| What it does | Security scanner for AI agent configurations and MCP tool definitions
| AI execution infrastructure that turns mission-critical manual tasks into reliable, paid AI services
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| Stage | Not given
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| Founded | Not given
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| Based in | Not given
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| Pricing model | Freemium
| Contact for pricing
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| Pricing | Free: $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.
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| 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
| - Job of Work Mapper: identifies valuable processes and maps required outcomes, steps, systems and stakeholders
- Execution Engine: manages multi-week or multi-month workflows with fault tolerance, checkpoints and error recovery
- Built-in stakeholder management: communicates with stakeholders across channels and escalates exceptions
- Intelligence flywheel: captures execution data to benchmark models, improve accuracy and optimise costs
- Small focused AI models in deterministic graph: reduces errors and cost vs single large models
- Fully auditable and explainable execution
- Durable execution engine with checkpoints and automated recovery
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| 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
| - Handles multi-stakeholder workflows spanning days, weeks or months without requiring core product rebuild
- Partners keep control of brand and customer relationships while using platform for execution
- Usage-based pricing aligns fees with completed outcomes rather than features
- Small focused AI models designed for accuracy and repeatability in high-trust workflows
- Includes mapping stage to validate commercial viability before significant investment
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| Community votes | 0 | 0 |
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| DR (Domain Rating by Ahrefs) | 13 ▲ +1 (up) since last check | 12 ● no change since last check |
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| Trust Flow (Majestic) | 3 | 8 |
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| Citation Flow (Majestic) | 21 | 29 |
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| Referring domains (Majestic) | 18 | 64 |
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Foo Guard
Aguru