deploy_project · Openl MCP: Risk & Policy

WHAT IT DOES

What deploy_project does on Openl

AI agents invoke deploy_project to trigger actions in Openl. 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 deploy_project needs a policy

This tool executes a deployment action that publishes rules to production systems, affecting live runtime behavior. While not creating/modifying data in a traditional sense, deployment is an execute operation because it triggers an external process whose effects depend on which project/branch is deployed.

From the tool's definition Tool description states 'Deploy a project to production environment. Publishes rules to a deployment repository for runtime execution.' The use of 'Deploy', 'production environment', and 'runtime execution' indicates this triggers external operations with…

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

deploy_project Rate-limited

deploy_project 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": {
    "deploy_project": {
      "limits": [
        {
          "counter": "deploy_project_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 Openl, so you can run agents against it safely.

FAQ

Questions about deploy_project

What does the deploy_project tool do? +

Deploy a project to production environment. Publishes rules to a deployment repository for runtime execution. Use production repository name (not ID) - e.g.,. It is categorised as a Execute tool in the Openl MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on deploy_project? +

Register the Openl MCP server in PolicyLayer and add a rule for deploy_project: 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 Openl. Nothing to install.

What risk level is deploy_project? +

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

Can I rate-limit deploy_project? +

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

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

deploy_project is provided by the Openl MCP server (openl-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.