AI agents call memory_context to retrieve information from Jt without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves and loads existing context data (preferences, entities, knowledge) without modifying or creating anything. It is a read-only operation that surfaces stored information at session start.
From the tool's definition Load session-start context: user preferences, project-related entities, and recently accessed knowledge.
Attacks that exploit this kind of access
Load session-start context: user preferences, project-related entities, and recently accessed knowledge. It is categorised as a Read tool in the Jt MCP Server, which means it retrieves data without modifying state.
Register the Jt MCP server in PolicyLayer and add a rule for memory_context: 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 Jt. Nothing to install.
memory_context 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 memory_context 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_context. 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_context is provided by the Jt MCP server (@houkasaurusrex/jt-mcp-server). 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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