List all active context caches with their metadata (alias, token count, expiry).
AI agents call context_list to retrieve information from Mnemo without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool queries and returns metadata about existing context caches without performing any side effects. This is a read-only operation that retrieves system state. Severity is low because the information exposed (cache metadata like aliases, token counts, expiry times) poses minimal risk even if accessed by an unauthorized agent.
From the tool's definition Tool name 'context_list' and description 'List all active context caches with their metadata' indicate pure information retrieval with no modification, deletion, or execution.
Documented attack patterns abuse exactly the kind of access context_list gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Mnemo, and nothing reaches the server without passing your rules. This is the rule we recommend for context_list:
{
"version": "1",
"default": "deny",
"tools": {
"context_list": {}
}
}context_list is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List all active context caches with their metadata (alias, token count, expiry). It is categorised as a Read tool in the Mnemo MCP Server, which means it retrieves data without modifying state.
Register the Mnemo MCP server in PolicyLayer and add a rule for context_list: 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 Mnemo. Nothing to install.
context_list 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 context_list 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 context_list. 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.
context_list is provided by the Mnemo MCP server (logos-flux/mnemo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Mnemo, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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6 Mnemo tools catalogued and risk-classified — across an index of 43,000+ MCP servers.