run_monte_carlo

run_monte_carlo

Server Portfolio l4b4r4b4b4/portfolio-mcp
Category Execute
Risk class High
Parameters 00 required

What run_monte_carlo does on Portfolio

AI agents invoke run_monte_carlo to trigger actions in Portfolio. 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.

Why run_monte_carlo needs a policy

Monte Carlo simulations execute complex numerical computations whose results depend on random inputs and parameters passed by the user. While not destructive or modifying data, this is an Execute operation because it runs algorithms with side effects (CPU/memory consumption, time passage) and outputs that vary based on arguments.

From the tool's definition Tool name 'run_monte_carlo' combined with server context describing 'Monte Carlo simulations' and 'advanced analysis'.

Questions about run_monte_carlo

What does the run_monte_carlo tool do? +

run_monte_carlo. It is categorised as a Execute tool in the Portfolio MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on run_monte_carlo? +

Register the Portfolio MCP server in PolicyLayer and add a rule for run_monte_carlo: 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 Portfolio. Nothing to install.

What risk level is run_monte_carlo? +

run_monte_carlo is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit run_monte_carlo? +

Yes. Add a rate_limit block to the run_monte_carlo 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.

How do I block run_monte_carlo completely? +

Set action: deny in the PolicyLayer policy for run_monte_carlo. 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.

What MCP server provides run_monte_carlo? +

run_monte_carlo is provided by the Portfolio MCP server (l4b4r4b4b4/portfolio-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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