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 Pydantic AI 10 tools — connect in under 2 minutes

Name: OpenAI
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect OpenAI through the Vinkius and every tool is automatically validated against Pydantic schemas — catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

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

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to OpenAI "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in OpenAI?"
    )
    print(result.data)

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 OpenAI MCP Server

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

Pydantic AI validates every OpenAI tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code — full type safety, structured output guarantees, and dependency injection for testable agents.

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 Pydantic AI 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 Pydantic AI via MCP

Follow these steps to integrate the OpenAI MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 10 tools from OpenAI with type-safe schemas

Why Use Pydantic AI with the OpenAI MCP Server

Pydantic AI provides unique advantages when paired with OpenAI through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture — switch between OpenAI, Anthropic, or Gemini without changing your OpenAI integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your OpenAI connection logic from agent behavior for testable, maintainable code

OpenAI + Pydantic AI Use Cases

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

Type-safe data pipelines: query OpenAI with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple OpenAI tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query OpenAI and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock OpenAI responses and write comprehensive agent tests

OpenAI MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect OpenAI to Pydantic AI 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 Pydantic AI

Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI

Common issues when connecting OpenAI to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

OpenAI + Pydantic AI FAQ

Common questions about integrating OpenAI MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer — your OpenAI MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.