Target URL: https://skyai.pro/#/ SKYAI is a Web3 AI data infrastructure project whose core value is to enable LLM and AI agents to view, analyze, and utilize real-time on-chain data. The key message on the official site is that “MCP enables LLM to pull on-chain and aggregated data in real time, enabling autonomous decision-making.” The technical center of the (SkyAI) project is Model Context Protocol, a scalable application of MCP to blockchain.
Investment View
Third, there are concerns about price volatility and market manipulation. Disclosing the number of API calls, number of active AI agents, number of registered MCP servers, paid dataset transaction volume, data provider revenue, and number of monthly active developers makes token valuation much easier. SKYAI has a good market narrative and problem definition in that it is a Web3 data infrastructure that enables AI agents to utilize on-chain data in real time.
The uploaded evaluation framework requires analyzing official websites, white papers, on-chain data, GitHub, and governance forums to assess technological maturity, economic self-sufficiency, institutional integration, network resilience, and narrative evolution. It also requires a nine-step analysis structure, quantitative scores, mathematical models, and in-line citations. However, the SKYAI official site was confirmed to be a JavaScript-dependent page in the current browser, so direct text extraction was limited.
Investment View
(CoinGecko) Weighted overall score: 43/100 L2: Early stage of narrative-market verification SKYAI has quickly secured the narrative of “blockchain data infrastructure for AI-agents” and exchange liquidity, but public code, usage, revenue, data provider network, governance, and security audits have not been sufficiently verified. CoinGecko recently indicated that there were on-chain analysis issues related to “coordinated wallets, CEX manipulation,” so there is also market trust risk. In particular, the lack of a public GitHub repository, unclear token value capture formula, and limited team disclosure are major deducting factors in the maturity evaluation.