How to Use the Deepgram MCP in OpenAI Agents SDK

Control Deepgram audio processing directly within your OpenAI Agents SDK production pipeline.

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Connect Deepgram MCP to OpenAI Agents SDK

Create your Vinkius account to connect Deepgram 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 Deepgram with OpenAI Agents SDK

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Manage Deepgram keys in OpenAI Agents SDK

Handle your API credentials without leaving your Python environment. Use `create_key` and `list_keys` to provision access while keeping your security posture tight. You won't need to hop between browsers or dashboards. Your agent manages the lifecycle of your keys inside the OpenAI Agents SDK runtime.

Get Deepgram usage stats for OpenAI Agents SDK

Keep tabs on your spending by pulling real-time metrics. Use `get_balances` and `get_usage` to see exactly what your integration is costing you. These tools hook into your agent logic. You get visibility into your API consumption patterns without manual lookups.

Run Deepgram speech tools via OpenAI Agents SDK

Convert audio to text or generate speech on the fly. The `transcribe_url` and `speak_text` functions turn your agent into a functional audio engine. Your code handles the heavy lifting. This MCP Server lets your agent process files or generate responses based on the data you feed it.

Setup guide

Set up Deepgram 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 Deepgram tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Deepgram 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="Deepgram Agent",
            instructions="You have access to Deepgram tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

Get your connection token →

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

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

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Common questions about Deepgram MCP in OpenAI Agents SDK

Use the MCPServerStreamableHttp class to connect the server. Define your endpoint, pass the server to your agent constructor, and let the tools auto-discover.

Yes. Since you're using a production agent system, you can wrap the tool calls in your own error handling logic. This ensures your agent reacts safely if a transcription fails.

Absolutely. You can attach validation constraints to any tool call. If the agent tries to perform a suspicious action, the guardrail stops it before execution.

Deepgram processes your audio stream in memory. This MCP Server never persists your raw audio files or sensitive transcripts on Vinkius infrastructure.

The connection remains ephemeral. Your agent talks directly to the API, and we only handle the transport layer for your tool definitions.

Use it with your favorite AI tools

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