Saves the current AI session state for another agent to resume.
AI agents use save_handoff to create or update resources in M3 Memory — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your M3 Memory environment.
This tool creates or modifies persistent memory records (session state) that another agent can later retrieve. It is a Write operation because it stores new data reversibly; the saved state can be retrieved, updated, or cleared later without permanent loss.
From the tool's definition The tool 'saves the current AI session state for another agent to resume' — this is a create/modify operation that stores data persistently in the memory layer.
Documented attack patterns abuse exactly the kind of access save_handoff gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and M3 Memory, and nothing reaches the server without passing your rules. This is the rule we recommend for save_handoff:
{
"version": "1",
"default": "deny",
"tools": {
"save_handoff": {
"limits": [
{
"counter": "save_handoff_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}save_handoff 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.
Free to start. No card required.
Saves the current AI session state for another agent to resume. It is categorised as a Write tool in the M3 Memory MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the M3 Memory MCP server in PolicyLayer and add a rule for save_handoff: 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 M3 Memory. Nothing to install.
save_handoff 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 save_handoff 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 save_handoff. 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.
save_handoff is provided by the M3 Memory MCP server (skynetcmd/m3-memory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from M3 Memory, 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.
43 M3 Memory tools catalogued and risk-classified — across an index of 43,000+ MCP servers.