issue-close · Python MCP: Risk & Policy

WHAT IT DOES

What issue-close does on Python

AI agents use issue-close 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-close needs a policy

Closing an issue is a write operation that changes the state of data (issue state modified from open to closed) and optionally creates new data (comment). While the action is reversible (issues can typically be reopened), it does modify project state and communication artifacts.

From the tool's definition Tool description states 'Closes an issue' which modifies the state of an issue from open to closed, and accepts an 'optional comment' which creates new content. These are reversible write operations.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

issue-close Rate-limited

issue-close 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-close": {
      "limits": [
        {
          "counter": "issue-close_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-close

What does the issue-close tool do? +

Closes an issue with an optional comment and reason. Returns structured data with issue number, state, URL, reason, and comment URL. 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-close? +

Register the Python MCP server in PolicyLayer and add a rule for issue-close: 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-close? +

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

Can I rate-limit issue-close? +

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

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

issue-close 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.

// THE FULL RECORD

issue-close is one line of Python's registry record.

The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.

Teams ship this data inside their own products. See what a licence covers →