Get quarterly and annual earnings details for a company.
AI agents call get_earnings_data_mcp to retrieve information from Agentic AI System with MCP Integration without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries public or authorized earnings information from financial data sources. It performs a read-only operation with no side effects, no data modification, no code execution, and no financial transactions. The blast radius of misuse is minimal—an agent can only access earnings data it is authorized to view.
From the tool's definition Tool name 'get_earnings_data_mcp' and description 'Get quarterly and annual earnings details for a company' indicate retrieval of historical financial data with no modification, creation, deletion, or execution capabilities.
Attacks that exploit this kind of access
Get quarterly and annual earnings details for a company. It is categorised as a Read tool in the Agentic AI System with MCP Integration MCP Server, which means it retrieves data without modifying state.
Register the Agentic AI System with MCP Integration MCP server in PolicyLayer and add a rule for get_earnings_data_mcp: 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 Agentic AI System with MCP Integration. Nothing to install.
get_earnings_data_mcp 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_earnings_data_mcp 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_earnings_data_mcp. 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_earnings_data_mcp is provided by the Agentic AI System with MCP Integration MCP server (pratyush-usc-mba/designing-an-agentic-ai-system-with-mcp-integration). 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.
Teams ship this data inside their own products. See what a licence covers →