recall
AI agents call recall to retrieve information from Chronos MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves stored information from persistent memory and the knowledge graph. It has no destructive effects, does not modify state, and does not execute arbitrary code or trigger external operations. It is a read-only query operation. The low severity reflects minimal risk if misused—an AI agent could retrieve sensitive information but cannot alter or delete it.
From the tool's definition Tool name is 'recall' and sits alongside sibling tools like 'get_memory', 'get_memory_health', and 'log_search_feedback' in a memory/knowledge-graph server.
Attacks that exploit this kind of access
recall. It is categorised as a Read tool in the Chronos MCP MCP Server, which means it retrieves data without modifying state.
Register the Chronos MCP server in PolicyLayer and add a rule for recall: 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 Chronos MCP. Nothing to install.
recall 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 recall 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 recall. 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.
recall is provided by the Chronos MCP server (kodaxadev/chronosmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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