AI agents use append_note to create or update resources in Memory — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Memory environment.
The name 'append_note' strongly implies creating or modifying a note by appending content to it, which is a reversible write operation. The server context (personal notes and files) supports this interpretation. Confidence is reduced due to the empty description — the tool could potentially overwrite rather than append, but the name suggests additive modification.
From the tool's definition Tool name 'append_note' suggests appending/adding content to a note, which is a write operation. Description is empty and uninformative.
Attacks that exploit this kind of access
append_note. It is categorised as a Write tool in the Memory MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Memory MCP server in PolicyLayer and add a rule for append_note: 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 Memory. Nothing to install.
append_note is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the append_note 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 append_note. 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.
append_note is provided by the Memory MCP server (shaktisinhchavda/memory-mcp). 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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