Agentic AI Protocols: MCP, A2A and ACP

What is Agentic AI Protocols: MCP, A2A & ACP | AXD?

MCP, A2A, and ACP: the communication standards enabling agentic AI systems to coordinate, negotiate, and transact autonomously..

What is Introduction: The Language Problem?

Why Agentic Systems Need Protocols

What is MCP: The Model Context Protocol?

What is Architecture?

Key concepts in Agentic AI Protocols: MCP, A2A & ACP | AXD

How do agentic ai protocols: mcp, a2a & acp relate to agentic commerce?

  1. Agency requires intentional delegation — every agentic system begins with a designed act of delegation
  2. Trust is the primary material — AXD works in trust rather than attention
  3. Absence is the primary use state — the most consequential experiences happen when no one is watching
  4. Relationships have temporality — agentic experiences accumulate history over time
  5. Outcomes replace outputs — AXD designers specify results, not interfaces
DimensionTraditional UXAgentic Experience Design (AXD)
Primary materialAttention and affordanceTrust and delegation
User statePresent, navigatingAbsent, delegating
Design outputScreens and interfacesOutcomes and constraints
Temporal modelSession-basedRelationship-based
Success metricTask completionTrust calibration

Frequently Asked Questions

What are agentic protocols in AI systems?

Agentic protocols are the standardised communication and interaction rules that govern how autonomous AI agents interact with each other, with human users, and with external systems. They define the grammar of agent-to-agent negotiation, trust establishment, capability advertisement, and task delegation in multi-agent ecosystems.

Why do agentic AI systems need new protocols?

Existing internet protocols (HTTP, REST, GraphQL) were designed for human-initiated, request-response interactions. Agentic AI systems operate autonomously, requiring protocols that support agent identity verification, capability discovery, trust negotiation, delegated authority, and autonomous decision-making - none of which existing protocols adequately address.

How do agentic protocols relate to agentic commerce?

Agentic commerce depends on agents being able to discover merchants, negotiate terms, verify trust, and execute transactions autonomously. Agentic protocols provide the communication infrastructure for this: standardised ways for agents to advertise capabilities, establish trust, negotiate prices, and confirm transactions without human intervention at each step.

What are agentic protocols in AI systems?

Agentic protocols are the standardised communication and interaction rules that govern how autonomous AI agents interact with each other, with human users, and with external systems. They define the grammar of agent-to-agent negotiation, trust establishment, capability advertisement, and task delegation in multi-agent ecosystems.

Why do agentic AI systems need new protocols?

Existing internet protocols (HTTP, REST, GraphQL) were designed for human-initiated, request-response interactions. Agentic AI systems operate autonomously, requiring protocols that support agent identity verification, capability discovery, trust negotiation, delegated authority, and autonomous decision-making - none of which existing protocols adequately address.

Key Takeaways

In the early days of the internet, every computer manufacturer had its own proprietary networking protocol. IBM had SNA. Digital had DECnet. Xerox had XNS. Each worked well within its own ecosystem, but connecting systems across organisational boundaries was an exercise in frustration. It took TCP/IP - a single, open, universal protocol - to transform a collection of isolated networks into the internet. Agentic AI faces the same inflection point. Today, autonomous agents are being built on dozens of different frameworks - LangChain, CrewAI, AutoGen, BeeAI, Google ADK, Amazon Bedrock Agents, and many more. Each framework has its own conventions for how agents access tools, communicate with each other, and report their actions. The result is a landscape of capable but isolated agents, each speaking its own dialect. The AXD Institute's Three protocols have emerged to solve this problem. A single agent operating within a single application can communicate however it likes. The moment that agent needs to access an external tool, collaborate with another agent, or operate across an organisational boundary, it needs a shared language. Protocols provide that language. The need is acute for three reasons. First, The three protocols that have gained the most traction - MCP, A2A, and ACP - each address a different layer of this communication challenge. They are not competitors. They are complementary, each solving a distinct problem in the agentic communication stack. The Model Context Protocol was created by Anthropic in November 2024 and donated to the Linux Foundation in December 2025. It has been described as "USB-C for AI" - a universal connector that standardises how AI models access external tools, data sources, and services. MCP operates on the MCP follows a client-server architecture built on JSON-RPC 2.0. The host application (such as Claude, ChatGPT, or Cursor) acts as the MCP client. External systems - databases, APIs, file systems, web services - expose their capa

References and Citations

Gartner: Machine Customers as Strategic Technology Trend Stanford HAI: Human-Centered AI Research NIST AI Risk Management Framework About the AXD Institute Contact Us Email the AXD Institute Tony Wood on LinkedIn Tony Wood on X (Twitter)