Simulate agent payment policies for tokenized A2A corridors: set spend caps, MCC allowlists, velocity throttles, and approval thresholds; run synthetic transactions against the policy and export the result as a Policy Mandate. Browser-based, client-side only, zero PII. Renders the interactive AIN...
AI agents invoke agentic_mandate_sandbox to trigger actions in Ainumbers Mcp Apps. 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 |
|---|---|---|---|
inputs | object | — | Map of tool input element IDs to values (see manifest input_schema). Applied via AIN Bridge prefill. |
Parameters from the server's own tool schema.
Although labeled a sandbox and described as client-side only with no PII, the tool's core function is to execute payment policy logic and run synthetic transactions. This is an Execute category tool because it triggers external payment policy operations whose behavior depends on user-supplied arguments.
From the tool's definition Tool description states it will "run synthetic transactions against the policy" and "simulate agent payment policies." The tool executes payment policy simulations with configurable parameters including "spend caps, MCC allowlists, velocity throttles, and…
Attacks that exploit this kind of access
Simulate agent payment policies for tokenized A2A corridors: set spend caps, MCC allowlists, velocity throttles, and approval thresholds; run synthetic transactions against the policy and export the result as a Policy Mandate. Browser-based, client-side only, zero PII. Renders the interactive AINumbers tool as a widget; inputs are applied via the AIN Bridge and the tool runs client-side (zero PII, zero network). It is categorised as a Execute tool in the Ainumbers Mcp Apps MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
agentic_mandate_sandbox accepts 1 parameter: inputs. The full parameter table on this page comes from the server's own tool schema.
Register the Ainumbers Mcp Apps MCP server in PolicyLayer and add a rule for agentic_mandate_sandbox: 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 Ainumbers Mcp Apps. Nothing to install.
agentic_mandate_sandbox 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 agentic_mandate_sandbox 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 agentic_mandate_sandbox. 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.
agentic_mandate_sandbox is provided by the Ainumbers Mcp Apps MCP server (postoaklabs/ainumbers-mcp-apps). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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