What's your ASO score?
SEO made you visible to search engines. ASO (Agent Signal Optimization) makes you discoverable, trustable, and payable by the AI agents that are becoming the web's next visitors.
aso-mcp is the free, open-source ASO Scanner — an MCP server that scans any website and produces an Agent Readiness Report scored on the open ASO framework. The beta npm package is @forgemeshlabs/aso-audit-mcp.
This release tracks Google's current agent-readiness guidance without overstating it: Google Search says traditional SEO fundamentals still apply to generative AI search, llms.txt is ignored by Google Search itself, and browser agents benefit from clean DOM, screenshot, and accessibility-tree signals. The scanner keeps llms.txt because non-Google agents use it, and adds a browser-agent UX check for semantic controls, linked labels, ARIA/role fallbacks, and hidden-overlay risk.
Beta. Experimental ASO scanner for evaluating whether agents can discover, trust, understand, and use a website/API/tool. ASO scoring is experimental and will evolve as agent standards mature.
=== Agent Readiness Report: https://example.com ===
ASO Score: 70/100
Agent Readiness: Ready
Level: ASO-4 Trustable — Agents can verify trust, reputation, and operational signals.
Discoverability 20/20 Identity 15/20 Trust 11/15
Commerce 5/15 Reputation 4/15 Memory 15/15
Find gaps in discovery, trust, interoperability, and commerce — every emerging agent standard in one scan:
| Pillar / Category | Checks |
|---|---|
| Discovery | robots.txt, sitemap.xml, Link headers, DNS-AID (_agent.<domain>), /.well-known/ai |
| Content | Markdown content negotiation, llms.txt, LLM-readable docs (/index.md, llms-full.txt) |
| Bot Access | Explicit AI crawler rules (GPTBot, ClaudeBot, Google-Extended, PerplexityBot…), Content Signals, Web Bot Auth |
| Interoperability | API Catalog (RFC 9727), OAuth discovery (RFC 8414), OAuth Protected Resource (RFC 9728), auth.md, MCP Server Card (/.well-known/mcp/server-card.json), Google A2A Agent Card (/.well-known/agent-card.json, required fields validated), Agent Skills, WebMCP |
| Commerce | x402, MPP, UCP, ACP, machine-readable pricing |
| Identity & Trust | HTTPS enforcement, JSON-LD/schema.org, agent-friendly browser UX, OpenAPI, agent.json, security.txt, status endpoint, versioning, cross-file identity & signal consistency |
The MCP tool audit_x402_endpoint complements the origin-wide ASO scan with a
no-spend protocol audit of one paid endpoint. It returns a 0-100 score, A-F
grade, compliance verdict, per-check booleans, failed checks, and observed
schemes/networks/extensions. It validates the live 402 challenge but never
sends PAYMENT-SIGNATURE, so it cannot authorize or settle a payment.
Checks: HTTPS/TLS, HTTP 402, PAYMENT-REQUIRED, Base64 JSON, x402Version: 2,
non-empty accepts, CAIP-2 networks, required payment fields, and JSON content
type. For body-gated routes, pass method, body, and optionally
content_type.
This is deliberately reported separately from the ASO Score: protocol compliance does not prove discoverability, trust, settlement, idempotency, or paid-response quality.
Agent protocols are changing quickly. The scanner is maintained as part of a living framework: checks are versioned, and stable standards, optional capabilities, release candidates, drafts, and vendor conventions are labeled separately. See the dated scanner source list and the canonical ASO source registry.
Every check returns pass / partial / fail with concrete evidence and a fix recommendation. Results roll up into the six ASO pillars (Discoverability 20, Identity 20, Trust 15, Commerce 15, Reputation 15, Memory 15) → your ASO Score and maturity level.
Requires Node.js ≥ 18. Published on npm as @forgemeshlabs/aso-audit-mcp — no clone or build needed.
npm install -g @forgemeshlabs/aso-audit-mcpOr skip the install entirely and run it with npx (recommended for MCP clients):
npx -y @forgemeshlabs/aso-audit-mcpclaude mcp add aso -- npx -y @forgemeshlabs/aso-audit-mcp{
"mcpServers": {
"aso": {
"command": "npx",
"args": ["-y", "@forgemeshlabs/aso-audit-mcp"]
}
}
}Only needed if you're hacking on the scanner itself:
git clone https://github.com/forgemeshlabs/aso-audit-mcp
cd aso-audit-mcp
npm install && npm run build
claude mcp add aso -- node /path/to/aso-audit-mcp/dist/index.js| Tool | What it does |
|---|---|
scan_site |
Full ASO scan → Agent Readiness Report: ASO Score, level, pillar breakdown, all 34 checks with evidence + recommendations |
get_fix_plan |
Prioritized remediation plan with ready-to-paste templates (robots.txt AI rules, llms.txt, agent.json, A2A agent card, MCP server card, x402 manifest, pricing.json, security.txt, status endpoint) |
check_signal |
Run one specific check (e.g. a2a-agent-card, llms-txt, x402) |
list_checks |
Catalog of every check with spec links |
get_aso_framework |
The ASO rubric: pillars, weights, levels, certification thresholds |
Try it: "Scan example.com for agent readiness" · "What's my ASO score?" · "Give me a fix plan to make my site agent-ready."
npm run smoke -- https://your-site.comThis repository includes glama.json for Glama MCP registry ownership and install metadata.
