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MCP Scorecard — Trust Scores for Every MCP Server — 18 websites ranked by shared content topics, category and on-page relevance.

Each result shows its full tech stack, contacts and AI-policy — not just a name · Browse all sites in Technology And Computing →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
mcp-scorecard.ai ↗	100 match 2 shared topics	MCP Scorecard — Trust Scores for Every MCP Server	en	technology-and-computing	robots llmsaihumans	emailphone	none
mcppedia.org ↗	71 match 2 shared topics	MCPpedia — Find the Right MCP Server	en	information-and-network-security	robots llmsaihumans	emailphone	none
cy-brush.com ↗	66 match 2 shared topics	Cybrush - Practical Cybersecurity for Everyone	en	information-and-network-security	robotsllmsaihumans	emailphone	none
mcpblog.dev ↗	65 match 2 shared topics	MCPBlog.dev — The MCP Ecosystem Blog	en	information-and-network-security	robots llmsaihumans	emailphone	none
mynaadam.com ↗	65 match 2 shared topics	sealayer — Every Document. Blockchain Verified. Forever.	United Arab Emirates~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
cypherblk.com ↗	64 match 2 shared topics	The trust layer for second-life devices \| CypherBlk	en	information-and-network-security	robotsllmsaihumans	email phone	none
leakcatch.com ↗	64 match 2 shared topics	LeakCatch — Know Who Leaked. Every Time.	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
eshard.uk ↗	64 match 2 shared topics	eShard \| Security investigations for critical missions	United Kingdom en	information-and-network-security X-Cart	robotsllmsaihumans	emailphone	none
certstream.dev ↗	64 match 2 shared topics	Certstream Server Rust - Real-Time Certificate Transparency Log Streaming	en	information-and-network-security	robotsllmsaihumans	emailphone	none
sigshare.dev ↗	64 match 2 shared topics	sig-share — Open Verification for Digital Content	en	information-and-network-security	robotsllmsaihumans	emailphone	none
decentrasec.com ↗	64 match 2 shared topics	Zero-Trust Infrastructure — ScholarMark & Deep Tech	PK~ en	information-and-network-security	robots llmsaihumans	emailphone	none
iblades.ai ↗	64 match 2 shared topics	iBlades - We Make Cybersecurity Simple, Reliable, and Accessible for Everyone	United States~ en	information-and-network-security	robotsllmsaihumans	emailphone	none
sigalmark.com ↗	64 match 2 shared topics	Sigalmark \| Building Trust	en	information-and-network-security HubSpot	robotsllmsaihumans	emailphone	none
mena.me ↗	64 match 2 shared topics	MENA: Enterprise Infrastructure for Execution, Detection, and Trust	en	information-and-network-security	robotsllmsaihumans	emailphone	none
trustedpedia.com ↗	64 match 2 shared topics	PlatformVeritas — Trust-Scored, Immutable Data	en	information-and-network-security	robotsllmsaihumans	emailphone	none
elitecoretechnologies.co.uk ↗	63 match 2 shared topics	Elite Core Technologies: UK Tech Solutions & IT Services	United Kingdom en	information-and-network-security	robotsllmsaihumans	emailphone	none
trustedtechafrica.com ↗	63 match 2 shared topics	TrustedTech Africa — Building Safer Digital Ecosystems	en	information-and-network-security	robotsllmsaihumans	email phone	none
bitlyft.com ↗	63 match 2 shared topics	MDR & Autonomous SOC for Mid-Market \| True MDR + AIR \| BitLyft	en	information-and-network-security HubSpot	robotsllmsaihumans	emailphone	none

How the match score works

Each match is a 0–100 similarity score — the higher it is, the more two sites resemble one another. It’s computed automatically from our own crawl data (never from what a site says about itself) by combining several independent signals, so a high score means several of them point the same way:

shared topics how many of the same fine‑grained content topics (IAB sub‑categories) both sites cover — the main signal.
same category whether they sit in the same business / industry category.
content & title how closely their titles and page descriptions line up in wording and meaning.

No single signal decides the result — they’re blended together. Treat the score as a way to rank candidates rather than an absolute percentage; the chips on each result show which signals contributed.