Agent Protocols: MCP, A2A & More

There's no single protocol for AI agents. Different protocols solve different problems. Click on any part of the communication flow to understand where each standard fits.

The Core Communication Flow

Your Agent
Other Agent
Tool / API
Your Agent
Other Agent
Other Agent
Tool / API
A2A Layer
Agent → Agent

How do agents collaborate?

Multi-agent systems need ways to delegate tasks, share context, and coordinate work. This layer handles agent-to-agent communication, whether in centralized orchestration or decentralized networks.

Agent-to-Agent Protocol (A2A)Linux Foundation
Agent Network Protocol (ANP)Open Source Community

The Standardization Landscape

We're in the early days of agent interoperability. Unlike the web (HTTP, HTML) or email (SMTP, IMAP), there's no single governing body for agent protocols yet.

Linux FoundationMCP, OASF via AAIF
IETFANS, DN-ANR drafts
Industry ConsortiumsA2A (150+ orgs)

Supporting Infrastructure

Beyond communication, agents need standards for discovery and description.

Discovery & Coordination

How do agents find and organize with each other?

Before agents can communicate, they need to discover each other. ANS provides DNS-based discovery, while NANDA offers a broader framework for agent lifecycle management and decentralized coordination at scale.

Agent Name Service (ANS)NANDA
Schema & Evaluation

How do we describe agent capabilities?

Standardized schemas let us describe what agents can do, how they behave, and how to evaluate them. This enables interoperability, marketplace discovery, and consistent evaluation frameworks.

Open Agentic Schema Framework (OASF)Open Agent Specification (Agent Spec)
Building with these protocols?

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Protocol Comparison

Select protocols to compare:(3/3)
Strengths
Model Context Protocol (MCP)
stable
  • Universal adoption (all major AI platforms)
  • Linux Foundation governance ensures neutrality
  • Mature specification with extensive docs
Agent-to-Agent Protocol (A2A)
beta
  • Massive industry backing (150+ organizations)
  • Task-centric design with lifecycle management
  • Multimodal content support
Agent Network Protocol (ANP)
experimental
  • Fully decentralized—no central authority
  • Strong privacy through DID-based identity
  • Semantic interoperability
Considerations
Model Context Protocol (MCP)
  • • Not designed for agent-to-agent communication
  • • Security model still evolving
  • • Requires server deployment per integration
Agent-to-Agent Protocol (A2A)
  • • Still evolving (beta)
  • • Requires Agent Card infrastructure
  • • More complex than REST APIs
Agent Network Protocol (ANP)
  • • Early stage (experimental)
  • • Smaller ecosystem
  • • Complex implementation
Best For
Model Context Protocol (MCP)
Connecting AI assistants to enterprise systemsBuilding plugin ecosystemsDatabase queryingFile system access
Agent-to-Agent Protocol (A2A)
Cross-vendor agent collaborationEnterprise workflow automationMulti-agent customer serviceAgent marketplace integration
Agent Network Protocol (ANP)
Decentralized agent marketplacesCross-organizational collaborationPrivacy-preserving networksFederated research systems
Technical Details
Model Context Protocol (MCP)Agent-to-Agent Protocol (A2A)Agent Network Protocol (ANP)
Architectureclient-serverpeer-to-peerdecentralized
Message FormatJSON-RPC 2.0JSON-RPC 2.0JSON-LD
Transportstdio, HTTP/SSE, WebSocketHTTP/HTTPS, gRPC, SSE, WebSocketHTTP/HTTPS, WebSocket, DIDComm
Version2025-11-250.30.1
SDKsTypeScript, Python, RustPython, TypeScript, JavaPython, TypeScript
Architecture
Model Context Protocol (MCP)client-server
Agent-to-Agent Protocol (A2A)peer-to-peer
Agent Network Protocol (ANP)decentralized
Message Format
Model Context Protocol (MCP)JSON-RPC 2.0
Agent-to-Agent Protocol (A2A)JSON-RPC 2.0
Agent Network Protocol (ANP)JSON-LD
Transport
Model Context Protocol (MCP)stdio, HTTP/SSE, WebSocket
Agent-to-Agent Protocol (A2A)HTTP/HTTPS, gRPC, SSE, WebSocket
Agent Network Protocol (ANP)HTTP/HTTPS, WebSocket, DIDComm
Version
Model Context Protocol (MCP)2025-11-25
Agent-to-Agent Protocol (A2A)0.3
Agent Network Protocol (ANP)0.1
SDKs
Model Context Protocol (MCP)TypeScript, Python, Rust
Agent-to-Agent Protocol (A2A)Python, TypeScript, Java
Agent Network Protocol (ANP)Python, TypeScript

All Protocols & Initiatives

9 standards documented
Model Context Protocol (MCP)

The universal standard for connecting AI agents to external tools and data.

Supporters: Anthropic, OpenAI, Google...
Agent-to-Agent Protocol (A2A)

The standard for AI agents to communicate, collaborate, and delegate tasks.

Supporters: Google, Microsoft, IBM...
Agent Network Protocol (ANP)

Decentralized protocol for trustless agent discovery and collaboration.

Supporters: ANP Community, Academic Research
AG-UI Protocol

The standard for streaming AI agent interactions to user interfaces.

Supporters: CopilotKit, Microsoft, Google...
Agent Protocol

A standardized REST API specification for exposing AI agents as services.

Supporters: AI Engineer Foundation, AutoGPT, W3C Community Group
Agent Name Service (ANS)

DNS-based discovery system for AI agents with PKI trust.

Supporters: IETF Contributors
NANDA

Framework for decentralized AI agent coordination and lifecycle management.

Supporters: MIT, Academic Research
Open Agentic Schema Framework (OASF)

Standardized schemas for defining AI agent capabilities and metadata.

Supporters: AGNTCY, Cisco (Outshift)
Open Agent Specification (Agent Spec)

Declarative language for portable agent definitions with built-in evaluation.

Supporters: Oracle, CopilotKit