get_shared_report
AI agents call get_shared_report to retrieve information from Clockify Time Tracking without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The 'get_' prefix is a strong indicator of a read operation. No evidence suggests execution of arbitrary code, destructive actions, financial transactions, or data modification. The tool appears to fetch or query shared report data from the Clockify system. Confidence is moderate (0.7) due to the empty description, which prevents full verification of potential side effects or scope.
From the tool's definition Tool name 'get_shared_report' indicates retrieval of report data. The description is empty, but the naming pattern and context within a time-tracking server (Clockify) suggest this retrieves existing report data rather than modifying, executing, or deleting…
Attacks that exploit this kind of access
get_shared_report. It is categorised as a Read tool in the Clockify Time Tracking MCP Server, which means it retrieves data without modifying state.
Register the Clockify Time Tracking MCP server in PolicyLayer and add a rule for get_shared_report: 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 Clockify Time Tracking. Nothing to install.
get_shared_report 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 get_shared_report 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 get_shared_report. 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.
get_shared_report is provided by the Clockify Time Tracking MCP server (pypi:clockify-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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