Resume from the latest checkpoint. Restores all context fragments, dedup index, co-access patterns, and custom metadata from the most recent checkpoint.
AI agents call resume_state to retrieve information from Entroly Context Engine without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool reads and restores previously saved state from a checkpoint into the active session. It does not create, modify, delete, or execute anything — it retrieves persisted context data and loads it into memory. However, severity is medium because restoring state could overwrite or displace the current in-memory context, potentially causing unintended context shifts for the AI agent.
From the tool's definition "Resume from the latest checkpoint" and "Restores all context fragments, dedup index, co-access patterns, and custom metadata from the most recent checkpoint"
Documented attack patterns abuse exactly the kind of access resume_state gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Entroly Context Engine, and nothing reaches the server without passing your rules. This is the rule we recommend for resume_state:
{
"version": "1",
"default": "deny",
"tools": {
"resume_state": {}
}
}resume_state is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Resume from the latest checkpoint. Restores all context fragments, dedup index, co-access patterns, and custom metadata from the most recent checkpoint. It is categorised as a Read tool in the Entroly Context Engine MCP Server, which means it retrieves data without modifying state.
Register the Entroly Context Engine MCP server in PolicyLayer and add a rule for resume_state: 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 Entroly Context Engine. Nothing to install.
resume_state is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the resume_state 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 resume_state. 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.
resume_state is provided by the Entroly Context Engine MCP server (juyterman1000/entroly). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Entroly Context Engine, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
52 Entroly Context Engine tools catalogued and risk-classified — across an index of 43,000+ MCP servers.