monte_carlo_estimate
Monte Carlo estimation: estimate pi or compute a definite integral via random sampling.
This record as markdown: /tools/io-github-malamutemayhem-unclick-mcp-server/monte-carlo-estimate.md
What monte_carlo_estimate does on UnClick
AI agents invoke monte_carlo_estimate to trigger actions in UnClick. 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 |
|---|---|---|---|
a | number | — | Lower bound for integral |
b | number | — | Upper bound for integral |
seed | integer | — | Random seed for reproducibility |
method | string | — | Estimation method (default pi) |
samples | integer | — | Number of random samples (default 10000, max 10000000) |
expression | string | — | JS expression in x for integral method |
Parameters from the server's own tool schema.
Why monte_carlo_estimate is rated High
This tool executes a computational algorithm (Monte Carlo simulation) rather than simply reading stored data or writing/modifying records. It performs mathematical computation via random sampling. The blast radius is low since it only produces numerical estimates with no side effects on external systems or data.
From the tool's definition 'Monte Carlo estimation', 'compute a definite integral via random sampling' — runs a computational process (random sampling simulation) to produce a numerical result
Risk signalsAccepts freeform code/query input (expression)
Attacks that exploit this kind of access
The rule that runs monte_carlo_estimate safely
PolicyLayer is an MCP gateway: it sits between your AI agents and UnClick, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For monte_carlo_estimate, this is the rule to start with:
monte_carlo_estimate 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 UnClick, apply this rule, and every monte_carlo_estimate call is checked against it from then on.
Questions about monte_carlo_estimate
Monte Carlo estimation: estimate pi or compute a definite integral via random sampling. It is categorised as a Execute tool in the UnClick MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
monte_carlo_estimate accepts 6 parameters: a, b, seed, method, samples, expression. The full parameter table on this page comes from the server's own tool schema.
Register the UnClick MCP server in PolicyLayer and add a rule for monte_carlo_estimate: 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 UnClick. Nothing to install.
monte_carlo_estimate 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 monte_carlo_estimate 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 monte_carlo_estimate. 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.
monte_carlo_estimate is provided by the UnClick MCP server (@unclick/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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