Lovo AI (Genny) MCP for AI. Generate professional audio from text in a conversation.

Q: How do I find the right voice using Lovo AI (Genny TTS & Voice Synthesis API)?

Run listvoices first. This gives you a full catalog. If you narrow down a speaker, use getspeaker to verify its specific capabilities and tones before committing.

Q: Can I change the voice after running createttsjob?

No, you can't edit a job in progress. You have to run createttsjob again with the new speaker ID and updated text.

Q: How do I make sure my agent uses American English voices?

Use listvoices and filter by language or check a specific voice's metadata using getspeaker. This confirms regional support before generating content.

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

How this MCP server connects to your AI agent

Lovo AI (Genny TTS & Voice Synthesis API) connects text to lifelike speech. Your agent uses this server to generate high-quality, controllable voiceovers for videos, podcasts, or ad copy using hundreds of premium voices and granular style controls.

What AI agents can do with Lovo AI (Genny TTS & Voice Synthesis API) Automation

Create tts job

Submits a text-to-speech synthesis job, returning a unique Job ID.

Get tts job

Checks the status of a previously submitted job using its Job ID, providing the final audio link when done.

Get speaker

Retrieves detailed metadata for one specific voice ID to check its capabilities and parameters.

+ 1 more capabilities included

Discover available voices

Run list_voices to get a catalog of all available AI speakers, filtering by language or gender.

Check voice details

Use get_speaker to pull deep metadata on a specific speaker ID so you can nail the perfect tone for your content.

Create audio files

Run create_tts_job to submit text and parameters (like speed or emotional style) and get an active Job ID back.

Track job status

Use get_tts_job with a Job ID. This tells you if the audio is still processing, failed, or ready to download.

Ask an AI about this

Included with Plan

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AI Agent

What AI agents can do with Lovo AI (Genny) TTS & Voice Synthesis API: 4 Tools

Manage the entire text-to-speech lifecycle—from listing voices to submitting jobs and retrieving final audio links.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Lovo AI (Genny TTS & Voice Synthesis API) on Vinkius

Create Tts Job

Submits a text-to-speech synthesis job, returning a unique Job ID.

Get Tts Job

Checks the status of a previously submitted job using its Job ID, providing the...

Get Speaker

Retrieves detailed metadata for one specific voice ID to check its capabilities and...

List Voices

Provides an exhaustive list of all available voice profiles, allowing filtering by...

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Claude AI

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

Start a conversation

Open a new chat. The Lovo AI (Genny) integration is available immediately — no restart needed.

Antigravity

Configure Agent Environment

Open your Antigravity agent's workspace configuration or mcp-servers.json file.

Bind the Endpoint

Add the Vinkius endpoint URL to your agent's MCP connections list:

"mcp_servers": {
  "lovo-ai-genny-tts-voice-synthesis-api": {
    "serverUrl": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
  }
}

Provide your secure token in place of [YOUR_TOKEN_HERE] to ensure your agent requests are authenticated.

Execute

Start your Antigravity session. The agent will autonomously discover and utilize the Lovo AI (Genny) tools with full Vinkius guardrails applied.

VS Code Copilot

⚡

One-Click Install (Recommended)

In your Vinkius Dashboard, simply click the Add to VS Code button for this server. We'll automatically configure your local workspace.

Or configure manually

Open MCP Settings

Open VS Code, press Ctrl/Cmd + Shift + P, and search for GitHub Copilot: MCP Servers.

Add Server Config

Add the Vinkius endpoint configuration to your mcp-servers.json file:

"lovo-ai-genny-tts-voice-synthesis-api": {
  "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}

Ensure you replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.

LangChain

Install Dependencies

Install the LangChain MCP adapters for your environment:

pip install langchain-mcp-adapters

Connect the Server

Use the SSEClient in LangChain to connect to the Vinkius managed endpoint:

from langchain_mcp_adapters.client import SSEClient

# Connect to Vinkius
client = SSEClient(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
tools = client.get_tools()

CrewAI

Define the Tool

Load the Vinkius MCP tools into your CrewAI agents:

from crewai import Agent
from mcp_crewai import MCPTool

# Connect securely to Vinkius
vinkius_tools = MCPTool(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

# Assign to Agent
researcher = Agent(
    role='Data Researcher',
    tools=vinkius_tools.get_all()
)

Execute Task

Run your CrewAI process. The agent will autonomously route tasks to the Vinkius managed server.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

Import from OpenAPI, Swagger, or YAML specs
Create Agent Skills with progressive disclosure
Deploy to edge with MCPFusion framework
Built in DLP, auth, and compliance on every call
Real time usage dashboard and cost metering
Publish to catalog or keep private

Start building

Make Your AI Do More

Start with Lovo AI (Genny TTS & Voice Synthesis API), then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.

