AI Transport Protocol

1.1.1. Leveraging AI

AI Agents have the potential to revolutionize various domains by automating and enhancing data exchange, decision-making, and interactions with external systems. However, their widespread adoption depends on ensuring that they are equipped with accurate, accessible, and verifiable data. This protocol aims to provide the framework that AI agents can use to interact with data sources effectively while ensuring minimal risk of misinformation and guaranteeing that AI-driven outputs are reliable.¶

1.1.2. Factual Integrity

To facilitate the effective use of AI-generated content by humans, it is crucial that the generated information remains highly faithful to factual accuracy. At a minimum, AI agents must ensure that referenced information is neither distorted nor misrepresented, and that the generated content maintains logical consistency. Furthermore, factual integrity is essential for building trust in AI-generated outputs. When AI systems produce content that aligns with verifiable sources without introducing misinformation, users can rely on them with greater confidence. Maintaining factual integrity also reduces the risk of spreading inaccuracies, thereby enhancing the reliability and usability of AI-generated content across various domains.¶

1.1.3. Reachability

AI agents are required to generate outputs based on various inputs, including resources that may not be explicitly specified. Therefore, it is essential that all necessary resources are accessible to AI agents and that they are aware of where to obtain specific information. This ensures that AI agents can function effectively, without limitations, in retrieving and processing the data required for accurate outputs.¶

1.1.4. Accessibility

Web resources may restrict AI agents from scraping content, particularly for critical components such as advertisements or other important sections of a site. This restriction could result in the inaccessibility of essential data, limiting the AI's ability to function optimally. The protocol addresses these challenges by outlining strategies for AI agents to respect data access rules while still ensuring valuable resources are reachable when needed.¶

1.1.5. Traceability

To ensure the reliability and transparency of AI-generated outputs, it is necessary to establish traceability mechanisms. These mechanisms allow for tracking the sources and reasoning behind the data used by AI agents in generating content. This will help verify the quality of the data and provide accountability for the outputs generated, which is crucial in sensitive contexts such as legal, medical, and financial applications.¶

1.1.6. Latency

Reducing latency in communication between AI agents and data sources is vital for ensuring responsive and real-time interactions. The protocol establishes guidelines for minimizing latency and ensuring that AI agents can efficiently process and respond to data requests in a timely manner. Optimized transport mechanisms will contribute to lowering delays and improving the overall user experience.¶

1.2.1. Large Integrated Resource

Establish a robust network of Model Content Protocol (MCP) servers to facilitate seamless communication between AI agents and various external data sources. This network will serve as the backbone for enabling efficient data retrieval, processing, and integration into AI systems, ensuring smooth and consistent interactions across different platforms.¶

1.2.2. Educational Use of AI

Promote the greater adoption of AI in educational contexts, enhancing learning methods through AI agents that interact with students, provide personalized feedback, and facilitate dynamic learning experiences. AI agents can help create customized educational environments, where students’ progress is tracked and tailored learning paths are provided based on their individual needs.¶

2.1.1. Transport

In this protocol, use the MOQTransport protocol for transport, ensuring the secure and efficient transmission of data between AI agents and external systems.¶

2.1.2. Session

The session of the MOQ concept. The MOQ session provides a framework for managing ongoing interactions between AI agents and external data sources, ensuring that context and state are preserved during the communication process.¶

2.1.3. Track

A single resource delivered as a "track" within the MOQ system. A track may refer to any distinct data set, file, or content that is used in the protocol’s operations.¶

2.1.4. Group

A group is a set of data sent in a single QUIC stream.¶

2.1.5. Announcement

The MOQ's Announcement. It indicates where endpoints can find resources such as MCP server.¶

2.1.6. Subscription

The MOQ's Subscription. A single subscription is a single resource.¶

2.1.7. Fetch Request

The MOQ's Fetch Request. Endpoints send request to the other as the MOQ's Fetch Request. Thus request and responce will be negotiated on a single QUIC stream.¶

2.1.8. Relay

The MOQ relay is a component that facilitates the transfer of data between AI agents and external resources, ensuring that communication is efficient and reliable.¶

2.2.1. MCP Server

MCP servers provides information from resources to MCP clients¶

2.2.2. MCP Client

MCP clients comminucate with MCP servers and accesses to modified resources through the server.¶

2.2.3. Resources

The Resources of the MCP concept. Every resources maps to a single track.¶

• Remote Resource: A resource that is served from a remote server, such as an API response.¶

• Local Resource: A resource that is located within a local environment, such as a database or file system, providing content that is directiory accessible by the AI agent.¶

2.2.4. Tools

The Tools of the MCP concept. Functions that can be called by the LLM¶

2.2.5. Prompts

The Prompts of the MCP concept. Pre-written templates that help users accomplish specific tasks¶

2.2.6. Request-Response

An endpoint sends a REQUEST message to another endpoint. The receiving endpoint verifies if it has a method that matches the Method Name and processes the Parameters. The endpoint that received the request responds by sending a RESULT message.¶

2.2.7. Notification

An endpoint informs other endpoints about the methods it supports by sending a NOTIFICATION message.¶

2.3.1. Level 3: Official Pronouncements

Content generated from authoritative sources, such as government reports or officially published information, which carries a high level of reliability.¶

2.3.2. Level 2: Corporate and Industry Sources

Content generated from corporate websites, industry reports, and professional publications. These sources are generally reliable but should still be verified.¶

2.3.3. Level 1: Individual Comments

Content generated from individual comments on the web, such as social media posts, blog entries, and forum discussions. These sources vary in reliability and should be verified for accuracy.¶

2.3.4. Level 0: Unverified Content

Content from anonymous sources or user-generated content that has not been verified. This level carries the lowest reliability.¶

3.1.1. REQUEST Structure

REQUEST {
  id: Request ID (i),
  method: Method Name (b),
  parameters: [
    {
      id: Parameter ID (i),
      value: Parameter Value (b),
    }
  ]
}

3.1.2. RESULT Structure

RESULT {
  id: Request ID (i),
  [key: Responce Key (b)]: Responce Value (b),
}

3.1.3. ERROR Structure

ERROR {
  code: Error Code (i),
  reason: Reason (b),
  data: Data (b),
}

### NOTIFICATION Structure
~~~text
NOTIFICATION {
  id: Notification ID (i),
  method: Method Name (b),
  arguments: [
    {
      id: Argument ID (i),
      type: Argument Type (i),
    }
  ]
}

3.1.4. RESOURCE

3.1.5. TOOL

3.1.6. PROMPT Structure

PROMPT {
  name: Prompt Name (b),
  parameters?: [
    {
      id: Parameter ID (i),
      name: Parameter Name (b),
      required: Required (i),
    }...
  ]
}

3.1.7. Concept Mapping

• "prompts/list" endpoint -> A Track named "prompts"¶

3.2.1. Set up

A session is established by a client connecting to a server using the MOQ (Media over QUIC) protocol. During the setup phase, the client initiates a connection request to the server. Any additional information required for the session, such as authentication tokens or configuration parameters, should be included as extensions to the MOQ setup messages. This ensures that both the client and server have all necessary information to establish a secure and efficient communication channel.¶

3.2.2. Announce

Endpoints can discover available resources through MOQ announce negotiation. This process begins with a subscriber indicating to a publisher the specific resources they are interested in. The publisher then responds with an announcement detailing the available resources. This negotiation allows for dynamic resource discovery and ensures that subscribers are aware of the resources they can access. The server's announcement includes metadata about the resources, such as their type, availability, and any access restrictions.¶

3.2.3. Subscribe

Reserved Tracks¶

3.2.4. Fetch

3.2.5. Terminate