Cradl AI MCP Server for Mastra AI 10 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Cradl AI through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token — get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"cradl-ai": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Cradl AI Agent",
instructions:
"You help users interact with Cradl AI " +
"using 10 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Cradl AI?"
);
console.log(result.text);
}
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.
Mastra's agent abstraction provides a clean separation between LLM logic and Cradl AI tool infrastructure. Connect 10 tools through the Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution — deployable to any Node.js host in one command.
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 Mastra 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 Cradl AI to Mastra AI via MCP
Follow these steps to integrate the Cradl AI MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 10 tools from Cradl AI via MCP
Why Use Mastra AI with the Cradl AI MCP Server
Mastra AI provides unique advantages when paired with Cradl AI through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Cradl AI without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Cradl AI tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure
Cradl AI + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Cradl AI MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Cradl AI, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Cradl AI as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Cradl AI on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Cradl AI tools alongside other MCP servers
Cradl AI MCP Tools for Mastra AI (10)
These 10 tools become available when you connect Cradl AI to Mastra AI 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 Mastra AI
Ready-to-use prompts you can give your Mastra AI 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 Mastra AI
Common issues when connecting Cradl AI to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpCradl AI + Mastra AI FAQ
Common questions about integrating Cradl AI MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.Can Mastra agents use tools from multiple servers?
Does Mastra support workflow orchestration?
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 Mastra AI
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.