simulate_spend_policy

SERVERAinumbers Mcp Apps SOURCEpostoaklabs/ainumbers-mcp-apps

High RISK CLASS

Category Execute

Parameters 40 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/postoaklabs-ainumbers-mcp-apps/simulate-spend-policy.md

WHAT IT DOES

What simulate_spend_policy does on Ainumbers Mcp Apps

AI agents invoke simulate_spend_policy 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
`compute`	string	—	Compute mode (v0.4 Compute Binding). "auto" (default) = server for gpu:false nodes with registered kernels; "server" = force server-side; "browser" = always ret
`parent_hashes`	array	—	execution_hash values from upstream ChainGraph AP2 artifacts to chain from (sets chain.parent_hashes in the export).
`parent_tool_ids`	array	—	tool_id values matching parent_hashes, in the same order.
`policy_parameters`	object	—	Input parameters for this tool's decision function. For gpu:false nodes with a registered kernel, these are computed server-side when compute is "auto" or "serv

Parameters from the server's own tool schema.

RISK

Why simulate_spend_policy is rated High

Runs spend-policy simulations on a compute node, triggering external agentic payment policy execution.

From the tool's definition compute node, deterministic execution, AP2 artifact, execution_hash, chain provenance

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs simulate_spend_policy safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Ainumbers Mcp Apps, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For simulate_spend_policy, this is the rule to start with:

simulate_spend_policy Rate-limited

simulate_spend_policy 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.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "simulate_spend_policy": {
      "limits": [
        {
          "counter": "simulate_spend_policy_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Ainumbers Mcp Apps, apply this rule, and every simulate_spend_policy call is checked against it from then on.

FAQ

Questions about simulate_spend_policy

What does the simulate_spend_policy tool do? +

Agent Spend-Policy Simulator: OpenChainGraph compute node (payment_policy). Deterministic OpenChainGraph compute node. By default (compute:"auto") inputs are computed server-side on Cloudflare Workers for gpu:false nodes with a registered kernel; compute:"browser" forces client-side execution and returns a browser delegation URL instead. gpu:true nodes always delegate to the browser. Inputs are processed transiently to compute the response and are not stored, logged, or retained. Use synthetic or anonymised inputs only. Exports an AP2 artifact with execution_hash for chain provenance. Consumes upstream artifacts from: art-01-ap2-mandate-chain-validator, art-04-agent-identity-attestation-checker. Output feeds: ptg-01-ap2-prompt-template-generator. Open at: https://ainumbers.co/chaingraph/art-02-agent-spend-policy-simulator.html FV-status (published/proven/still-trusted for this spec): /fv-status/8b5ae30d812cd234cfb6068c4ce2022f01d10f2a358979b0f0d73421e09d2543.json — a snapshot, not a subscription; this receipt verifies offline regardless of whether that file is ever fetched. 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.

What parameters does simulate_spend_policy accept? +

simulate_spend_policy accepts 4 parameters: compute, parent_hashes, parent_tool_ids, policy_parameters. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on simulate_spend_policy? +

Register the Ainumbers Mcp Apps MCP server in PolicyLayer and add a rule for simulate_spend_policy: 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.

What risk level is simulate_spend_policy? +

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

Can I rate-limit simulate_spend_policy? +

Yes. Add a rate_limit block to the simulate_spend_policy 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 simulate_spend_policy completely? +

Set action: deny in the PolicyLayer policy for simulate_spend_policy. 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 simulate_spend_policy? +

simulate_spend_policy 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.

KEEP EXPLORING

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