Overall AI readiness score
A combined result across all audit signals.
Overall AI readiness score
A combined result across all audit signals.
Overall AI readiness assessment
vercel.com was independently audited by llmsmap. vercel.com currently scores 60/100 for AI readiness. The result combines AI-specific files, crawler policy, sitemap discovery, structured homepage data, and—when available—the mobile Google Lighthouse technical profile.
llms.txt is accessible and contains — tokens. No accessible llms-full.txt was detected, so deeper context still has to be assembled from regular pages. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.
robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 1. No Schema.org type was detected on the homepage. 0 OpenGraph tags were found and markup completeness is 0%, leaving more entity interpretation to crawlers.
The Google Lighthouse measurement is still collecting. Once complete, performance, accessibility, technical quality, SEO, and experimental browser-agent signals will be added with a limited weight.
Google data is temporarily unavailable. The independent llmsmap AI-readiness audit remains valid.
Machine-readable files, crawler policy, discovery, and homepage markup.
Full version was not found
ai.txt file was not found
1 sitemap found
Schema.org markup was not found on the homepage
OpenGraph tags were not found on the homepage
Based on robots.txt analysis
Declared discovery routes for crawlers and agents.
# Vercel > Vercel is a cloud platform for building, deploying, and scaling web applications and AI workloads. Use this index to find machine-readable documentation and platform resources. Follow the linked indexes when you need individual pages. ## When to use Vercel - Deploy and scale web applications, APIs, and AI workloads from a Git repository or the Vercel CLI. - Automate projects, deployments, domains, and account resources through the Vercel REST API or SDK. - Connect an authenticated AI assistant to Vercel projects, deployments, logs, analytics, and documentation through Vercel MCP. - Route AI requests across providers through Vercel AI Gateway, with automatic fallbacks, spending controls, usage monitoring, and no markup on token prices. - Run untrusted or agent-generated code in isolated Vercel Sandboxes. ## How agents should use Vercel - For research, fetch the Markdown documentation indexes below and follow their links to individual Markdown pages. - For REST API calls, read the OpenAPI description and authentication documentation before choosing an operation. Ask for approval before changing account resources. - For Vercel MCP, use an OAuth-capable MCP client and let the user authorize access to their Vercel account. ## Agent setup - [Set up Vercel for your coding agent](https://vercel.com/get-started.md): Follow the agent playbook to install the CLI, add Vercel guidance, and connect Vercel MCP. - [Getting started with Vercel](https://vercel.com/docs/getting-started-with-vercel.md?from=llms-txt): Install the Vercel CLI, add the Vercel plugin or Vercel Skills, and deploy your first project. - [Vercel plugin](https://vercel.com/docs/agent-resources/vercel-plugin.md?from=llms-txt): Install with `npx plugins add vercel/vercel-plugin`, or `opencode plugin add github:vercel/vercel-plugin` in OpenCode, for Vercel skills, commands, and specialist agents. - [Vercel Skills](https://vercel.com/docs/agent-resources/skills.md?from=llms-txt): Browse and install individual skills for coding agents that do not support the plugin. ## Documentation - [Vercel product documentation](https://vercel.com/docs/products.md): Curated product index with links to documentation. - [Documentation sitemap](https://vercel.com/docs/sitemap.md): Documentation pages with summaries and prerequisites. - [Full documentation content](https://vercel.com/docs/llms-full.txt): Complete documentation and REST API reference in one file. ## REST API and developer resources - [Vercel REST API documentation](https://vercel.com/docs/rest-api.md): Endpoint reference for the public Vercel REST API. - [Vercel REST API OpenAPI description](https://vercel.com/openapi.json): Machine-readable OpenAPI 3.0 description for the public REST API. - [Vercel REST API authentication](https://vercel.com/docs/accounts/access-tokens.md#use-a-scoped-token-with-the-api): Create scoped access tokens and use them as Bearer tokens in API requests. - [Vercel webhook documentation](https://vercel.com/docs/webhooks.md): Event subscriptions, payloads, and delivery behavior. - [Vercel MCP server](https://vercel.com/docs/agent-resources/vercel-mcp.md): OAuth-authenticated tools for Vercel documentation and account resources. ## Self-serve onboarding - [Find a domain with Vercel CLI or API](https://vercel.com/domains/get-started.md): Search available names, compare registration and renewal prices, and return a verified shortlist. Neither requires authentication. - [Vercel Hobby plan](https://vercel.com/docs/plans/hobby.md): Free plan for non-commercial personal projects. - [Vercel CLI tokens](https://vercel.com/docs/cli/tokens.md): Create and manage personal access tokens for the Vercel API and CLI. - [Vercel AI Gateway](https://vercel.com/docs/ai-gateway.md): One API for AI models, with routing, fallbacks, and usage monitoring. - [AI Gateway models](https://vercel.com/ai-gateway/models.md): Every AI Gateway model with pricing, context window, providers, and capability tags. - [AI Gateway model list API](https://ai-gateway.vercel.sh/v1/models): Live JSON list of every model ID with pricing and capabilities. No API key required. - [Vercel Sandbox](https://vercel.com/docs/sandbox.md): Isolated compute for running code and agent workloads. - [Vercel Templates](https://vercel.com/templates.md): Deployable starter projects for frameworks, AI, storage, and more, each with a one-click deploy link. ## Knowledge Base - [Knowledge Base](https://vercel.com/kb.md): Featured and recent guides, plus a directory of topics. - [Knowledge Base sitemap](https://vercel.com/kb/sitemap.md): Troubleshooting guides, topics, videos, bulletins, and product references. ## Learning and updates - [Vercel Academy](https://vercel.com/academy/llms.txt): Courses and learning paths. - [Vercel Blog sitemap](https://vercel.com/blog/sitemap.md): Articles, engineering posts, and product announcements. - [Vercel Changelog sitemap](https://vercel.com/changelog/sitemap.md): Product updates and release notes. ## Optional - [Agent resource catalog](https://vercel.com/.well-known/ai-catalog.json): Experimental catalog of agent-facing resources. - [Product taxonomy](https://vercel.com/docs/taxonomy.json): Canonical product names, aliases, and deprecations. - [Documentation graph](https://vercel.com/docs/graph.json): Cross-site links, prerequisites, semantic neighbors, and related pages.
Sites with a close AI-readiness score — compare how they set up llms.txt and markup.