Get user's profile information (background, preferences, work, interests). USE THIS TOOL: At the start of conversations to understand who you're helping. This provides context about the user's technical preferences, work style, and personal details. Returns: User profile summary as text.
AI agents call memory_about_user to retrieve information from Core without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
profile | boolean | — | Set to true to get full profile. Leave empty for default profile view. |
Parameters from the server's own tool schema.
This tool purely retrieves stored profile data about the user with no side effects. It reads and returns a text summary of user background, preferences, and interests. No data is created, modified, or deleted. Severity is low as it only reads personal profile data already stored in the system, though there is a minor privacy consideration.
From the tool's definition 'Get user's profile information (background, preferences, work, interests)' and 'Returns: User profile summary as text'
Documented attack patterns abuse exactly the kind of access memory_about_user gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Core, and nothing reaches the server without passing your rules. This is the rule we recommend for memory_about_user:
{
"version": "1",
"default": "deny",
"tools": {
"memory_about_user": {}
}
}memory_about_user is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get user's profile information (background, preferences, work, interests). USE THIS TOOL: At the start of conversations to understand who you're helping. This provides context about the user's technical preferences, work style, and personal details. Returns: User profile summary as text. It is categorised as a Read tool in the Core MCP Server, which means it retrieves data without modifying state.
memory_about_user accepts 1 parameter: profile. The full parameter table on this page comes from the server's own tool schema.
Register the Core MCP server in PolicyLayer and add a rule for memory_about_user: 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 Core. Nothing to install.
memory_about_user 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_about_user 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_about_user. 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_about_user is provided by the Core MCP server (@transcend-io/mcp-server-core). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Core, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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9 Core tools catalogued and risk-classified — across an index of 43,000+ MCP servers.