issue-create · Python MCP: Risk & Policy

WHAT IT DOES

What issue-create does on Python

AI agents use issue-create to create or update resources in Python — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Python environment.

WHY IT NEEDS A POLICY

Why issue-create needs a policy

This tool creates new issues in what appears to be an issue tracking system (likely GitHub or similar, given the server context mentions structured output from development tools). Creating an issue is a reversible write operation—issues can typically be deleted or closed—rather than a destructive action. The impact is bounded to creating one issue record, making it Write rather than Execute.

From the tool's definition Tool name 'issue-create' and description 'Creates a new issue' indicate a data creation operation that modifies state by adding a new record. The tool returns 'issue number, URL, and labels applied', confirming it persists new data.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

issue-create Rate-limited

issue-create stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "issue-create": {
      "limits": [
        {
          "counter": "issue-create_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

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, so you can run agents against it safely.

FAQ

Questions about issue-create

What does the issue-create tool do? +

Creates a new issue. Returns structured data with issue number, URL, and labels applied. It is categorised as a Write tool in the Python MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on issue-create? +

Register the Python MCP server in PolicyLayer and add a rule for issue-create: 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. Nothing to install.

What risk level is issue-create? +

issue-create is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit issue-create? +

Yes. Add a rate_limit block to the issue-create 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 issue-create completely? +

Set action: deny in the PolicyLayer policy for issue-create. 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 issue-create? +

issue-create is provided by the Python MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.