How to Use the Lovo AI (Genny TTS & Voice Synthesis API) MCP in OpenAI Agents SDK

Q: Can OpenAI Agents SDK handle the latency of Lovo AI (Genny TTS & Voice Synthesis API)?

Yes. You can manage latency by using getttsjob to poll for completion asynchronously. This prevents your agent from blocking while waiting for the audio file to render.

Q: How are voice profiles managed in OpenAI Agents SDK?

You query the available options using listvoices. The agent stores these IDs in memory and selects the appropriate one for the current text generation task.

Turn text into high-fidelity audio directly within your OpenAI Agents SDK workflow.

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Connect Lovo AI (Genny TTS & Voice Synthesis API) MCP to OpenAI Agents SDK

Create your Vinkius account to connect Lovo AI (Genny TTS & Voice Synthesis API) 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 Lovo AI (Genny TTS & Voice Synthesis API) with OpenAI Agents SDK

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Claude

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Direct synthesis control

Your agent manages the entire audio lifecycle through `create_tts_job`. It submits text directly to the Genny engine and keeps your production pipeline moving without leaving the Python environment. Once the job starts, your agent monitors progress using `get_tts_job`. This ensures your safety guardrails track every audio output before it reaches the end user.

Programmatic voice selection

Stop guessing which voice fits your brand. Use `list_voices` to pull the current roster of available profiles into your agent's context for runtime decisions. Need technical specs on a specific narrator? Call `get_speaker` to retrieve metadata. Your agent now handles voice casting based on the specific requirements of the current task.

Production-ready MCP integration

The OpenAI Agents SDK automatically detects these tools. You just define the server connection and the agent maps the functions to its execution logic. Because this is an MCP server, your agent maintains a strict interface. It validates every call against the tool schema, keeping your synthesis jobs consistent across all deployments.

Setup guide

Set up Lovo AI (Genny TTS & Voice Synthesis API) 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 Lovo AI (Genny TTS & Voice Synthesis API) tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Lovo AI (Genny TTS & Voice Synthesis API) tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Lovo AI (Genny TTS & Voice Synthesis API) 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="Lovo AI (Genny TTS & Voice Synthesis API) Agent",
            instructions="You have access to Lovo AI (Genny TTS & Voice Synthesis API) tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Lovo AI (Genny TTS & Voice Synthesis API) MCP in OpenAI Agents SDK

Install the necessary dependencies and initialize the server via `MCPServerStreamableHttp`. Pass the server object into your agent constructor to enable auto-discovery of the synthesis tools.

Yes. You can manage latency by using `get_tts_job` to poll for completion asynchronously. This prevents your agent from blocking while waiting for the audio file to render.

It does. Since the tools are exposed via the standard protocol, your agent's built-in validation layer inspects every request to `create_tts_job` before it executes.

You query the available options using `list_voices`. The agent stores these IDs in memory and selects the appropriate one for the current text generation task.

The server operates in a zero-trust sandbox. It only processes the specific text strings you send for synthesis, ensuring no extraneous data leaves your agent's environment.

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