Restack Review 2026

Durable execution framework for long-running AI agents and workflows — built on Temporal-style guarantees, in Python and TypeScript.

Restack is an open-source framework for building AI agents and long-running workflows that need to survive process crashes, model outages, human-in-the-loop pauses, and multi-day timers. Instead of gluing together queues, retries, and state stores by hand, developers describe each agent as a durable workflow whose functions Restack automatically checkpoints, retries with exponential backoff, and resumes exactly where they left off — the same execution model popularized by Temporal, but tuned for LLM workloads. Every model call, tool invocation, and message is recorded as an event, giving you fully replayable traces you can inspect in the local dev UI or send to any OTel-compatible backend. Restack ships SDKs for Python and TypeScript with first-class support for streaming events to the frontend, orchestrating multi-agent systems, and handing off to humans for approval. The platform also provides a local development experience via `restack up`, deployable Docker images for production, and Restack Cloud for teams that want a managed control plane. Cloud pricing is usage-based (workflow-seconds and events) starting around $25/user/month for small teams and scaling into the $161–$999/month range for higher-traffic accounts. Because workflows are versioned and deterministic, upgrading a prompt or model doesn't corrupt in-flight runs. Restack has become a popular choice for background research assistants, ETL pipelines with LLM enrichment, procurement bots, and any agent that needs to sleep, wake up, and continue reliably. MCP integration lets Restack workflows call MCP servers as tools.