How fast are Groq's chat completions compared to standard GPUs?

Groq's LPU architecture is designed for extreme low-latency inference, often delivering hundreds of tokens per second. Your agent uses the 'chat' tool to execute these blazing-fast requests, returning AI responses almost instantly.

Can my agent transcribe long audio files using Groq Whisper?

Yes. Use the 'transcribe' tool. Provide the public URL of your audio file and select a Whisper model (e.g., 'whisper-large-v3'). The agent will parse the stream and return the full text transcript flawlessly.

How do I ensure the AI response is formatted as valid JSON via chat?

Use the 'chat_json' tool. This activates Groq's JSON mode, which explicitly constrains the text inference to rigid, valid JSON formatting, making it perfect for direct system integrations.

Groq MCP Server for OpenAI Agents SDK 8 tools — connect in under 2 minutes

Name: Groq
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 8 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Groq through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

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

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Groq Assistant",
            instructions=(
                "You help users interact with Groq. "
                "You have access to 8 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Groq"
        )
        print(result.final_output)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Groq MCP Server

Connect your Groq account to any AI agent and take full control of your high-speed generative AI inference and LPU-accelerated LLM workflows through natural conversation.

The OpenAI Agents SDK auto-discovers all 8 tools from Groq through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Groq, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

What you can do

LPU Chat Orchestration — Execute blazing-fast text generation against hardware-accelerated Groq endpoints, utilizing Llama 3, Mixtral, and more flawlessly
Intelligent Audio Transcription — Parse audio streams into high-accuracy language transcripts utilizing hardware-optimized Whisper models natively
Cross-Lingual Translation — Evaluate non-English audio files and retrieve immediate translations exclusively into English text synchronousy
Structured JSON Mode — Constrain AI text inference explicitly to rigid valid JSON formatting to automate data population and system integrations flawlessly
Tool & Function Calling — Bind external definitions resolving explicit function call JSON architectures to enable your AI agents to interact with tools securely
Model Discovery — Enumerate available high-speed models and retrieve specific model IDs and versions for precise active inference boundaries natively
Inference Auditing — Monitor model capabilities and metadata properties to ensure your AI agents are utilizing the most efficient architectural instances synchronousy

The Groq MCP Server exposes 8 tools through the Vinkius. Connect it to OpenAI Agents SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Groq to OpenAI Agents SDK via MCP

Follow these steps to integrate the Groq MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 8 tools from Groq

Why Use OpenAI Agents SDK with the Groq MCP Server

OpenAI Agents SDK provides unique advantages when paired with Groq through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Groq + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Groq MCP Server delivers measurable value.

Automated workflows: build agents that query Groq, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries Groq, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Groq tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Groq to resolve tickets, look up records, and update statuses without human intervention

Groq MCP Tools for OpenAI Agents SDK (8)

These 8 tools become available when you connect Groq to OpenAI Agents SDK via MCP:

chat_completion

Supports Llama, Mixtral, Gemma models. Generate a chat completion with ultra-fast inference

create_embedding

Create text embeddings

get_model

Get model details

list_models

List available models

moderate_content

Check content for safety

structured_output

Generate structured JSON output

transcribe_audio

Transcribe audio to text

translate_audio

Translate audio to English text

Example Prompts for Groq in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Groq immediately.

"Ask llama3-70b: 'Write a python function to scrape a website.'"

"Transcribe this audio meeting: https://example.com/meeting.mp3"

"Get model info for 'mixtral-8x7b-32768'"

Troubleshooting Groq MCP Server with OpenAI Agents SDK

Common issues when connecting Groq to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Groq + OpenAI Agents SDK FAQ

Common questions about integrating Groq MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.