stop_research · Python MCP Server Template MCP

WHAT IT DOES

What stop_research does on Python MCP Server Template

AI agents invoke stop_research to trigger actions in Python MCP Server Template. 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 stop_research needs a policy

This tool executes a command to halt a running research operation, which is an active intervention in system state rather than read-only data retrieval (Read), data modification (Write), or irreversible deletion (Destructive). It fits Execute because it triggers an external operation whose effect (stopping research) depends on context.

From the tool's definition Tool name 'stop_research' and description 'Stop the current research task' indicate an action that triggers an external operation or state change—terminating an ongoing process.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

stop_research Rate-limited

stop_research 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": {
    "stop_research": {
      "limits": [
        {
          "counter": "stop_research_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 Python MCP Server Template, so you can run agents against it safely.

FAQ

Questions about stop_research

What does the stop_research tool do? +

Stop the current research task. It is categorised as a Execute tool in the Python MCP Server Template MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on stop_research? +

Register the Python MCP Server Template MCP server in PolicyLayer and add a rule for stop_research: 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 Python MCP Server Template. Nothing to install.

What risk level is stop_research? +

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

Can I rate-limit stop_research? +

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

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

stop_research is provided by the Python MCP Server Template MCP server (raido-star/ridiculous). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.