Use this MCP plus 5,100+ others, all in one place
Add new capabilities to your AI anytime you want
Every connection is secured and compliant automatically
Track usage and costs across all your servers
Works with Claude, ChatGPT, Cursor, and more
New servers added to the catalog every week

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Lovo AI. 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.

VINKIUS INFRASTRUCTURE

Cloud Hosted

Managed infra

V8 Isolated

Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on every call

GDPR Compliant

EU data residency

Token Compression

~60% cost reduction

Your data is protected. See how we built it.

Built on the Model Context Protocol (MCP) for Claude, ChatGPT, Cursor, and more

The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.

This connection provides 4 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.

Turning scripts into audio used to mean jumping between three different tools., Solved with Vinkius AI Gateway

Before having an agent handle this, you'd write your script in one app, export it to a document, copy the text into a TTS website, and then download the resulting MP3. If you needed ten versions, that was ten sets of copy-pasting and downloading.

Now, you just give your agent the text and say, 'Use this voice for this script.' The server handles everything: it pulls the right speaker details, runs `create_tts_job`, and keeps running `get_tts_job` until the final URL is ready. You get audio output without ever leaving your chat window.

Lovo AI (Genny) TTS & Voice Synthesis API MCP Server: Create professional voiceovers.

You don't have to manually switch between 'list voices,' then 'create job,' and finally checking a status dashboard. All the state management—the IDs, the waiting period, the final retrieval—happens automatically through your agent using these tools.

The result is predictable, high-fidelity audio output that matches complex emotional requirements (like 'sad' or 'professional'). It’s a finished product, not just a raw data stream.

Support 24/7 support@vinkius.com ↗

Security Vinkius Trust Center ↗

SLA Service Level Agreement ↗

Report Listing Send Report ↗

text-to-speech

voice-synthesis

ai-audio

genny

lovo-ai

What your AI can actually do with this

Lovo AI (Genny) TTS Server - Voice Synthesis API lets your agent transform plain text into lifelike speech. You'll use this server to generate high-quality, controllable voiceovers for anything—videos, podcasts, or ad copy—by leveraging hundreds of premium voices and granular style controls.

To get started, you first need a handle on what's available. Run list_voices if you wanna see an exhaustive catalog of all the AI speakers we got going. You can filter this massive list by language or gender to narrow down your search immediately.

Once you know which voices exist, you gotta pick the right one. Use get_speaker when you want deep metadata on a specific speaker ID. This pulls detailed information about that voice's capabilities and parameters; it's how you nail the perfect tone for your content before committing to an audio file.

When you're ready, you submit the actual text using create_tts_job. You pass in the source material along with specific synthesis parameters—things like desired speed or emotional style. This job submission doesn't give you the audio; it gives you a unique Job ID. Keep that ID safe because you need it next.

Because generating high-quality speech takes time, you don't get the file right away. You gotta use get_tts_job with your saved Job ID. This function checks the status of the job—it tells you if the audio is still processing in the background, if something failed and needs a retry, or if it’s finally ready for download.

The whole process flows like this: first, run list_voices to browse the field; next, use get_speaker on that ID to fine-tune your requirements; then, feed everything into create_tts_job; and last, monitor the outcome with get_tts_job. You're managing the entire voice production pipeline conversationally through your agent.

For instance, if you need a very specific sound—say, an upbeat corporate announcer in Mandarin—you first run list_voices to find available profiles. Then, you pull up that profile using get_speaker so you can confirm its emotional range and what kind of stylistic controls it supports. Once confirmed, you submit your script via create_tts_job, making sure you set the speed parameter precisely how you want it, along with any required emotional style tags.

The API returns a Job ID immediately. You'll then keep hitting get_tts_job until that status field flips from 'PROCESSING' to 'COMPLETED,' giving your agent the final link to download the finished audio file.

