mcp server
LayerCall
Score an IP, email, phone, domain or device for fraud in one call, with the signals behind it.
Description as published by the maintainer. Source
- version 1.0.0
- active
active — Most recent push to the repository was 2026-08-04.
What this server can do
7 functions, named and described by the server itself. Parameter names are shown because they say more about what a function does than its name usually does.
lookup_phone(phone, country, strictness)- Validate a phone number worldwide against its national numbering plan. Returns E.164, country, line type (mobile/fixed/VoIP/toll-free/premium) and a risk score. Works globally, not US-only. Required: phone.
score_device(ip, device_id)- Judge a browser fingerprint from /fp.js: headless detection, automation frameworks (Selenium, Puppeteer, Playwright), timezone-versus-IP mismatch and repeat-device history. Note the ceiling honestly — the declared signals it relies on are the first thing stealth tooling patches, so a clean result is weaker evidence than a dirty one. Required: device_id.
score_domain(domain)- Profile a domain: registration date from RDAP, registrar, MX/SPF/DMARC configuration, disposable-mail and risky-TLD detection. newly_registered is null when the age genuinely could not be determined — treat that as unknown, not as 'established'. Required: domain.
score_ip(ip, strictness)- Risk-score an IPv4 or IPv6 address. Detects commercial VPNs (naming the provider where its own published list confirms it), proxies, Tor exit nodes and datacenter hosting, and returns geolocation, ASN and a 0-100 risk score with an allow/review/block verdict. Required: ip.
score_user(ip, email, phone, strictness, phone_country)- Score an entire signup in one call — any combination of IP, email, phone and domain — returning a single weighted risk score, a verdict, and the top contributing signals. A hard block on any component is never averaged away. This is the tool to use when judging a person rather than a value.
verify_agent(url, method, headers)- Cryptographically verify a Web Bot Auth signature (RFC 9421) — proof of WHICH agent is calling, not a guess from the user-agent. Returns verified true/false plus the agent's identity and declared purpose. This is the only check here that proves rather than infers, so it carries no score and no verdict: a verified assistant acting for a real user is usually welcome, a verified scraper usually is not, and that policy is the caller's. Pass the request the agent made to YOU — the signature covers its method, authority and path. Required: url, headers.
verify_email(email, strictness)- Check an email for syntax, MX records, disposable/throwaway providers, role accounts (info@, admin@), homograph lookalikes and domain age. Returns a 0-100 risk score and an allow/review/block verdict. Required: email.
Last successful function declaration observed on . Source: https://www.layercall.com/api/mcp. We list what the server declared; we do not call any of these functions.
Endpoint status observed on . Source: https://www.layercall.com/api/mcp.
Signals
These are separate measurements of different things. They are deliberately not combined into one score, because a popularity number that mixes website traffic with saves and stars cannot be checked or acted on.
| Signal | Value | What it measures | Window | Observed | Source |
|---|---|---|---|---|---|
| GitHub stars | 0 | Number of GitHub accounts that bookmarked this repository since it was created. It is a bookmark count, not installs, not active users and not quality. | cumulative, all time | GitHub | |
| Last commit | 2026-08-04 | Date of the most recent push to any branch. This is the strongest cheap indicator of whether the project is still maintained. | point in time | GitHub | |
| Open issues | 0 | Open issues plus open pull requests, as GitHub counts them together. A high number can mean an active project or an abandoned one. | as of fetch | GitHub | |
| Latest published version | 1.0.0 | Latest version string the maintainer published to the registry. | as of fetch | Model Context Protocol | |
| Registry record last updated | 2026-08-04 | When the registry record was last updated by its maintainer. | point in time | Model Context Protocol | |
| License | MIT | Licence GitHub detected in the repository. Detection can be wrong; the LICENSE file is authoritative. | as of fetch | GitHub | |
| First listed in the MCP Registry | 2026-08-04 | Date this server was first published to the official MCP Registry. Not a usage or quality measure. | point in time | Model Context Protocol | |
| repository status | active | The repository exists on GitHub and is not archived. This says nothing about how recently it was worked on. | as of fetch | GitHub | |
| mcp tools declared | 7 tools | Number of functions the server itself declared when asked to list them. This is what the server offers an agent, not a measure of how well any of them work. | as of probe | www.layercall.com | |
| mcp endpoint status | ok | The server listed 7 functions when asked. | as of probe | www.layercall.com |
Where to get it
Related, by what their authors tagged them
-
Arcjet
— last commit 2026-04-09, shares bot-detection
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com.extentos/mcp-server
— last commit 2026-08-01, shares sdk
Build smart-glasses apps with AI agents: scaffold, validate, and simulate before real hardware.
These share tags the maintainers applied themselves, such as bot-detection, email-validation, risk-scoring, disposable-email. Common tags like "mcp" or "ai" are ignored for this: agreeing with six hundred other projects is not a similarity.
This is not a recommendation and not a test result. It is a map of what the authors said their work is about.
How the author describes it
Topics the maintainer set on GitHub: bot-detection, disposable-email, email-validation, express-middleware, fraud-detection, nextjs, proxy-detection, python, risk-scoring, sdk, typescript, vpn-detection.
This record as data
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GET /api/v1/entries/mcp_server.json