Can my agent run image predictions using custom models?

Yes. Provide the User ID, App ID, and Model ID, along with the input JSON (containing image URLs or bytes). The agent calls Clarifai's predict API and returns exactly what the AI detected, from tags to bounding boxes.

How can I audit the datasets being used in my Clarifai app?

Ask your agent to list datasets for a specific app. It returns the precise physical bounds mapping the image sets, helping you ensure that your training loop is using the correct data boundaries.

Can I see all active workflows in my organization?

Absolutely. Use the 'list_workflows' tool. Your agent will pull the chained AI limits, showing you composed computational blocks that tie multiple neural networks together for complex visual tasks.

Clarifai (Vision AI) MCP Server for OpenAI Agents SDK 6 tools — connect in under 2 minutes

Name: Clarifai (Vision AI)
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 6 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Clarifai (Vision AI) through 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="Clarifai (Vision AI) Assistant",
            instructions=(
                "You help users interact with Clarifai (Vision AI). "
                "You have access to 6 tools."
            ),
            mcp_servers=[mcp_server],
        )

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

asyncio.run(main())

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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 Clarifai (Vision AI) MCP Server

Connect your Clarifai account to any AI agent and take full control of your computer vision and AI workflows through natural conversation.

The OpenAI Agents SDK auto-discovers all 6 tools from Clarifai (Vision AI) through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Clarifai (Vision AI), another analyzes results, and a third generates reports, all orchestrated through Vinkius.

What you can do

AI Inference (Predictions) — Dispatch automated validation inferences and parse exactly what the neural networks evaluated
App & Model Management — List Clarifai apps and models to organize and audit your compute environments
Chained Workflows — Retrieve composed computational blocks that tie multiple models together for complex AI tasks
Datasets & Concepts — Identify data structures used for training and audit the textual concepts tagging your visual data
Identity Mapping — Navigate users and apps to isolate your AI logic across different execution contexts

The Clarifai (Vision AI) MCP Server exposes 6 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 Clarifai (Vision AI) to OpenAI Agents SDK via MCP

Follow these steps to integrate the Clarifai (Vision AI) 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 6 tools from Clarifai (Vision AI)

Why Use OpenAI Agents SDK with the Clarifai (Vision AI) MCP Server

OpenAI Agents SDK provides unique advantages when paired with Clarifai (Vision AI) 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

Clarifai (Vision AI) + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Clarifai (Vision AI) MCP Server delivers measurable value.

Automated workflows: build agents that query Clarifai (Vision AI), process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries Clarifai (Vision AI), another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Clarifai (Vision AI) tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Clarifai (Vision AI) to resolve tickets, look up records, and update statuses without human intervention

Clarifai (Vision AI) MCP Tools for OpenAI Agents SDK (6)

These 6 tools become available when you connect Clarifai (Vision AI) to OpenAI Agents SDK via MCP:

list_apps

Identify bounded Clarifai apps managing global compute limits

list_concepts

Extracts explicitly attached semantic bounds tagging datasets matching limits

list_datasets

Identify precise physical bounds mapping data structures resolving visual nodes

list_models

Perform structural extraction of computer vision parameters driving AI features

list_workflows

Retrieve the exact structural matching verifying chained AI limits

predict_model

/models/{model_id}/outputs` parsing exactly what the AI limit evaluated bounding image classifications. Dispatch an automated validation inference routing explicit network predictions

Example Prompts for Clarifai (Vision AI) in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Clarifai (Vision AI) immediately.

"List all my Clarifai apps for user 'user_123'"

"Predict using model 'general-v2' in app 'General-Vision' with image URL 'https://example.com/photo.jpg'"

"What datasets are available in the 'Custom-Trainer' app?"

Troubleshooting Clarifai (Vision AI) MCP Server with OpenAI Agents SDK

Common issues when connecting Clarifai (Vision AI) 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.

Clarifai (Vision AI) + OpenAI Agents SDK FAQ

Common questions about integrating Clarifai (Vision AI) 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.