AI Platform Training & Prediction is Google Cloud's earlier-generation managed service for training custom machine learning models and serving online and batch predictions. The API exposes models, model versions, jobs, online predict and explain calls, hyperparameter trial measurement, and study management. Most teams new to Google Cloud now use the Vertex AI API for the same workloads, but AI Platform remains supported for existing pipelines.
29 endpointsThe Cloud AutoML API trains and serves custom machine learning models for image classification, object detection, text classification, translation, and tabular prediction without requiring the caller to write training code. It exposes operations to manage datasets, kick off training, deploy or undeploy models, and run online or batch predictions. Long-running operations track training and deployment progress, and the API integrates with Cloud Storage for dataset import and batch prediction results. Note that AutoML is in maintenance with Vertex AI as Google's go-forward platform.
25 endpointsGoogle Cloud Document AI parses structured information from unstructured and semi-structured documents using Google's pretrained processors for forms, invoices, receipts, contracts, and identity documents. The API supports synchronous processing for single documents and batch processing for large volumes, with optional human-in-the-loop review for low-confidence extractions. Custom processors can be deployed, undeployed, evaluated, and trained against project-specific document types. Operations are scoped under projects, locations, and processors with full lifecycle management for processor versions.
# Add to your MCP client config (Claude Desktop, Cursor, Windsurf)
{
"jentic": {
"url": "https://api.jentic.com/mcp",
"auth": "oauth"
}
}
# Then ask your agent:
"find live events near a location"
# → Jentic returns the GET /events tool with parameter schema, agent executes.