Review slips in Sanka.
AI agents call list_slips to retrieve information from Sanka MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The verb 'list' and 'review' are characteristic of Read operations that query or retrieve data without changing state. The sibling tools (activate_invoice, approve_payroll_run, etc.) show this server handles sensitive business operations, but this specific tool only retrieves slip records for viewing.
From the tool's definition Tool name 'list_slips' and description 'Review slips in Sanka' indicate a retrieval/query operation with no modification or side effects.
Attacks that exploit this kind of access
Review slips in Sanka. It is categorised as a Read tool in the Sanka MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Sanka MCP Server MCP server in PolicyLayer and add a rule for list_slips: 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 Sanka MCP Server. Nothing to install.
list_slips 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 list_slips 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 list_slips. 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.
list_slips is provided by the Sanka MCP Server MCP server (sankahq/sanka-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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