Built · Hosted · Managed by Vinkius Lovo AI (Genny) TTS Server - Voice Synthesis API

Server ID 019e5d31-3dbc-7240-a7c4-34c8377cbc21

Vinkius Inspector

Compliance Grade A+

Score 100/100

Report View Report ↗

Here's how it actually works

The bottom line is: you tell your agent what to say, which voice to use, and when the job's done, all through simple API calls.

First, run list_voices to browse and select the voice you want.

Next, use your agent to call create_tts_job, supplying the text, speaker ID, and desired emotional style.

Finally, wait a minute or two, then check status using get_tts_job until it confirms the final audio URL is available.

Who is this actually for?

Content creators who need video narrations fast. Developers integrating high-fidelity speech into apps without manual work. Marketers needing localized audio for ad campaigns. If your workflow involves turning scripts into broadcast-ready audio, you're here.

Video Editor

Needs to add professional narration to a script quickly. They use the server to run create_tts_job for voiceover tracks.

Developer

Integrates speech synthesis into an application's backend. They rely on the full cycle: list_voices -> get_speaker -> create_tts_job.

Marketing Copywriter

Needs to generate localized audio for social media ads. They run jobs and use get_tts_job to confirm the final output URL is ready for review.

What Changes When You Connect

You don't just get generic audio. By checking the speaker details with get_speaker, you ensure the voice has the precise tone (e.g., cheerful, sad) needed for your script.

The process is controlled. You initiate jobs using create_tts_job and then use get_tts_job to track it until the final audio URL appears—no guessing games here.

It gives you full voice control. Use list_voices to browse hundreds of premium speakers, letting you select exactly the language or style your content needs.

You bypass manual file management. Everything happens in a single flow: send text, get ID, poll status. Your agent handles the whole queue.

It works across platforms. You can generate video narrations for podcasts or ad copy directly from your script-writing interface via any MCP client.

See it in action

01 01

Building a multilingual podcast series

The user needs five versions of a script in different languages. Instead of manual API calls, they ask their agent to first run list_voices to confirm all necessary language packs are available. Then, the agent loops through and runs create_tts_job for each version, managing multiple jobs concurrently.

02 02

Automating ad copy generation

A marketing team needs 20 different audio versions of an ad script using a professional male voice. They run the text through create_tts_job and then continuously poll status using get_tts_job, getting confirmation when all 20 assets are ready for download.

03 03

Creating character dialogue for a game

A developer needs to ensure the voice used for the 'villain' NPC has an overly dramatic tone. They first call get_speaker using the villain's ID to verify its emotional range, then use that data when calling create_tts_job.

04 04

Verifying speech options before committing

Before submitting a massive job, the user wants to know which voices are available in Mandarin. They start by running list_voices, filtering strictly for that language, preventing them from selecting an unsupported profile.

The honest tradeoffs

Treating it like a single API call

Anti-pattern

Calling create_tts_job once and then expecting the audio file immediately. The job needs time to process, or you'll just get an error.

The Fix

You gotta run three steps: 1) Use create_tts_job. 2) Wait a moment. 3) Run get_tts_job repeatedly until the status is 'complete'. This sequence works.

Using generic voice parameters

Anti-pattern

Just picking a speaker ID and running text, hoping for the right tone. You might end up with something that sounds flat or wrong.

The Fix

Always run get_speaker first to pull deep metadata on the desired voice profile. That ensures you know exactly which emotional styles (like 'cheerful' vs. 'professional') are supported before running create_tts_job.

Assuming job IDs persist

Anti-pattern

If you lose the Job ID after submitting a task, you can't check on it later. The whole process stalls.

The Fix

Make sure your agent captures and stores the Job ID returned by create_tts_job. You need that specific ID to run get_tts_job successfully.

When It Fits, When It Doesn't

Use this server if your primary goal is converting text into high-quality, controllable audio files. The core workflow requires three steps: discovery (list_voices/get_speaker), creation (create_tts_job), and polling (get_tts_job). Don't use it if you need to edit the source text after creating a job—you have to restart the whole thing. Also, don't rely on this for complex phonetic corrections; it handles general style and tone changes, but extreme linguistic nuance might require human review.

It’s perfect when your workflow is: 'Here's my script -> Pick a voice -> Make audio.' It fails if the process needs to be non-linear or highly stateful beyond simple status checking. Keep it for the repeatable, text-to-speech pipeline.

