Toggle anonymous metrics sharing. Default is OFF.
AI agents use opt_in_share to create or update resources in Librarian MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Librarian MCP environment.
This tool modifies a configuration/preference setting (metrics sharing opt-in toggle). It is a reversible write operation — turning sharing on or off — with no destructive, financial, or execution implications. Misuse could at most enable unwanted anonymous data sharing, which is a low blast radius.
From the tool's definition Toggle anonymous metrics sharing. Default is OFF.
Attacks that exploit this kind of access
Toggle anonymous metrics sharing. Default is OFF. It is categorised as a Write tool in the Librarian MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Librarian MCP server in PolicyLayer and add a rule for opt_in_share: 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 Librarian MCP. Nothing to install.
opt_in_share 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 opt_in_share 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 opt_in_share. 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.
opt_in_share is provided by the Librarian MCP server (liana-banyan/librarian-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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