YBK · Enterprise AI Asset Governance
One control plane for every AI asset: MCP, skill, agent, app
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Most teams already run MCP servers, skills, agents and AI apps. What's missing is treating them as assets — one identity, one permission model, one cost ledger, one audit trail. ybkkasi does that: • Five asset types in one ledger with a lifecycle state machine • Cost attribution by department × agent × skill — attribution, not just observation • Dependency topology and blast-radius analysis • Fully self-hosted, MIT. Node 22 + node:sqlite, zero added dependencies
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PH · launched Oct 19, 2026 · 1 upvote (top 67%)
- Horizontal
- Compliance & governance
- B2B
- AI-native
- Commercial product
- Artificial Intelligence
- GitHub
Similar launches
See all 225 similar launches →Could you build this?
Partial The inventory dashboard, lifecycle state machines, and cost reporting can be vibe-coded, but deploying a reliable enterprise runtime proxy to enforce MCP permissions and capture real-time telemetry across agent frameworks requires deep systems engineering.
What it would actually take: A production version requires an MCP/HTTP reverse proxy layer deployed between clients and AI tools/agents, a high-throughput event ingestion pipeline (e.g., Kafka or ClickHouse), and strict enterprise RBAC/IAM integration (OIDC/SAML). The hard part is building lightweight, non-blocking middleware that parses and audits Model Context Protocol traffic and heterogeneous agent execution streams without introducing latency. This demands expertise in distributed proxy architectures, enterprise security compliance, and AI protocol standards.
Competitors
Other products that read as similar to this one : 225 launches clear the similarity bar, closest 8 shown.
Attention rank: #110 of 226 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 334 days after the earliest competitor.
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