Which models can I use?

Any model available on your API key: GPT-4o, GPT-4o-mini, GPT-4-turbo, o1, o3 — use `list_models` to see all.

Can I generate images?

Yes! Use `generate_image` with a text prompt. Supports 1024x1024, 1792x1024, and 1024x1792 sizes.

How does content moderation work?

The `moderate_content` tool analyzes text against OpenAI's content policy, flagging categories like hate, violence, and self-harm with confidence scores.

OpenAI MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: OpenAI
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="OpenAI Specialist",
    goal="Help users interact with OpenAI effectively",
    backstory=(
        "You are an expert at leveraging OpenAI 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 OpenAI "
        "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 OpenAI MCP Server

Connect the OpenAI API to any AI agent and unlock the full power of GPT models as composable tools.

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

What you can do

Chat Completions — Generate responses from GPT-4o, GPT-4o-mini, and other models
Image Generation — Create images with DALL-E 3 from text descriptions
Embeddings — Convert text to vector representations for semantic search
Content Moderation — Check text for policy violations automatically
Fine-tuning — Create and monitor custom model training jobs
File Management — List uploaded files for training and assistants
Assistants — Browse configured OpenAI Assistants
Structured Output — Generate structured JSON responses from prompts

The OpenAI 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.

How to Connect OpenAI to CrewAI via MCP

Follow these steps to integrate the OpenAI MCP Server with CrewAI.

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 OpenAI

Why Use CrewAI with the OpenAI MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with OpenAI 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 the 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

OpenAI + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries OpenAI 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 OpenAI, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain OpenAI 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 OpenAI against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

OpenAI MCP Tools for CrewAI (10)

These 10 tools become available when you connect OpenAI to CrewAI via MCP:

chat_completion

Specify model (gpt-4o, gpt-4o-mini, etc.) and messages array as JSON. Generate a chat completion using OpenAI models

create_embedding

Create text embeddings

create_fine_tune

Requires a previously uploaded JSONL training file ID. Create a fine-tuning job

generate_image

Returns the image URL. Generate an image with DALL-E 3

list_assistants

List OpenAI Assistants

list_files

List uploaded files

list_fine_tunes

List fine-tuning jobs

list_models

List available OpenAI models

moderate_content

Check content for policy violations

structured_output

Provide a system prompt and user message. Generate structured JSON output from a prompt

Example Prompts for OpenAI in CrewAI

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

"Ask GPT-4o to summarize this document in 3 bullet points."

"Generate an image of a futuristic cityscape at sunset."

"Check if this text violates content policies."

Troubleshooting OpenAI MCP Server with CrewAI

Common issues when connecting OpenAI 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

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

OpenAI + CrewAI FAQ

Common questions about integrating OpenAI 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.