How to Use the ElevenLabs MCP in OpenAI Agents SDK

Q: How do I monitor character limits for ElevenLabs in OpenAI Agents SDK?

Call the getsubscription tool directly from your agent code. This returns your current quota status so you can set up logic to halt generation before you exceed your monthly budget.

Q: Can OpenAI Agents SDK automatically select the best voice?

Yes, use listvoices to pull the available catalog into your agent's context. You can then write a logic block to choose the specific voice ID that matches your desired persona.

Q: Does ElevenLabs support custom pronunciations for OpenAI Agents SDK?

Absolutely. You can call listpronunciationdictionaries to see what is available. Pass these to your generation calls to ensure your agent handles domain-specific jargon correctly.

Q: How do I handle audio latency in my agent?

Test different models using listmodels to find the balance between speed and quality. Smaller models often generate faster, which helps keep your conversation flow snappy.

Integrate ElevenLabs into your OpenAI Agents SDK workflow to generate lifelike audio and manage voice assets directly from your agent.

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…and any MCP-compatible client

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Connect ElevenLabs MCP to OpenAI Agents SDK

Create your Vinkius account to connect ElevenLabs to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup ElevenLabs with OpenAI Agents SDK

Ask AI about this MCP

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Claude

Perplexity

Generate production-grade audio

Feed your text into `text_to_speech` to output high-fidelity audio streams. Your agent handles the conversion process without leaving the Python environment. Specify the exact model via `list_models` to match your latency requirements. This keeps your agent responsive while maintaining top-tier voice quality.

Manage voice and subscription state

Query `get_subscription` and `get_user_info` to keep tabs on your API character usage in real-time. Don't let your agent hit a hard wall mid-conversation. Retrieve specific voice profiles using `list_voices` or `get_voice` to ensure brand consistency. Your agent selects the right tone every time based on your configuration.

Track generation history

Access past audio outputs through `list_history` and `get_history_item` for debugging or caching purposes. It provides a clear audit trail of every generation task. Use `list_projects` to coordinate long-form dubbing tasks. Your agent remains in control of the entire production pipeline with these tools.

Setup guide

Set up ElevenLabs MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all ElevenLabs tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives ElevenLabs tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate ElevenLabs tools and returns structured results. Copy the full example on the right to get started.

agent.py

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="ElevenLabs Agent",
            instructions="You have access to ElevenLabs tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by ElevenLabs. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about ElevenLabs MCP in OpenAI Agents SDK

Call the `get_subscription` tool directly from your agent code. This returns your current quota status so you can set up logic to halt generation before you exceed your monthly budget.

Yes, use `list_voices` to pull the available catalog into your agent's context. You can then write a logic block to choose the specific voice ID that matches your desired persona.

Absolutely. You can call `list_pronunciation_dictionaries` to see what is available. Pass these to your generation calls to ensure your agent handles domain-specific jargon correctly.

Test different models using `list_models` to find the balance between speed and quality. Smaller models often generate faster, which helps keep your conversation flow snappy.

The server only provides metadata and access to your ElevenLabs history. Your audio data remains protected under your ElevenLabs account security protocols, and your agent only interacts with the API through authenticated tokens.

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