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Sites similar to mcpfoundry.org

Mcpfoundry alternatives & similar sites

The Open Registry for Secure MCP Tools | MCP Foundry — 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 Information And Network Security →

Domain	Match	Title	Country/Lang	Category	AI files	Contact	AI-protection
mcptrail.com ↗	70 match 2 shared topics	MCP firewall & security gateway for AI agents \| MCP Trail	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
mcp-servers.org ↗	69 match 2 shared topics	MCP Server Registry	en	information-and-network-security	robots llmsaihumans	emailphone	none
mcpandchill.com ↗	66 match 2 shared topics	MCP and Chill \| Practical Notes on MCP and AI Security	en	information-and-network-security	robotsllmsaihumans	emailphone	partial · 8
diffsec.dev ↗	66 match 2 shared topics	diff sec — open source AI for product security	en	information-and-network-security	robotsllmsaihumans	emailphone	none
0xclaw.dev ↗	66 match 2 shared topics	Local AI pentesting for security teams	en	information-and-network-security	robots llmsaihumans	emailphone	partial · 7
mcpverify.net ↗	66 match 2 shared topics	MCPVerify — Trust Infrastructure for AI Tools	en	information-and-network-security	robotsllmsaihumans	emailphone	none
polidata.ai ↗	66 match 2 shared topics	Polidata Secure AI & Cyber Security Services for SMEs	en	artificial-intelligence	robots llmsaihumans	emailphone	none
composedsecurity.com ↗	65 match 2 shared topics	Composed Security — Verified product security for AI engineering teams	en	information-and-network-security	robots llmsaihumans	emailphone	none
krathes.com ↗	65 match 2 shared topics	Krathes \| Agentic AI Security Tool & Watchdog	en	information-and-network-security	robotsllmsaihumans	emailphone	none
algorithmicresearchgroup.com ↗	65 match 2 shared topics	Algorithmic Research Group — Open infrastructure for AI security research	en	information-and-network-security	robotsllmsaihumans	emailphone	none
herdsecurityio.com ↗	65 match 2 shared topics	Herd Security — The AI Creative Platform for Security Training	en	artificial-intelligence Sanity	robotsllmsaihumans	emailphone	partial · 8
herdsecurity.io ↗	65 match 2 shared topics	Herd Security — The AI Creative Platform for Security Training	en	artificial-intelligence Sanity	robotsllmsaihumans	emailphone	none
policylayer.com ↗	65 match 2 shared topics	PolicyLayer \| Policy Gateway for AI Agent Tool Calls	en	information-and-network-security	robots llmsaihumans	emailphone	none
owlshield.ai ↗	65 match 2 shared topics	OwlShield - Secure Your AI Agents	en	information-and-network-security	robotsllmsaihumans	emailphone	none
lvt.co ↗	65 match 2 shared topics	AI-Driven Mobile Security for Every Threat \| LVT	Colombia en	artificial-intelligence Webflow	robots llmsaihumans	emailphone	none
astrix.security ↗	65 match 2 shared topics	Identity Security for AI Agents & NHIs \| Astrix Security	en	information-and-network-security WordPress	robots llmsaihumans	emailphone	none
hacker101.co ↗	65 match 2 shared topics	HackerOne \| Leader in Continuous Threat Exposure Management \| Security for AI	Colombia en	information-and-network-security Drupal	robotsllmsaihumans	emailphone	none
vmeni.com ↗	65 match 2 shared topics	Vmeni \| Secure AI Infrastructure for Regulated Industries	en	artificial-intelligence	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.