Query a cached context. The cache must have been created with context_load first.
AI agents call context_query 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.
This tool performs a read-only operation against cached context data. It retrieves or queries information from a previously loaded cache without creating, modifying, deleting, or executing anything. The operation is non-destructive and has no side effects beyond data retrieval. It is the lowest-risk classification.
From the tool's definition Tool name 'context_query' combined with description 'Query a cached context' indicates retrieval/querying of previously loaded data with no modification or execution of code.
Documented attack patterns abuse exactly the kind of access context_query 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_query:
{
"version": "1",
"default": "deny",
"tools": {
"context_query": {}
}
}context_query 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.
Query a cached context. The cache must have been created with context_load first. 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_query: 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_query 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_query 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_query. 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_query 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.
Free to start. No card required.
6 Mnemo tools catalogued and risk-classified — across an index of 43,000+ MCP servers.