Ai Gateway
Routes AI requests through Vercel's unified gateway so you can switch between 100+ models from different providers without changing code. The skill enforces current model naming (dots in versions, not hyphens) and pushes you toward OIDC auth instead of manual API keys. It's opinionated about outdated models, flagging gpt-4o and older Gemini versions with migration suggestions. Use this when you want provider failover, cost tracking, or the flexibility to swap OpenAI for Anthropic without rewriting integration code. The validation rules are aggressive but save you from deployment surprises with malformed model slugs.
- skills.sh installs
- 260
- GitHub stars
- 183
- last updated
- Jun 3, 2026
Install
$ npx -y skills add vercel-labs/vercel-plugin --skill ai-gateway --agent claude-codeInstalls into .claude/skills of the current project.
Files
Vercel AI Gateway
AI Gateway exposes models from multiple providers through shared authentication, model IDs, routing, billing, and observability. Model availability, SDK APIs, CLI commands, prices, and product capabilities change frequently. Verify them from current sources before changing code.
Start with current sources
Before implementing:
-
Inspect the project's language, package manager, installed AI SDK version, and existing provider integration.
-
Read the relevant Vercel page under https://vercel.com/docs/ai-gateway. Use the page's
.mdform when a tool needs Markdown. -
Fetch the complete live model list. Do not construct model variants by analogy:
curl -fsSL https://ai-gateway.vercel.sh/v1/models -
If the code uses the
aipackage, load theai-sdkskill when available. Read version-matched docs undernode_modules/ai/docs/and source undernode_modules/ai/src/. If the skill is not installed, use those bundled files directly. -
Run
vercel ai-gateway <command> --helpbefore documenting or scripting CLI flags.
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- Repository
- github.com/vercel-labs/vercel-plugin
- Categories
- Backend & APIs, AI & Agent Building, Cloud & Infrastructure
- First seen
- Jun 3, 2026
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