calculateCustomDCF
Run a tailored Discounted Cash Flow (DCF) analysis using the FMP Custom DCF Advanced API. With detailed inputs, this API allows users to fine-tune their assumptions and variables, offering a more personalized and precise valuation for a company.
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What calculateCustomDCF does on Financial Modeling Prep
AI agents invoke calculateCustomDCF to trigger actions in Financial Modeling Prep. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
input | object | — |
Parameters from the server's own tool schema.
Why calculateCustomDCF is rated High
This tool executes a financial modeling algorithm with user-controlled parameters (assumptions, variables). While it does not directly move money or irreversibly delete data, it runs code/computation with externally-determined inputs whose effects depend on those arguments.
From the tool's definition Tool performs a 'Run a tailored Discounted Cash Flow (DCF) analysis' — the verb 'run' combined with 'Advanced API' and 'fine-tune assumptions and variables' indicates execution of a complex computational operation whose output depends entirely on…
Risk signalsHigh parameter count (20 properties)
Attacks that exploit this kind of access
The rule that runs calculateCustomDCF safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Financial Modeling Prep, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For calculateCustomDCF, this is the rule to start with:
calculateCustomDCF stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Financial Modeling Prep, apply this rule, and every calculateCustomDCF call is checked against it from then on.
Questions about calculateCustomDCF
Run a tailored Discounted Cash Flow (DCF) analysis using the FMP Custom DCF Advanced API. With detailed inputs, this API allows users to fine-tune their assumptions and variables, offering a more personalized and precise valuation for a company. It is categorised as a Execute tool in the Financial Modeling Prep MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
calculateCustomDCF accepts 1 parameter: input. The full parameter table on this page comes from the server's own tool schema.
Register the Financial Modeling Prep MCP server in PolicyLayer and add a rule for calculateCustomDCF: 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. Nothing to install.
calculateCustomDCF is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the calculateCustomDCF 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 calculateCustomDCF. 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.
calculateCustomDCF is provided by the Financial Modeling Prep MCP server (cfocoder/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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