🏦Industry Landscape
From LLMs and AI agents to apps like Gmail, Google Maps, or DeFi tools - modern digital systems are capable, but deeply fragmented. Each works well on its own, but lacks a connection or common protocol, modular way to talk to others in real-time.
This leads to key limitations:
No shared context: Tools and agents can’t easily exchange live data or invoke each other’s capabilities.
Static by design: Updates require manual intervention or reconfiguration. There’s no fluid adaptability.
Isolated intelligence: LLMs, smart contracts, and APIs operate in closed loops, missing broader awareness.
Lack of protocol-level integration: There's no universal method to connect agents, apps, and actions together.
The Missing Link: Context
Whether it's an AI assistant managing your inbox or a smart contract needing live market data, the problem isn’t intelligence, it’s context. Systems need a standard way to fetch external resources, run modular tasks, or collaborate with others on demand.
That’s where Model Context Protocol (MCP) comes in. It provides a flexible, decentralized bridge that connects everything - from LLMs and APIs to wallets, compute modules, and cloud services.
But despite its potential, MCP is still early. Adoption is low, tooling is fragmented, and there’s no unified entry point for builders or users.
Where Axom AI Comes In
Axom AI solves this by building the missing infrastructure around MCP:
A marketplace for discovering and deploying MCP servers.
A playground to explore and interact with them live.
A developer-friendly framework for building and scaling with modular context.
Axom turns MCP from a promising spec into a usable foundation, making LLMs smarter, agents more capable, and digital systems truly interoperable.
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