A3T is a standards-based runtime for agents, paired with a typed database built for agent memory and state. Agents run as Kubernetes pods, wired together on a canvas, backed by memory, tools, and knowledge you define.
Pick a pre-built template, or import your own workflow definition from any registry. Templates declare the durability contract, variables, and tool surface up front — all as standards-based YAML.
$ a3t template pull ./my-template.yaml
Bind an LLM, list the tools the agent can call, declare the knowledge it reads from, and let it write back to memory. Every state transition is queryable AQL against ADB.
All four surfaces share one typed substrate: ADB.
The Agent Canvas is a Kubernetes CRD you compose visually or in YAML. Bind triggers — HTTP, topics, webhooks, cron — on the input side, emit to webhooks, queues, or downstream agents on the output side.
kubectl apply -f canvas.yaml · or drag on the canvas.
Free tier includes 10 agents, 100k invocations per month, and every template in the public registry. Bring your own cluster when you're ready to scale.
Every agent runs on a typed workflow engine with a lock-free execution queue. Steps dispatch in under a millisecond, routing is deterministic, checkpoints are content-addressed. Ephemeral agents stay hot; checkpointed agents rehydrate on demand.
ADB persists everything an agent touches — configuration as key/value, timelines as timeseries, embeddings as vectors, relationships as graphs. AQL is the single query language that joins across all four, so a skill can ask "recent events for this entity that match this intent."
Everything A3T runs is open source under BSL 2.0. Build locally with Docker, edit templates in VSCode, develop agents with Claude over MCP — standards-based, CI/CD-friendly, no cloud dependency.
Local A3T ships as a single Docker image. No system packages, no package managers, no version juggling. Run it once, get a local cluster with CRDs, controller, and the agent runtime preloaded.
Requires Docker Desktop 4.25+ · macOS / Linux / WSL2.
The A3T extension brings schema validation, type hints, deployment, and live runtime monitoring straight into VSCode. Edit agent definitions with confidence, push to your local cluster with one click.
A3T exposes its runtime over MCP. Point Claude or any MCP client at your local cluster, generate new templates, run them against test fixtures, and ship through your existing CI/CD.
$ claude mcp add a3t-local http://localhost:8080/mcp
A3T is a standards-based runtime. Everything is specified — from CRDs to AQL grammar to SDK internals. No proprietary magic, no abandoned tutorials.
Open docsA3T ships as a production-ready helm chart. Install into any Kubernetes — k3s, EKS, GKE, AKS, OpenShift. The controller speaks CRDs; your SRE team already knows how to operate it.
Every A3T object is a Kubernetes Custom Resource. Agents, templates, canvases, and every resource the agents consume — all reconciled by the A3T controller, all manageable with kubectl, ArgoCD, or your own tooling.
$ kubectl api-resources | grep a3t.io
Every admin action in A3T is a REST/gRPC endpoint. Provision tenants, manage RBAC, install CRDs, promote resources across clusters — all from your own automation.
OpenAPI 3.1 spec · gRPC reflection · Go and TypeScript SDKs.
Enterprise deployments bring SSO via OIDC, namespace-scoped RBAC, OPA/Gatekeeper policies, and cosign-signed templates. Your security team already trusts these primitives.
team-a-dev, ships to team-a-prod. Kubernetes handles the isolation.