Agent Lighthouse MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Agent Lighthouse MCP Serveraudit https://docs.example.com for AI agent readiness"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Logo files, icons, and usage rules: brand guide. Download the complete brand kit.

Example report from a scan of zapier.com on 2 September 2026. Scores describe that scan, not the site's current state.
⚡ Quickstart
Requires Node.js 22.22.2+ (22.x), 24.15.0+ (24.x), or 26+.
Run a zero-install scan directly in your terminal. The --view flag opens the standalone HTML report for screenshots, stakeholder review, and pull-request artifacts.
# Instant audit (prints terminal report & generates HTML + JSON reports)
npx @forkpoint/agent-lighthouse https://yourstore.com
# Open the standalone HTML report in your browser
npx @forkpoint/agent-lighthouse https://yourstore.com --view
# Run in CI and fail if score is below threshold
npx @forkpoint/agent-lighthouse https://staging.yourstore.com --min-score 85Agent Lighthouse checks 215 audits covering llms.txt, robots.txt crawler policy, Schema.org, OpenAPI discovery, WebMCP action surfaces, AEO/GEO content structure, agentic commerce, and operability.
Related MCP server: maxaeo-ai-visibility-mcp
Agentic readiness skill
Use the agent-lighthouse skill with a coding agent to turn an Agent Lighthouse report into code review and verified fixes. It supports any website stack.
The skill reads the report, traces findings through source files and hosting settings, checks related routes, and verifies requested changes. It keeps local fixes separate from deployed scan results.
Install the plugin from this repository's marketplace. In Claude Code:
claude plugin marketplace add ForkPoint/agent-lighthouse
claude plugin install agent-lighthouse@agent-lighthouseIn Codex:
codex plugin marketplace add ForkPoint/agent-lighthouse
codex plugin add agent-lighthouse@agent-lighthouseTo install from a local checkout, pass /absolute/path/to/agent-lighthouse to marketplace add instead, then run the same install command. Start a new chat after installation.
Example: “Use the agent-lighthouse skill to assess this site's Agent Lighthouse report and source code. Fix confirmed issues and verify the changes.”
Read the installation and workflow guide. The marketplace packages the skill and its references. The CLI and MCP npm packages remain separate.
🎯 What Agent Lighthouse Checks
Agent Lighthouse evaluates websites across 8 agent-journey categories grouped into 3 readiness pillars:
├── 1. Agentic Readiness
│ ├── Access & Crawl Control (robots.txt rules for GPTBot, ClaudeBot, PerplexityBot, blocks, status codes)
│ ├── Machine Discovery (llms.txt, llms-full.txt, sitemaps, feeds, .well-known surfaces)
│ ├── Agent Interfaces (WebMCP manifests, OpenAPI specs, agents.json, search actions)
│ └── Agentic Commerce (product offers, availability, checkout and payment surfaces)
│
├── 2. AI Search Optimization
│ ├── Content Extraction (clean main content, semantic structure, render and response cost)
│ ├── Structured Data (Schema.org Product, Offer, SKU, GTIN, Organization, JSON-LD validity)
│ └── Answer Readiness (direct answerability, step lists, tables, unique data, citations)
│
└── 3. Technical Foundation
└── Agent Operability & Safety (HTTPS, security.txt, tdmrep, stability, broken agent endpoints)📦 Packages & Architecture
This repository is organized as a lightweight pnpm monorepo published under the @forkpoint scope:
Package | npm Package | Description |
| Main CLI binary ( | |
| Core gatherer-audit engine, scoring algorithms, and types. | |
| Standalone HTML, Markdown, and unified report view-model. | |
| Model Context Protocol (MCP) server for Claude / Cursor / IDEs. |
🛡️ GitHub Actions CI
Use Agent Lighthouse as a pull-request gate for agentic readiness regressions:
name: Agent Lighthouse
on:
pull_request:
branches: [main]
jobs:
agent-lighthouse:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: ForkPoint/agent-lighthouse@main
with:
url: https://staging.yourstore.com
min-score: "85"
github-token: ${{ secrets.GITHUB_TOKEN }}The action generates terminal, HTML, JSON, and Markdown reports. Set comment-on-pr: true with github-token to post the Markdown summary on pull requests. See the marketplace setup guide for release-ready examples.
💻 Programmatic Node.js / TypeScript SDK
import { runScan } from "@forkpoint/agent-lighthouse-core";
import {
buildReportView,
generateHtmlReport,
} from "@forkpoint/agent-lighthouse-report";
const report = await runScan("https://example.com");
const view = buildReportView(report);
console.log(`Overall Score: ${view.overallScore}/100 (${view.scoreTier})`);
// Generate standalone HTML report
const html = generateHtmlReport(report);🤖 Model Context Protocol (MCP) Server
Add Agent Lighthouse to your Claude Desktop or Cursor IDE to let AI coding agents audit live staging URLs:
{
"mcpServers": {
"agent-lighthouse": {
"command": "npx",
"args": ["-y", "@forkpoint/agent-lighthouse-mcp"]
}
}
}📣 Share Your Score
Generated reports are standalone files, so teams can attach them to pull requests, send them to clients, or publish before/after improvements.
[](https://github.com/ForkPoint/agent-lighthouse)If you run Agent Lighthouse on a public site, share the result through the site score template. Good examples help other developers learn what agent-ready sites look like.
More material lives in:
🛠️ Development
# Clone the repository
git clone https://github.com/ForkPoint/agent-lighthouse.git
cd agent-lighthouse
# Install dependencies
pnpm install
# Build all packages
pnpm build
# Run unit tests
pnpm test📄 License
Apache-2.0 © ForkPoint
This server cannot be deployed
Maintenance
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