These tools and metrics are designed to help AI actors develop and use trustworthy AI systems and applications that respect human rights and are fair, transparent, explainable, robust, secure and safe.
Corsair

Corsair addresses a trust and accountability gap in agentic AI systems: as AI agents gain the ability to take real-world actions across connected apps, teams need a way to ensure those actions are secure, auditable, and controllable rather than opaque.
Corsair provides a multi-tenant integration layer supporting OAuth, MCP, webhooks, and both hosted and self-hosted execution. Its core trustworthy AI features include:
- Permission gating: Developers can set a permission mode per integration; sensitive or destructive actions (e.g. sending an email, modifying records) require explicit human approval before execution, giving end users a review step rather than a surprise.
- Credential isolation: Agents interact only with method names and results; Corsair resolves credentials internally at call time, so raw API keys and tokens are never exposed to the AI system itself.
- Data locality and self-hosting: The SDK can run entirely on a developer's own infrastructure, so credentials and user data never need to leave their stack
- Open source transparency: The integration logic is publicly auditable (Apache 2.0 licensed) rather than a closed-source black box, allowing independent verification of how agent actions are executed and gated.
The tool is aimed at developers building AI products and agents that need to take actions in third-party systems (email, calendars, CRMs, project management tools) while maintaining clear human oversight, credential security, and auditability — principles central to trustworthy, accountable AI deployment.
About the tool
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Tags:
- accountability
- ai agent
- ai integration
- mcp
Github stars:
- 11288
Github forks:
- 654
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