util_token_raw_to_amount

Scale raw token units by decimals into human-readable amounts

SERVERDelx Mcp A2a SOURCEhttps://api.delx.ai/v1/mcp

High RISK CLASS

Category Execute

Parameters 22 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-davidmosiah-delx-mcp-a2a/util-token-raw-to-amount.md

WHAT IT DOES

What util_token_raw_to_amount does on Delx Mcp A2a

AI agents invoke util_token_raw_to_amount to trigger actions in Delx Mcp A2a. 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
`raw`	string	Yes	Input field: raw.
`decimals`	integer	Yes	Input field: decimals.

Parameters from the server's own tool schema.

RISK

Why util_token_raw_to_amount is rated High

util_token_raw_to_amount triggers real processes with real consequences. An agent gone sideways doesn't fire it once. It starts dozens of builds, sends mass notifications, or burns through compute before anyone looks up.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs util_token_raw_to_amount safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Delx Mcp A2a, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For util_token_raw_to_amount, this is the rule to start with:

util_token_raw_to_amount Rate-limited

util_token_raw_to_amount 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": {
    "util_token_raw_to_amount": {
      "limits": [
        {
          "counter": "util_token_raw_to_amount_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 Delx Mcp A2a, apply this rule, and every util_token_raw_to_amount call is checked against it from then on.

FAQ

Questions about util_token_raw_to_amount

What does the util_token_raw_to_amount tool do? +

Scale raw token units by decimals into human-readable amounts. It is categorised as a Execute tool in the Delx Mcp A2a MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

What parameters does util_token_raw_to_amount accept? +

util_token_raw_to_amount accepts 2 parameters: raw, decimals. Required: raw, decimals. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on util_token_raw_to_amount? +

Register the Delx Mcp A2a MCP server in PolicyLayer and add a rule for util_token_raw_to_amount: 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 Delx Mcp A2a. Nothing to install.

What risk level is util_token_raw_to_amount? +

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

Can I rate-limit util_token_raw_to_amount? +

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

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

util_token_raw_to_amount is provided by the Delx Mcp A2a MCP server (https://api.delx.ai/v1/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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