Model Context Protocol
MCP
Model Context Protocol (MCP) is an open standard launched by Anthropic in November 2024 to let AI agents access tools and databases without writing custom integration code for each system . Its core purpose is to bridge the isolation between AI models and data silos by replacing fragmented, bespoke integrations with a unified client-server protocol .
By early 2025, MCP had gained substantial traction: over 10 tools including Claude Desktop, Cursor, and Continue had integrated it; the community had contributed more than 1,000 MCP servers spanning file systems, GitHub, and Google Drive; and companies like Block and Apollo were using it internally . OpenAI, Google, Alibaba, and Tencent have also adopted the protocol, and Gartner projected that 30% of enterprise AI projects would use standardized protocols like MCP by 2026 .
Yunqi Capital, which published research on the protocol in April 2025, argued that "MCP becoming a unified standard matters more than MCP's capabilities themselves" — the standardization lowers the barrier for agents to invoke complex tools, expands their functional boundaries, and creates a more mature development environment, even if technical challenges around LLM scheduling accuracy and router micro-distribution rules remain unresolved .
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Coverage
Are Models and "Shells" Both Undervalued? ZhenFund's Yusen Dai's Mid-2025 AI Review --- The past six months have been a turbulent period for AI. On one hand, DeepSeek's breakthrough has reignited global enthusiasm for Chinese AI; on the other, the commercialization path for large models remains unclear, and the market is growing increasingly anxious about when AI will generate real returns. Against this backdrop, I believe it's necessary to take stock of where we stand at this mid-point in 2025. **The Core Question: Are Models and "Shells" Both Undervalued?** Over the past two years, the AI industry has cycled through several narratives: from the initial frenzy over foundation models, to the subsequent boom in AI applications ("shells"), then a period of disillusionment as applications failed to deliver, and now a renewed focus on models following DeepSeek's success. But I want to propose a contrarian view: **both models and "shells" may be simultaneously undervalued by the market right now.** This might sound paradoxical. Let me explain. **Why Models Are Undervalued** The market's current skepticism toward model companies stems largely from two concerns: the commoditization of models (will they all become undifferent
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