Build with OpenAI Agents API on Vercel
Vercel now integrates with OpenAI Agents API to enable long-running, tool-using agent workflows hosted on Vercel's infrastructure. Developers can leverage OpenAI's managed agent loop combined with Vercel Sandbox for isolated code execution and Vercel Queues for webhook processing, creating scalable agent applications without maintaining virtual machines.
provides an OpenAI-hosted agent harness for long-running, tool-using workflows. You can host the agent experience on Vercel and connect each session to for code execution and file access.OpenAI Agents APIVercel Sandbox
OpenAI runs the agent loop and maintains session state. Signed OpenAI webhooks are processed through , while Vercel Sandbox provides an isolated, persistent execution environment for each agent session.Vercel Queues
With this integration, you get:
Follow the to build and deploy an agent, or explore the .step-by-step guidesample application
An OpenAI-managed agent loop and session state
Durable processing of sandbox lifecycle events
An isolated execution environment for every agent session
Persistent workspaces that remain available across follow-up instructions
A scale-to-zero architecture without long-lived virtual machines
Source: original entry ↗
More from Vercel
Follow Vercel to get its new changes in your feed and email digest.
Muse Wonder now available on AI Gateway
Meta's Muse Wonder model is now accessible through Vercel's AI Gateway, supporting coding tasks, multi-step agent workflows, and computer use with a 1M-token context window. Users can access the model via a single API key without creating a separate Meta account and use it for text, image, PDF processing, tool calling, and structured outputs.
Agents can now buy domains with the Vercel CLI
Vercel CLI now enables agents to discover, check availability, and initiate domain purchases through structured commands, with purchase confirmation remaining under user control via interactive terminal or dashboard approval.
New Pro teams default to 30-day deployment retention
Pro teams now default to a 30-day deployment retention period to balance keeping recent history available while reducing storage costs. You can configure a longer retention period in team settings if needed.