create_pull_request | PolicyLayer

WHAT IT DOES

What create_pull_request does on Eureka Labo Task Management MCP Server

AI agents invoke create_pull_request to trigger actions in Eureka Labo Task Management MCP Server. 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 create_pull_request needs a policy

Creating a pull request triggers an external operation on GitHub — it opens a PR visible to collaborators, potentially triggering CI/CD pipelines, notifications, and review workflows. This is not a simple write to local data but an external action with side effects that depend on repository state and branch contents, placing it in the Execute category.

From the tool's definition 'Create a GitHub pull request for all tasks in the current branch. Generates PR description from work sessions. Requires GitHub integration configured for the project.'

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

create_pull_request Rate-limited

create_pull_request 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": {
    "create_pull_request": {
      "limits": [
        {
          "counter": "create_pull_request_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 Eureka Labo Task Management MCP Server, so you can run agents against it safely.

FAQ

Questions about create_pull_request

What does the create_pull_request tool do? +

Create a GitHub pull request for all tasks in the current branch. Generates PR description from work sessions. Requires GitHub integration configured for the project. It is categorised as a Execute tool in the Eureka Labo Task Management MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on create_pull_request? +

Register the Eureka Labo Task Management MCP Server MCP server in PolicyLayer and add a rule for create_pull_request: 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 Eureka Labo Task Management MCP Server. Nothing to install.

What risk level is create_pull_request? +

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

Can I rate-limit create_pull_request? +

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

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

create_pull_request is provided by the Eureka Labo Task Management MCP Server MCP server (mazemaze/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.