AI agents use memory_set_config to create or update resources in Rekal — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Rekal environment.
The tool name strongly suggests it modifies configuration state reversibly. Without an explicit description, confidence is moderate, but the pattern of sibling tools (memory_delete, memory_prune, memory_health) and the server's role in managing persistent memory storage indicates this performs a Write operation.
From the tool's definition Tool name 'memory_set_config' indicates configuration modification. The server manages a local SQLite storage system with memory persistence.
Documented attack patterns abuse exactly the kind of access memory_set_config gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Rekal, and nothing reaches the server without passing your rules. This is the rule we recommend for memory_set_config:
{
"version": "1",
"default": "deny",
"tools": {
"memory_set_config": {
"limits": [
{
"counter": "memory_set_config_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}memory_set_config 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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memory_set_config. It is categorised as a Write tool in the Rekal MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Rekal MCP server in PolicyLayer and add a rule for memory_set_config: 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 Rekal. Nothing to install.
memory_set_config 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 memory_set_config 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 memory_set_config. 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.
memory_set_config is provided by the Rekal MCP server (janbjorge/rekal). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Rekal, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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21 Rekal tools catalogued and risk-classified — across an index of 43,000+ MCP servers.