AI agents use rollback_plan to create or update resources in Context Engine MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Context Engine MCP Server environment.
Rollback operations modify state by restoring a previous version of a plan. This is a Write action (reversible state modification) rather than Destructive because: (1) it restores to an existing prior state rather than permanently deleting, (2) the rollback operation itself can be undone by rolling forward again, and (3) the sister tool 'delete_plan' is explicitly listed separately, indicating deletion is distinct…
From the tool's definition Tool name 'rollback_plan' and description 'Rollback a plan to a previous version' indicates reverting plan state to a prior checkpoint.
Documented attack patterns abuse exactly the kind of access rollback_plan gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Context Engine MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for rollback_plan:
{
"version": "1",
"default": "deny",
"tools": {
"rollback_plan": {
"limits": [
{
"counter": "rollback_plan_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}rollback_plan 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.
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Rollback a plan to a previous version. It is categorised as a Write tool in the Context Engine MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Context Engine MCP Server MCP server in PolicyLayer and add a rule for rollback_plan: 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 Context Engine MCP Server. Nothing to install.
rollback_plan is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the rollback_plan 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.
Set action: deny in the PolicyLayer policy for rollback_plan. 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.
rollback_plan is provided by the Context Engine MCP Server MCP server (kirachon/context-engine). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Context Engine MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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50 Context Engine MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.