ofaudio-mcp

account_status

Check credits and quotas for all configured audio providers in one call, preventing mid-batch failures from exhausted credits or voice slots.

Instructions

Credits + quotas for ALL configured providers in one call — check before fan-out.

Returns a section per available provider (only those with a configured key):

"elevenlabs": tier, characters used/limit/remaining, voice slots, cloning entitlements, next quota reset, and "quality" (which audio formats this tier can request — lossless wav/pcm need Pro+, mp3_192 needs Creator+).
"mureka": prepaid credit balance, total recharge/spending, and concurrent_request_limit (=1 on the $30 tier — drives how many music jobs run at once).

Use it to avoid mid-batch failures (out of credits / voice slots) and to pick a supported audio format for the account's tier. A provider that errors is reported under its own key rather than failing the whole call.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "account_status"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 31, 2026

TDQS

A4.9/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description fully discloses behavior: it returns sections only for configured providers, details the fields per provider (tier, limits, quality), and explains error handling. This goes far beyond a simple 'get status' statement.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear opening sentence, then two bullet-like sections for each provider. Every sentence adds value, and the formatting improves scannability without being bloated.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no parameters, the description thoroughly covers return structure, per-provider details, and edge cases (providers with errors). It provides all needed context for an AI agent to understand what will be returned.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, so the baseline is 4. The description instead focuses on output semantics, which is appropriate. Since there are no parameters to document, this is effectively complete.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Credits + quotas for ALL configured providers in one call' with a specific verb (check) and resource (account status). It also distinguishes from siblings by emphasizing provider-wide coverage and pre-fan-out use.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit guidance is given: 'check before fan-out' and 'Use it to avoid mid-batch failures... and to pick a supported audio format.' It also clarifies that per-provider errors are isolated, which helps decide when to call this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.