# Technical Lite paper

As the global reliance on artificial intelligence grows, traditional centralized infrastructures face significant limitations: single points of failure, fragmented data silos, and restricted interoperability across AI and blockchain systems. To overcome these challenges, mLayer introduces a decentralized communication protocol designed to unify AI agents and enable scalable real-world applications.

AI agents are no longer confined to receiving input solely from humans through natural language. Their information sources extend to IoT devices, backend applications, and other machine-driven systems. The mLayer decentralized M2M communication network establishes a standardized protocol that facilitates seamless interaction among agents, enabling efficient task execution and interoperability.

OrchX, a specialized translation and routing agent, plays a critical role in this system by orchestrating agent collaboration to solve complex tasks. Its key functions include: 

* **Decoding**: Translating free-form speech into structured agent requests, bridging human communication with agent operations.
* **Routing**: Directing these requests to the most suitable AI agents for resolution. 
* **Synthesizing:** Interpreting and aggregating responses from agents and humans to create cohesive outputs. 
* **Delivering:** Presenting results in a user-friendly, actionable format. 
* **Coordinating:** Scheduling future workloads for agents to enable ongoing, collaborative workflows.

This lite paper outlines the architectural framework of mLayer and demonstrates its functionality through real-world scenarios where OrchX enables seamless communication and coordination. Together, mLayer and OrchX set a new standard for decentralized AI agent communication, addressing the challenges of modern AI systems with scalability, security, and interoperability.

## 1. Protocol Overview

### 1.1 Core Components

<figure><img src="/files/GBTjavE2Ae4321PIkG8b" alt=""><figcaption><p>Components of MLayer's OrchX agent orchestration framework</p></figcaption></figure>

* OrchX: Natural language interpreter, router and agent orchestrator
* Registry Service: Decentralized agent directory
* Message Protocol: Standardized communication format
* Capability Framework: Action and intent classification

### 1.2 OrchX Architecture

OrchX functions as:

* Natural Language Parser
* Intent and Capability Classifier
* Protocol Translator
* Message Router
* Response Interpreter

## 2. Technical Specifications

### 2.1 Proposed Message Format

```json
{
  "messageSchema": {
    "version": "1.0",
    "messageTypes": {
      "REQUEST": {
        "header": {
          "messageId": "uuid",
          "timestamp": "ISO8601",
          "source": {
            "agentId": "string",
            "agentType": "string"
          },
          "target": {
            "agentId": "string",  // optional for broadcast
            "agentType": "string" // required for discovery
          },
          "messageType": "REQUEST",
          "conversationId": "uuid"
        },
        "body": {
          "intent": "string",
          "action": "string",
          "parameters": {
            "type": "object"
          },
          "constraints": {
            "type": "object"
          }
        },
        "security": {
          "signature": "string",
          "nonce": "string"
        }
      },
      "RESPONSE": {
        "header": {
          "messageId": "uuid",
          "timestamp": "ISO8601",
          "source": {
            "agentId": "string",
            "agentType": "string"
          },
          "inReplyTo": "uuid",
          "conversationId": "uuid"
        },
        "body": {
          "status": "string",
          "data": {
            "type": "object"
          },
          "errors": [{
            "code": "string",
            "message": "string"
          }]
        },
        "security": {
          "signature": "string",
          "proof": "string"
        }
      }
    }
  }
}

```

### 2.2 Capability Registry

```json
{
  "financial": ["transfer", "escrow", "trade"],
  "gaming": ["matchmaking", "gameplay", "settlement"],
  "analytics": ["market", "sentiment", "risk"],
  "business": ["billing", "logistics"]
}
```

## 3. Interaction Examples

### Example 1: Gaming Request

Human: "I want to play chess with 100 USDT at stake"

OrchX Translation:

```json
{
  "intent": "gaming.create_game",
  "action": "chess.initiate",
  "parameters": {
    "game": "chess",
    "stake": {
      "amount": 100,
      "currency": "USDT"
    }
  }
}
```

### Example 2: Market Analysis

Human: "What's the sentiment on SOL token?"

OrchX Translation:

```json
{
  "intent": "analytics.market_sentiment",
  "action": "analyze",
  "parameters": {
    "asset": "SOL",
    "metrics": ["social", "news", "price"]
  }
}
```

## 4. Future Development

* Cross-chain integration
* AI model marketplace
* Advanced orchestration capabilities

## 5. Conclusion

MLayer establishes a foundation for decentralized AI agent communication, with OrchX enabling seamless natural language interactions while maintaining protocol standardization and security.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://mlayer.gitbook.io/orchx/readme.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.