The Earnings Surprises Bulk API allows users to retrieve bulk data on annual earnings surprises, enabling quick analysis of which companies have beaten, missed, or met their earnings estimates. This API provides actual versus estimated earnings per share (EPS) for multiple companies at once, offe...
AI agents call getEarningsSurprisesBulk to retrieve information from Financial Modeling Prep MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool only reads and returns historical financial data (earnings surprises and EPS comparisons). It does not create, modify, delete, execute code, or move money. The data retrieved is informational for analysis purposes only, with no capability to alter systems or commitments. Misuse would be limited to unauthorized data access rather than operational damage.
From the tool's definition The tool 'retrieves bulk data on annual earnings surprises' and 'provides actual versus estimated earnings per share (EPS) for multiple companies at once' — these are query/retrieval operations with no modification or side effects.
Attacks that exploit this kind of access
The Earnings Surprises Bulk API allows users to retrieve bulk data on annual earnings surprises, enabling quick analysis of which companies have beaten, missed, or met their earnings estimates. This API provides actual versus estimated earnings per share (EPS) for multiple companies at once, offering valuable insights for investors and analysts. It is categorised as a Read tool in the Financial Modeling Prep MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Financial Modeling Prep MCP Server MCP server in PolicyLayer and add a rule for getEarningsSurprisesBulk: 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 Financial Modeling Prep MCP Server. Nothing to install.
getEarningsSurprisesBulk 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 getEarningsSurprisesBulk 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 getEarningsSurprisesBulk. 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.
getEarningsSurprisesBulk is provided by the Financial Modeling Prep MCP Server MCP server (vijitdaroch/financial-modeling-prep-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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