Cradl AI MCP Server for OpenAI Agents SDK 10 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Cradl AI through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="Cradl AI Assistant",
instructions=(
"You help users interact with Cradl AI. "
"You have access to 10 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Cradl AI"
)
print(result.final_output)
asyncio.run(main())
* 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 Cradl AI MCP Server
Integrate Cradl AI, the advanced document data extraction platform, directly into your AI workflow. Automate the processing of invoices, receipts, IDs, and custom forms using powerful deep learning models and natural language.
The OpenAI Agents SDK auto-discovers all 10 tools from Cradl AI through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Cradl AI, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Data Extraction — Trigger real-time data extraction from document URLs with high precision.
- Model Management — List and explore your custom-trained extraction models.
- Workflow Monitoring — Track the status of document processing flows and individual tasks.
- Batch Processing — Audit and retrieve details for entire batches of processed documents.
The Cradl AI MCP Server exposes 10 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 Cradl AI to OpenAI Agents SDK via MCP
Follow these steps to integrate the Cradl 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 10 tools from Cradl AI
Why Use OpenAI Agents SDK with the Cradl AI MCP Server
OpenAI Agents SDK provides unique advantages when paired with Cradl 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
Cradl AI + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Cradl AI MCP Server delivers measurable value.
Automated workflows: build agents that query Cradl AI, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries Cradl AI, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Cradl AI tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Cradl AI to resolve tickets, look up records, and update statuses without human intervention
Cradl AI MCP Tools for OpenAI Agents SDK (10)
These 10 tools become available when you connect Cradl AI to OpenAI Agents SDK via MCP:
extract_data_from_url
Touches OCR engine, model prediction, and data normalization boundary. Trigger a new data extraction prediction from a file URL
get_batch_details
Touches individual file statuses and batch-level processing summary boundaries. Get details for a specific batch of documents
get_flow_details
Touches integration points and document routing rules boundaries. Get structure and settings for a specific flow
get_model_details
Touches schema definitions, extraction accuracy metrics, and model metadata boundaries. Get details for a specific extraction model
get_task_status
Resolves confidence scores and extracted key-value pairs from the document. Check the status and results of a document task
list_batches
Resolves batch identifiers, creation dates, and total document counts within each batch. List all document batches
list_extraction_models
Resolves model names, versions, and training statuses for document analysis. List all data extraction models in Cradl AI
list_processing_tasks
Resolves task IDs, statuses (PENDING, COMPLETED, FAILED), and processing timestamps. List recent document processing tasks
list_workflows
Resolves flow IDs, triggers, and configured processing steps. List all document processing flows
search_models_by_name
Resolves model metadata based on a name keyword search. Search for extraction models by name
Example Prompts for Cradl AI in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Cradl AI immediately.
"Extract data from this invoice: https://example.com/inv123.pdf using my 'Invoice Parser' model."
"Check the status of document processing task 't8s9df7'."
"List all extraction models available in my account."
Troubleshooting Cradl AI MCP Server with OpenAI Agents SDK
Common issues when connecting Cradl AI to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Cradl AI + OpenAI Agents SDK FAQ
Common questions about integrating Cradl AI MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect Cradl AI with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Cradl AI to OpenAI Agents SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.