How to Use the Cradl AI MCP in OpenAI Agents SDK

Q: Can OpenAI Agents SDK handle Cradl AI batch processing?

Yes. Use listbatches and getbatchdetails to manage large document volumes. Your agent can process and report on batches without leaving your Python environment.

Plug Cradl AI into your OpenAI Agents SDK production pipeline to automate document extraction with strict guardrails.

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Connect Cradl AI MCP to OpenAI Agents SDK

Create your Vinkius account to connect Cradl AI to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Cradl AI with OpenAI Agents SDK

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Automate document extraction via OpenAI Agents SDK

Your agent triggers `extract_data_from_url` to feed raw files into Cradl AI. It handles the OCR and data normalization without manual intervention. This MCP Server keeps your agent focused on logic. The system handles the heavy lifting of parsing complex documents into structured JSON.

Monitor extraction tasks in OpenAI Agents SDK

Use `list_processing_tasks` to track document status in real time. Your agent verifies successful completion before moving data into your database. `get_task_status` pulls confidence scores directly into your agent's context. You get clear visibility into every extraction result.

Manage extraction models with OpenAI Agents SDK

Query your model library using `list_extraction_models` to pick the right tool for the job. Your agent identifies the correct schema for any document type. `get_model_details` lets the agent check accuracy metrics before starting a task. You keep your production flows tight and predictable.

Setup guide

Set up Cradl AI MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Cradl AI tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Cradl AI tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Cradl AI tools and returns structured results. Copy the full example on the right to get started.

agent.py

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

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="Cradl AI Agent",
            instructions="You have access to Cradl AI tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Cradl AI. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Cradl AI MCP in OpenAI Agents SDK

Install the necessary packages and instantiate the MCPServerStreamableHttp class. Pass your server URL to the Agent constructor to let your agent discover all ten available tools.

Yes. Use `list_batches` and `get_batch_details` to manage large document volumes. Your agent can process and report on batches without leaving your Python environment.

It does. You can wrap tool calls in your agent's validation logic. This ensures the data returned by Cradl AI meets your specific schema requirements before the agent proceeds.

You can define which tools the agent sees during the initialization phase. Simply omit any tool names you don't want the agent to call.

Cradl AI processes document images and OCR text within a secure environment. We isolate your sensitive data during the extraction phase and never store raw files longer than your configured retention policy.

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