Retrieve the profit and loss (income) statement for a given ticker symbol.
AI agents call get_profitLoss to retrieve information from MCPServerDemo without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves financial data (profit and loss statements) based on a ticker symbol input. It performs no modifications, deletions, code execution, or financial transactions. The sibling tools (get_balancesheet, get_cashFlows, get_quarterlyresults, get_Ratio) are all read operations that fetch financial data.
From the tool's definition Tool name is 'get_profitLoss' with description 'Retrieve the profit and loss (income) statement for a given ticker symbol.' The verb 'Retrieve' and the context of fetching financial statements indicate a read-only operation that queries data without…
Attacks that exploit this kind of access
Retrieve the profit and loss (income) statement for a given ticker symbol. It is categorised as a Read tool in the MCPServerDemo MCP Server, which means it retrieves data without modifying state.
Register the MCPServerDemo MCP server in PolicyLayer and add a rule for get_profitLoss: 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 MCPServerDemo. Nothing to install.
get_profitLoss 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_profitLoss 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_profitLoss. 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_profitLoss is provided by the MCPServerDemo MCP server (nitinudasin/mcpserverdemo). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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