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Foo Guard vs Rigorix

A side-by-side comparison built from both listings. Blank cells mean the company has not given that detail; we never guess.

Foo Guard compared with Rigorix
DetailFoo Guard logo Foo GuardRigorix logo Rigorix
What it doesSecurity scanner for AI agent configurations and MCP tool definitions Execution governance for consequential AI-agent operations
StageNot given Not given
FoundedNot given Not given
Based inNot given Not given
Pricing modelFreemium Freemium
PricingFree: $0, no account needed. Pro: $19/mo or $190/yr. Team: $57/mo (3-user minimum) or $570/yr, then $19/mo per additional user. Free engine (MIT/Apache-2.0 open source). Team tier: €1,900/month including 25 writing seats and 50,000 governed actions per month; overage €0.02 per action above 50k monthly. Enterprise: from €90,000/year. Design partner program: €18,000 for 90 days (credited against first annual contract). Add-ons
Key features
  • Browser-based scanning for agent configurations
  • CLI for local scans and CI enforcement
  • 30+ security checks and secret detection
  • OWASP and SOC 2 rule packs
  • Gateway runtime enforcement for MCP requests
  • GitHub App integration with pull request checks
  • Optional AI-powered remediation guidance
  • Policy-as-code via .fooguard.yml
  • Authority revalidation at dispatch time against live conditions
  • Approval binding to canonical intent with single-use, time-bound enforcement
  • Sequence and prerequisite policy enforcement at plan time and runtime
  • Effect identity matching to prevent duplicate actions across runs
  • HMAC-signed, hash-chained, and Ed25519-anchored evidence
  • Cross-session capacity ledger for aggregate exposure control
  • Verifiers in five languages for independent offline verification
  • MCP server support for integration with Claude Code, Cursor, and other agents
  • Air-gapped deployment with documented key ceremony on Enterprise
  • Deterministic Rust enforcement engine with no models in the decision path
What makes it different
  • Deterministic security rules rather than AI-based scoring
  • Pre-deployment configuration analysis without agent execution
  • Runtime enforcement via Gateway for supported MCP tool calls
  • Audit logging and SIEM streaming for compliance
  • Works across browser, CLI, GitHub, and API
  • Authority is revalidated at the moment of execution, not just at approval time
  • Signed, verifiable evidence allows third-party audit without trusting the vendor
  • Deterministic enforcement with no AI models influencing the gate decision
  • Pricing on governed actions, not seats, aligned with consequence not headcount
  • Refusals and verification are never metered or charged
Community votes00
DR (Domain Rating by Ahrefs)8 +1 (up) since last checkNot checked yet no change since last check
Trust Flow (Majestic)30
Citation Flow (Majestic)210
Referring domains (Majestic)180

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