about deep_research_heavy

What does the deep_research_heavy tool do? +

deep_research_heavy. It is categorised as a Execute tool in the Openai MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on deep_research_heavy? +

Register the Openai MCP server in PolicyLayer and add a rule for deep_research_heavy: 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 Openai. Nothing to install.

What risk level is deep_research_heavy? +

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

Can I rate-limit deep_research_heavy? +

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

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

deep_research_heavy is provided by the Openai MCP server (robotlearning123/gpt2agent). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.