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Documentation Index

Fetch the complete documentation index at: https://avala.ai/docs/llms.txt

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Avala integrates with the tools and infrastructure you already use. Whether you need AI-assisted annotation through MCP-compatible editors, cloud storage for your datasets, robotics data ingestion, real-time event notifications, or model inference for auto-labeling, Avala’s integration ecosystem keeps your annotation workflows connected and efficient.

MCP Server

Use Avala directly from Claude, Cursor, VS Code, and ChatGPT through the Model Context Protocol. Query datasets, manage projects, and trigger exports without leaving your editor.

Cloud Storage

Connect your own S3 or GCS buckets so data stays in your infrastructure. Upload, reference, and manage assets directly from your connected storage.

MCAP & ROS

Ingest MCAP files, ROS 1 bags, and ROS 2 bags with full support for camera images, point clouds, transforms, IMU, GPS, lidar, and radar message types.

Webhooks

Receive real-time HTTP notifications when exports complete, tasks are submitted, projects change status, and more. Build event-driven pipelines around your annotation workflow.

Model Inference

Connect SageMaker endpoints or custom HTTP model servers to generate pre-annotations. Speed up labeling with AI predictions that annotators review and refine.