How do I get a Cradl AI API Key?

Log in to your Cradl AI dashboard and navigate to the API section to generate a new key. Ensure you keep this key secure.

Which document formats are supported?

Cradl AI supports major formats including PDF, JPEG, PNG, and TIFF for data extraction.

Can I train custom models via chat?

This integration currently focuses on executing extractions and monitoring tasks. Model training should be performed through the Cradl AI dashboard.

Cradl AI MCP Server for Google ADK 10 tools — connect in under 2 minutes

Name: Cradl AI
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 10 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add Cradl AI as an MCP tool provider through the Vinkius and your ADK agents can call every tool with full schema introspection.

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 google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token — get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="cradl_ai_agent",
    instruction=(
        "You help users interact with Cradl AI "
        "using 10 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

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 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.

Google ADK natively supports Cradl AI as an MCP tool provider — declare the Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 10 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

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 Google ADK 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 Google ADK via MCP

Follow these steps to integrate the Cradl AI MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 10 tools from Cradl AI via MCP

Why Use Google ADK with the Cradl AI MCP Server

Google ADK provides unique advantages when paired with Cradl AI through the Model Context Protocol.

Google ADK natively supports MCP tool servers — declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with Cradl AI

Production-ready features like session management, evaluation, and deployment come built-in — not bolted on

Seamless integration with Google Cloud services means you can combine Cradl AI tools with BigQuery, Vertex AI, and Cloud Functions

Cradl AI + Google ADK Use Cases

Practical scenarios where Google ADK combined with the Cradl AI MCP Server delivers measurable value.

Enterprise data agents: ADK agents query Cradl AI and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine Cradl AI tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query Cradl AI regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including Cradl AI

Cradl AI MCP Tools for Google ADK (10)

These 10 tools become available when you connect Cradl AI to Google ADK 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 Google ADK

Ready-to-use prompts you can give your Google ADK 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 Google ADK

Common issues when connecting Cradl AI to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

Cradl AI + Google ADK FAQ

Common questions about integrating Cradl AI MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.