This topic covers AI‑driven platforms that connect language models and autonomous agents to on‑chain DeFi protocols, market feeds, metadata systems and storage layers to enable real‑world asset (RWA) tokenization and end‑to‑end digital asset management. As institutional interest and regulatory scrutiny around RWAs increase in 2024–2025, practical implementations require reliable price and reference data, auditable data lineage, secure on‑chain interactions and robust storage/workflow orchestration. Key components are Model Context Protocol (MCP) servers and modular connectors: Edwin, Solana Agent Kit and Bsc‑mcp provide MCP surfaces for AI agents to execute actions on EVM chains, Solana and BNB Chain respectively; Solana Agent Kit explicitly offers LangChain‑ready actions for autonomous execution. Market and reference data come from CoinGecko and Nasdaq Data Link MCP servers to supply real‑time prices, historical series and off‑chain datasets. Metadata and provenance are handled by DataHub’s MCP server to index assets, trace lineage and support compliance or audit workflows. Keboola and other storage/workflow MCP integrations expose ETL, storage access and job triggers to agents, while context‑portal offers a lightweight project memory and structured knowledge graph for per‑workspace context. Together these categories — DeFi protocol integrations, crypto market data APIs, data catalog & lineage, and storage management integrations — form an operational stack for tokenizing assets, managing lifecycle events (custody, settlement, yield strategies) and preserving provenance. Important practical considerations include oracle selection, on‑chain governance, permissioning, data integrity and operator security. By combining MCP patterns with standardized data and storage connectors, organizations can prototype controlled, auditable RWA products while retaining the ability to integrate institutional datasets and compliance tooling.