- Package:
@forgemeshlabs/aso-audit-mcp - Current release:
v0.2.0 - Transport: local
stdio - Authentication: none required for local
stdiouse. The scanner does not ask for API keys, tokens, cookies, or third-party credentials. - HTTP deployment: not enabled by this npm package. Any public HTTP deployment of this scanner must add authentication, per-client rate limits, request logging, and an egress policy before exposure.
Recommended Glama/MCP install command:
npx -y @forgemeshlabs/aso-audit-mcpExample usage after connecting the server to an MCP client:
Scan https://example.com for agent readiness.
Give me the ASO fix plan for example.com.
Check only the llms-txt signal for example.com.
List the ASO scanner checks.
Release verification:
- Git tag:
v0.2.0 - npm package:
@forgemeshlabs/aso-audit-mcp - MCP server version:
0.2.0
v0.2.0 adds the deterministic no-spend x402 v2 endpoint compliance audit while preserving the broader ASO Agent Readiness score as a separate metric.
Glama installability requires a Glama release, which is a containerized build created from the Glama Dockerfile admin page, not a GitHub release. This repo includes a production Dockerfile and GLAMA.md with the build spec values to use in Glama:
Build steps:
npm ci
npm run build
npm prune --omit=dev
Runtime command:
node dist/index.jsIn Glama's CMD arguments field, enter:
["node", "dist/index.js"]Do not leave CMD arguments as []; Glama validates that field separately from the Dockerfile CMD.
SEO ranks pages for people. ASO prepares services for agent selection, invocation, payment, and repeat use.
| Level | Name | Score |
|---|---|---|
| ASO-0 | Invisible | 0–9 |
| ASO-1 | Discoverable | 10–29 |
| ASO-2 | Understandable | 30–49 |
| ASO-3 | Invocable | 50–69 |
| ASO-4 | Trustable | 70–89 |
| ASO-5 | Autonomous-Commerce-Ready | 90–100 |
Scores from this scanner are directional self-assessments. ASO Certification (ASO-3+) requires verified evidence — see the scoring rubric and agentsignaloptimization.com for audits, certification, and the full framework.
This scanner makes outbound requests to URLs you give it, so it is built to resist SSRF abuse:
- Scheme allow-list — only
http/https;file:,ftp:,gopher:,data:etc. are rejected. - Private-target blocking — after DNS resolution, requests to loopback, private (RFC 1918), link-local, CGNAT, reserved, multicast, and the cloud metadata address (
169.254.169.254) are refused. IPv6 loopback/ULA/link-local and IPv4-mapped forms are covered too. If a hostname resolves to any private address, the scan is refused. - Pinned-IP transport — each request dials the exact public IP that was validated, while TLS still verifies the original hostname. This closes the validate-then-connect DNS rebinding window.
- Manual redirect validation — automatic redirect following is disabled; every hop is re-validated against the same rules, capped at 5 redirects. A public URL that 30x-redirects to an internal address cannot slip through.
- Untrusted remote content — parsed manifests are omitted from tool output by default (
include_artifacts: trueto opt in, and they are then explicitly labeled untrusted); embedded text excerpts are control-char-sanitized and length-capped. Treat any returned remote content as data, never instructions. - Bounded —
GETonly,ASO-Scanner/1.0UA, max 6 concurrent, 10s timeout, 512KB body cap. Never authenticates, never POSTs, never crawls beyond well-known paths. - Tested hardening —
npm testcovers unsafe URL rejection, private IP ranges, artifact sanitization, redirect blocking, redirect hop caps, and the test-only loopback escape hatch.
Deployment: stdio (local, per-user) is the safe default. A public HTTP deployment is a network-egress tool and must add authentication, per-client rate limiting, request logging, and an egress policy before exposure.
- Reputation signals (citations, reviews, success rates) cannot be auto-verified by a crawler; they are reported as
manualand scored 0 until verified by audit — so the auto-verifiable maximum is 89/100. That is intentional honesty, not a bug. - Emerging specs (MCP Server Cards SEP-1649/SEP-2127, DNS-AID, Web Bot Auth, UCP/ACP/MPP) move fast. PRs updating paths welcome.
This package intentionally separates Google Search guidance from broader ASO guidance:
- Google Search generative AI features still rely on core Search ranking and quality systems; foundational SEO, crawlability, helpful content, and technical clarity remain the priority.
- Google Search does not use
llms.txtor special AI markdown files for ranking or AI Overviews/AI Mode visibility. ASO still checks them because other agents and MCP clients can use them. - Google/web.dev's agent-friendly site guidance focuses on browser-agent usability: stable layouts, semantic HTML, labels tied to inputs, meaningful roles/names/states, and avoiding hidden overlays.
- UCP, AP2, A2A, MCP, x402, DNS-AID, Content Signals, and Web Bot Auth are emerging non-SEO protocols. The scanner treats them as agent-readiness signals, not as Google Search ranking factors.
Primary references:
- https://developers.google.com/search/docs/fundamentals/ai-optimization-guide
- https://web.dev/articles/ai-agent-site-ux
- https://ucp.dev
MIT — free for everyone. If the scanner found gaps, the ASO framework shows you how to close them.