vercel-ai_skill

Overview

This skill provides practical guidance for building AI-powered and agentic workloads on Vercel, covering the AI SDK, AI Gateway, Vercel Agent, and MCP. It explains core capabilities, configuration flow, and when to route model traffic or deploy agents, so you can move from prototype to production with confidence.

How this skill works

The skill inspects Vercel platform features and maps them to common AI architecture needs: embedding and inference via the AI SDK, controlled model routing through AI Gateway, agent orchestration with Vercel Agent, and tooling/workflow integration via MCP. It highlights configuration steps, security considerations, and monitoring points to ensure safe model usage and operational visibility.

When to use it

• Building web apps or APIs that require model inference at the edge or serverless functions
• Routing requests to multiple models or providers and enforcing usage controls
• Designing agentic workflows that coordinate tools, triggers, and external integrations
• Integrating developer tooling, indexing, or observability into AI pipelines via MCP
• Prototyping a full AI stack on Vercel before scaling to production

Best practices

• Choose the AI SDK for local inference patterns and consistent client APIs across runtimes
• Use AI Gateway to centralize model routing, rate limits, and access controls
• Store secrets and API keys in environment variables and never hard-code credentials
• Design agents with clear intent, sandboxed tool access, and explicit failure handling
• Monitor usage and latency with observability tooling to detect drift and cost spikes

Example use cases

• A customer support chat widget that routes to smaller models for FAQs and larger models for complex escalations via AI Gateway
• An email triage agent that uses Vercel Agent to invoke external APIs and update CRM records
• A documentation search app using the AI SDK to compute embeddings stored in Vercel storage and serving semantic search
• A CI workflow that validates model responses and logs metrics to MCP integrations for compliance