Vercel now supports xmcp, a framework for building and shipping MCP servers with TypeScript, with zero-configuration.

xmcp uses file-based routing to create tools for your MCP server.

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my-project/
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├── src/
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│   ├── middleware.ts
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│   └── tools/
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│       ├── greet.ts
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│       ├── search.ts
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├── package.json
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├── tsconfig.json
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└── xmcp.config.ts

Once you've created a file for your tool, you can use a default export in a way that feels familiar to many other file-based routing frameworks. Below, we create a "greeting" tool.

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// src/tools/greet.ts
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import { z } from "zod";
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import { type InferSchema } from "xmcp";
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export const schema = {
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  name: z.string().describe("The name of the user to greet"),
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};
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// Tool metadata
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export const metadata = {
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  name: "greet",
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  description: "Greet the user",
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};
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export default async function greet({ name }: InferSchema<typeof schema>) {
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  const result = `Hello, ${name}!`;
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  return {
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    content: [{ type: "text", text: result }],
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  };
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}

Learn more about deploying xmcp to Vercel in the documentation.

AI Gateway is now generally available, providing a single unified API to access hundreds of AI models with transparent pricing and built-in observability.

With sub-20ms latency routing across multiple inference providers, AI Gateway delivers:

• Transparent pricing with no markup on tokens (including Bring Your Own Keys)

• Automatic failover for higher availability

• High rate limits

• Detailed cost and usage analytics

You can use AI Gateway with the AI SDK or through the OpenAI-compatible endpoint. With the AI SDK, it’s just a simple model string switch.

Get started with a single API call:

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import { streamText } from 'ai'
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const result = streamText({
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  model: 'openai/gpt-5',
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  prompt: 'How can AI Gateway not have a markup on tokens?'
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})

Read more about the announcement, learn more about AI Gateway, or get started now.

Streamdown is a new open source, drop-in Markdown renderer built for AI streaming. It powers the AI Elements Response component, but can also be used standalone to give developers a fully composable, independently managed option with npm i streamdown.

Streamdown is designed to handle unterminated chunks, interactive code blocks, math, and other cases that are unreliable with existing Markdown packages.

It's available now, and ships with:

• Tailwind typography styles: Preconfigured classes for headings, lists, and code blocks

• GitHub Flavored Markdown: Tables, task lists, and other GFM features

• Interactive code blocks: Shiki highlighting with built-in copy button

• Math support: LaTeX expressions via remark-math and KaTeX

• Graceful chunk handling: Proper formatting for unterminated Markdown chunks

• Security hardening: Safe handling of untrusted content with restricted images and links

You can get started with start with AI Elements:

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npx ai-elements@latest add response

Or as a standalone package:

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npm i streamdown

Read the docs and upgrade your AI-powered streaming.