PqP
Network.
A communication network for AI agents.
How do agents work together across devices?
PqP—Peer-Queue-Peer—is evolving from a peer network into communication infrastructure for AI agents. The research asks how independently operated agents can exchange tasks and results across different runtimes, interrupted connections, and periods offline.
Active research prototype. The networking foundation exists; agent interoperability is planned work, with security and reliable delivery as prerequisites.
From peers to agents
PqP’s foundation is its Web 5.0 research into a client-powered cloud network. Its TypeScript core supports peer discovery through DNS, encrypted messages through provider-hosted queues, and direct WebRTC connections. That work provides the foundation for the agent-network research.
The next layer concerns agent tasks: how they are addressed, authorized, acknowledged, and resumed. A2A is the first proposed interoperability target. The protocol adapter is planned; the current prototype does not yet establish A2A compatibility.
The architecture continues to use shared DNS, relay, queue, and identity services. Their role and failure modes remain part of the research.
Open research questions
Tasks that survive interruptions
Can an agent hand off a task and receive a result when either device goes offline? We need to understand recovery, duplicate delivery, and task completion across those gaps.
Identity across owners
How should an agent identify another agent and decide what it may ask of it? Authenticating a message and authorizing a task are separate problems.
From queues to direct connections
Can communication move between delayed queue delivery and a direct connection without losing task state or changing the meaning of an acknowledgement?
When the network earns its complexity
How do completion rates, latency, bandwidth, and infrastructure dependence compare with ordinary HTTP, webhooks, and durable brokers? These comparisons must guide the architecture.
The workloads we want to test
A coding agent handing a task to another machine. A long-running job returning its result after the requesting device reconnects. Agents coordinating work across separately operated environments.
These are proposed workloads for evaluation. The aim is to learn where queue-assisted peer communication helps, what it costs, and where a simpler transport works better.
Discuss the researchPublications
Toward a network for AI agents
PqP’s next research direction is task exchange between independently operated agents, using queued contact and direct connections across interruptions.
PqP NetworkBinding PqP messages to their sender
The identity implementation now connects authenticated principals, queue ownership, and message-signing identity across the control plane and clients.
PqP NetworkSigned ancestry for shared vault changes
PqP’s public-vault synchronization now records merge ancestry in signed metadata and prepares that metadata before replacing local content.
PqP NetworkDirect WebRTC connections in the desktop client
PqP’s Electron client can now establish a WebRTC path through the shared package, extending the transport work already integrated in the browser extension.
PqP NetworkPqP gets a shared networking core
The networking implementation is now a TypeScript package, with common cryptography and messaging behind Chrome and Electron adapters.
PqP NetworkA queue for each PqP participant
The first PqP Worker can find or create a participant’s queue, establishing the provisioning step for queue-assisted peer communication.
PqP Network