AI agents call textedit_get_documents to retrieve information from Mcp Mac without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries the state of open TextEdit documents and returns a list. It performs no write, delete, execute, or financial operations. The only potential concern is information disclosure (reading document names/metadata), which is a low-severity Read operation.
From the tool's definition Tool name 'textedit_get_documents' and description 'Get list of open TextEdit documents' indicate a retrieval operation with no modification or side effects.
Attacks that exploit this kind of access
Get list of open TextEdit documents. It is categorised as a Read tool in the Mcp Mac MCP Server, which means it retrieves data without modifying state.
Register the Mcp Mac MCP server in PolicyLayer and add a rule for textedit_get_documents: 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 Mcp Mac. Nothing to install.
textedit_get_documents 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 textedit_get_documents 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 textedit_get_documents. 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.
textedit_get_documents is provided by the Mcp Mac MCP server (samicokar/mcp-mac). 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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