How do I get a Groq API Key?

Log in to your [**Groq Cloud account**](https://console.groq.com/), navigate to the **API Keys** section, and click **Create API Key**.

Which models provide the best performance?

Models like `llama-3.3-70b-versatile` and `mixtral-8x7b-32768` provide an excellent balance of high-fidelity reasoning and speed on Groq.

Can I use Groq for code generation?

Yes! Use the `generate_code` and `explain_code` tools to ask the models to write snippets or provide step-by-step logic explanations.

INSTANT PLUG AND PLAY

Groq MCP Server for CrewAIGive CrewAI instant access to 10 tools to Analyze Sentiment, Create Chat Completion, Explain Code, and more

Name: Groq
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to Groq through Vinkius, pass the Edge URL in the `mcps` parameter and every Groq tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The Groq app connector for CrewAI is a standout in the Ai Frontier category — giving your AI agent 10 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Groq Specialist",
    goal="Help users interact with Groq effectively",
    backstory=(
        "You are an expert at leveraging Groq tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Groq "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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* 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 Cloud account to any AI agent and leverage the incredible speed of LPU™ (Language Processing Unit) technology for real-time inference and content generation.

When paired with CrewAI, Groq becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Groq tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

What you can do

Chat Orchestration — Generate high-speed chat completions using state-of-the-art models like Llama 3.3 and Mixtral with sub-second latency
Model Intelligence — List all available high-performance models and retrieve detailed metadata regarding ownership and capabilities
Text Processing — Programmatically summarize long documents, analyze sentiment, and translate text between languages instantly
Developer Automation — Generate optimized code snippets, explain complex logic, and perform grammar correction through natural language
Entity Extraction — Identify and extract structured information (names, dates, locations) from unstructured text as JSON objects

The Groq MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 10 Groq tools available for CrewAI

When CrewAI connects to Groq through Vinkius, your AI agent gets direct access to every tool listed below — spanning llm-inference, lpu-hardware, real-time-ai, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

analyze_sentiment

Analyze sentiment of a text

create_chat_completion

Supports models like llama-3.3-70b-versatile. Generate a response using Groq LLM

explain_code

Explain how a code snippet works

extract_entities

Extract named entities from text

fix_grammar

Correct grammar and spelling errors

generate_code

Generate code snippets from natural language

get_model_details

Get metadata for a specific model

list_available_models

List all available high-performance models

summarize_text

Summarize long text using Llama 3

translate_text

Translate text between languages

Connect Groq to CrewAI via MCP

Follow these steps to wire Groq into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

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

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from Groq

Why Use CrewAI with the Groq MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Groq through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Groq + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Groq MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Groq for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Groq, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Groq tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Groq against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Groq in CrewAI

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

"Summarize this long technical document: [text]"

"Generate a Python script for real-time data visualization."

"Analyze the sentiment of this user feedback: 'The speed is amazing but the UI needs work'."

Troubleshooting Groq MCP Server with CrewAI

Common issues when connecting Groq to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Groq + CrewAI FAQ

Common questions about integrating Groq MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.