✈️Phase 1: Protocol Launch
The foundation of Axom AI begins with the release of its protocol layer and the $AXOMAI token, the core utility asset powering access, coordination, and governance across the network.
Launch of $AXOMAI Token The $AXOMAI token will serve as the backbone of the Axom AI ecosystem, enabling MCP interactions, staking and governance participation over protocol upgrades.
MCP Protocol Design Design and implementation of the Model Context Protocol (MCP). A lightweight, modular interface standard that allows LLMs and agents to call external systems in a structured and secure way. This includes the request/response format, permission architecture, and a unified authentication model to support diverse APIs, from cloud services to smart contracts.
QEDA Coordination Engine Development of the Quantum Event-Driven Architecture (QEDA), Axom’s async-first orchestration layer that manages tool invocations, retries, multi-agent workflows, and parallel executions in a scalable event loop.
LLM Integration for Routing Initial integration of top-tier LLMs (e.g., GPT-4, Claude) to power context-aware routing. These models serve as the first layer of natural language understanding, parsing user input, interpreting context, and generating tool invocation schemas that align with available MCPs.
Expansion Through Native Modules To showcase the power of the MCP protocol and provide immediate functionality, Axom AI will ship with a set of internal MCP servers that connect popular services to the agent runtime. These include Google Maps for geolocation and routing, GitHub for developer operations, YouTube for video search and metadata parsing, and Brave for privacy-centric web search. These modules act as reference implementations and expand the system’s capabilities across web2 utilities from day one.
MCP Registry & Developer Schema An open registry for MCP modules will be launched alongside a developer schema specification. This empowers third-party builders to register new tools, define capabilities in a structured manner, and expose secure, callable endpoints to use in real time.
CLI + Voice-to-Intent Routing The protocol’s voice-first vision begins with testing voice-to-intent parsing and multi-agent routing through a local CLI and dev console. This verifies that speech and typed inputs can be converted into structured agent flows, setting the stage for future voice-native experiences.
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