getEarningsSurprisesBulk
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...
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What getEarningsSurprisesBulk does on Financial Modeling Prep (FMP) Server
AI agents call getEarningsSurprisesBulk to retrieve information from Financial Modeling Prep (FMP) Server without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
year | string | — | Year to get earnings surprises for |
Parameters from the server's own tool schema.
Why getEarningsSurprisesBulk is rated Low
This tool performs a read-only query of historical financial data (earnings surprises and EPS comparisons). It has no side effects—it neither modifies data, executes external operations, deletes information, nor commits financial transactions. The blast radius of misuse is minimal; an AI agent could only retrieve and analyze existing market data.
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.' The verbs 'retrieve' and 'provides' indicate data retrieval with no modification, creation, deletion, or…
Attacks that exploit this kind of access
The rule that runs getEarningsSurprisesBulk safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Financial Modeling Prep (FMP) Server , and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For getEarningsSurprisesBulk, this is the rule to start with:
getEarningsSurprisesBulk is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Financial Modeling Prep (FMP) Server , apply this rule, and every getEarningsSurprisesBulk call is checked against it from then on.
Questions about getEarningsSurprisesBulk
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 (FMP) Server MCP Server, which means it retrieves data without modifying state.
getEarningsSurprisesBulk accepts 1 parameter: year. The full parameter table on this page comes from the server's own tool schema.
Register the Financial Modeling Prep (FMP) 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 (FMP) 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 (FMP) Server MCP server (imbenrabi/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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