🛡️ DeFi's Silent Killer

**The Problem**: $21B sits in onchain treasuries, mostly idle despite 47% DeFi yields available. Institutional capital can't simply "connect wallet and deposit" - it requires risk frameworks, real-time reporting, and compliant custody. **Aarna's Solution**: Building an **Agentic Onchain Treasury (AOT)** - a complete treasury management infrastructure layer for DeFi. **Key Features**: - Smart contract-enforced allocation policies and risk triggers - Modular vault system (fixed income, indices, stablecoins) - TARS agents execute within governance-approved parameters - Transparent, auditable decision trail - 24/7 automated rebalancing vs manual oversight **Why It Matters**: Retail built DeFi's rails, but they weren't designed for institutional weight. The missing piece isn't yield - it's policy-governed, auditable infrastructure that bridges what onchain capital *could* do versus what it actually does. AOT transforms fragmented DeFi protocols into institutional-ready treasury management without human intermediaries or custody risk.

Aarna AI has released its **ATV SDK** with comprehensive developer resources and tooling. **Key Components:** - MCP server package available on npm (@aarna-ai/mcp-server-atv) - Full API endpoint at atv-api.aarna.ai/mcp - Complete documentation portal - Open-source SDK on GitHub **What This Means:** Developers can now integrate Aarna's ATV functionality into their applications using the Model Context Protocol (MCP) standard. The release includes production-ready API access and package management through npm. The SDK connects to Aarna's existing aTars AI assistant and engine infrastructure, previously launched in January for BTC-related queries. [View Documentation](http://atv-api.aarna.ai/docs) | [GitHub Repository](http://github.com/aarna-ai/atv-sdk)

**aarna Tokenized Vaults (atv)** launched the first DeFi yield vault with native Model Context Protocol (MCP) and agent-to-agent (A2A) support, enabling AI agents to interact with DeFi without custom code or SDK integration. **Key capabilities:** - Discover vaults across Ethereum and Base - Query real-time APY data - Build deposit transactions - Track user portfolios The platform exposes **19 tools** through MCP, allowing agents to perform tasks like checking withdrawal status and comparing yields across vaults. Setup takes 30 seconds and works with Claude Desktop, Cursor, Windsurf, and other Streamable HTTP clients. This addresses a core limitation: while AI agents could discuss yield farming, they previously lacked structured access to execute DeFi operations. The solution requires no wrapper layers—agents simply connect and operate. The infrastructure represents a shift toward composable DeFi designed for autonomous agents.

**Aarna has deployed the first DeFi yield vault with native Model Context Protocol (MCP) and agent-to-agent (A2A) support on Base.** The new infrastructure allows AI agents to interact directly with DeFi protocols without custom code or SDK integration. The system exposes 19 tools through MCP, enabling agents to: - Discover vaults across Ethereum and Base - Query real-time APY data - Build deposit transactions - Track user portfolios The solution addresses a key limitation: while AI agents can discuss yield farming, they previously couldn't execute actual DeFi transactions or query protocol states in a structured way. **Setup takes 30 seconds** and works with Claude Desktop, Cursor, Windsurf, and any Streamable HTTP client. Aarna's February momentum report also highlights progress on their full treasury stack and preparation for the agentic era. The vault is now live on Base. [Read the full update on CMC](link)

**aarna introduces AOT (Autonomous Onchain Treasury)**, a new framework that shifts institutional DeFi allocation from yield-chasing to policy-driven management. **Key principles:** - Focus on mandate, risk bounds, liquidity profile, and execution governance rather than APY alone - Formalizes onchain allocation with defined constraints and continuous oversight - Addresses treasury-scale challenges: deep pool liquidity limits, manual operation inefficiencies, dynamic risk management **Problem solved:** Large treasuries (DAOs, protocols, foundations) face slippage on mid-six-figure positions, concentration risk from manual rebalancing, and lack of transparent audit trails. Traditional approaches either park stables at low yields or chase variable returns that collapse during downturns. **AOT's approach:** Provides autonomous, agentic treasury management with onchain verifiability and programmable policies, allowing teams to focus on product development rather than position management. Targeted at allocators managing multi-million to billion-scale treasuries seeking risk-managed yield with institutional-grade transparency.