autonomous_plan · MCP Autonomous Analyst MCP: Risk & Policy

WHAT IT DOES

What autonomous_plan does on MCP Autonomous Analyst

AI agents invoke autonomous_plan to trigger actions in MCP Autonomous Analyst. 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 autonomous_plan needs a policy

The word 'agentic' signals autonomous decision-making and action-taking beyond simple data retrieval. In the context of this server (which includes an 'autonomous_pipeline' tool and local LLM orchestration), 'autonomous_plan' most likely triggers a chain of automated steps — qualifying as Execute. It is not merely reading/querying data, as it produces recommendations that may drive downstream actions.

From the tool's definition 'Agentic recommendation based on full dataset analysis' — the term 'agentic' implies autonomous multi-step orchestration; combined with sibling tool 'autonomous_pipeline', this tool likely triggers or coordinates a broader automated execution pipeline

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

autonomous_plan Rate-limited

autonomous_plan 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": {
    "autonomous_plan": {
      "limits": [
        {
          "counter": "autonomous_plan_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 MCP Autonomous Analyst, so you can run agents against it safely.

FAQ

Questions about autonomous_plan

What does the autonomous_plan tool do? +

Agentic recommendation based on full dataset analysis. It is categorised as a Execute tool in the MCP Autonomous Analyst MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on autonomous_plan? +

Register the MCP Autonomous Analyst MCP server in PolicyLayer and add a rule for autonomous_plan: 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 MCP Autonomous Analyst. Nothing to install.

What risk level is autonomous_plan? +

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

Can I rate-limit autonomous_plan? +

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

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

autonomous_plan is provided by the MCP Autonomous Analyst MCP server (madmando/mcp-autonomous-analyst). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.