Questions you might have

How do I find the right voice using Lovo AI (Genny TTS & Voice Synthesis API)? +

Run list_voices first. This gives you a full catalog. If you narrow down a speaker, use get_speaker to verify its specific capabilities and tones before committing.

What happens if my TTS job fails after using create_tts_job? +

The server will return an error code or status message. You'll need to review the error details provided by get_tts_job and adjust your source text or parameters.

Can I change the voice after running create_tts_job? +

No, you can't edit a job in progress. You have to run create_tts_job again with the new speaker ID and updated text.

How do I make sure my agent uses American English voices? +

Use list_voices and filter by language or check a specific voice's metadata using get_speaker. This confirms regional support before generating content.

What do I need to provide when using the `create_tts_job` tool? +

You must supply your Lovo Genny API Key for the agent to connect. This key authenticates all requests, allowing the system to process the text-to-speech job and assign a unique Job ID.

How do I check if my audio file is ready after calling `get_tts_job`? +

The response status will change from 'Processing' to 'Complete.' Once marked complete, the tool returns a direct URL. You use this link to access and download your finalized audio asset.

Are there rate limits when running multiple jobs using `create_tts_job`? +

Yes, Lovo AI enforces usage caps on job submissions. If you exceed the allowed volume, your agent will receive an error code (429). You'll need to pause and wait for the quota to reset.

What specific metadata can I retrieve using the `get_speaker` tool? +

You get more than just a name. The tool returns detailed specs like supported emotional styles, language codes, and pitch ranges. This data helps your agent choose the perfect speaker for niche content.

How can I find the right voice ID for my project? +

Use the list_voices tool. It returns a comprehensive list of speakers including their IDs, names, and supported styles. You can then use get_speaker with a specific ID to see more detailed information.

Can I adjust the emotion or speed of the generated voice? +

Yes! When using create_tts_job, you can provide an optional speed (number) and style (e.g., 'cheerful', 'sad', 'normal') to customize the output to your needs.

How do I get the final audio file once the job is submitted? +

After creating a job, use the get_tts_job tool with the returned Job ID. Once the status is 'completed', the response will include the URLs to download your synthesized audio.

How this MCP server connects to your AI agent

Lovo AI (Genny TTS & Voice Synthesis API) connects text to lifelike speech. Your agent uses this server to generate high-quality, controllable voiceovers for videos, podcasts, or ad copy using hundreds of premium voices and granular style controls.

What AI agents can do with Lovo AI (Genny TTS & Voice Synthesis API) Automation

Create tts job

Get tts job

Get speaker

What AI agents can do with Lovo AI (Genny) TTS & Voice Synthesis API: 4 Tools

Create Tts Job

Submits a text-to-speech synthesis job, returning a unique Job ID.

Get Tts Job

Checks the status of a previously submitted job using its Job ID, providing the...

Get Speaker

Retrieves detailed metadata for one specific voice ID to check its capabilities and...

List Voices

Provides an exhaustive list of all available voice profiles, allowing filtering by...

Security and governance baked right in.

Claude AI

Open Claude Settings

Add Custom Connector

Start a conversation

Claude Code

Open your terminal

Add the MCP Server

Start coding

Cursor

One-Click Install (Recommended)

Open Cursor Settings

Add New Server

Use in Composer

Antigravity

Configure Agent Environment

Bind the Endpoint

Execute

VS Code Copilot

One-Click Install (Recommended)

Open MCP Settings

Add Server Config

Windsurf

One-Click Install (Recommended)

Open Windsurf Settings

Add Server Endpoint

LangChain

Install Dependencies

Connect the Server

CrewAI

Define the Tool

Execute Task

Choose How to Get Started

Build Your Own

Make Your AI Do More

Built on the Model Context Protocol (MCP) for Claude, ChatGPT, Cursor, and more

Turning scripts into audio used to mean jumping between three different tools., Solved with Vinkius AI Gateway

Lovo AI (Genny) TTS & Voice Synthesis API MCP Server: Create professional voiceovers.

text-to-speech

voice-synthesis

ai-audio

genny

lovo-ai

What your AI can actually do with this

Here's how it actually works

Who is this actually for?

What Changes When You Connect

Building a multilingual podcast series

Automating ad copy generation

Creating character dialogue for a game

Verifying speech options before committing

The honest tradeoffs

Treating it like a single API call

Using generic voice parameters

Assuming job IDs persist

When It Fits, When It Doesn't

Questions you might have