Open-source MCP server scanning websites/APIs for AI agent readiness with ASO scoring and fix plans.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag β we're steadily working through the catalog.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Aso Audit MCP.
scan_siteFull ASO scan β Agent Readiness Report: ASO Score, level, pillar breakdown, all 34 checks with evidence + recommendations
get_fix_planPrioritized 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_signalRun one specific check (e.g. `a2a-agent-card`, `llms-txt`, `x402`)
list_checksCatalog of every check with spec links
get_aso_frameworkThe ASO rubric: pillars, weights, levels, certification thresholds
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 β 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.
Find gaps in discovery, trust, interoperability, and commerce β 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, PerplexityBotβ¦), 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) β your ASO Score and maturity level.
Requires Node.js β₯ 18. Published on npm as @forgemeshlabs/aso-audit-mcp β no clone or build needed.
Or skip the install entirely and run it with npx (recommended for MCP clients):
Only needed if you're hacking on the scanner itself:
| Tool | What it does |
|---|---|
scan_site | Full ASO scan β 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" Β· "What's my ASO score?" Β· "Give me a fix plan to make my site agent-ready."
This repository includes glama.json for Glama MCP registry ownership and install metadata.
@forgemeshlabs/aso-audit-mcpv0.2.0stdiostdio use. The scanner does not ask for API keys, tokens, cookies, or third-party credentials.Recommended Glama/MCP install command:
Example usage after connecting the server to an MCP client:
Release verification:
v0.2.0@forgemeshlabs/aso-audit-mcp0.2.0v0.2.0 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:
Runtime command:
In Glama's CMD arguments field, enter:
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 | 0β9 |
| ASO-1 | Discoverable | 10β29 |
| ASO-2 | Understandable | 30β49 |
| ASO-3 | Invocable | 50β69 |
| ASO-4 | Trustable | 70β89 |
| ASO-5 | Autonomous-Commerce-Ready | 90β100 |
Scores from this scanner are directional self-assessments. ASO Certification (ASO-3+) requires verified evidence β 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:
Factual signals from GitHub, npm, and our automated checks β not a rating.
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