MCP and A2A are a new distribution shift in the AI era

Here’s why MCP and A2A constitute a new distribution shift in the AI era.

The current internet is dominated by aggregators like Google, Amazon, and Meta, which act as gatekeepers by controlling access to users, data, and digital marketplaces.

MCP (Model Context Protocol) and A2A (Agent-to-Agent Protocol) moves the digital ecosystem away from aggregator-dominated gatekeeping.

Towards a more open, agentic, and user-centric model, reshaping who holds power and how digital experiences are created and controlled.

Key areas of dramatic change

• Control and orchestration move from a handful of aggregators to distributed, protocol-driven agent ecosystems.

• Integration and interoperability are radically simplified, enabling plug-and-play workflows and reducing vendor lock-in.

• Discovery, monetisation, and data flows become more open, dynamic, and modular, changing the competitive and power landscape.

How control structures are changing

Aspect	Aggregator Era	MCP/A2A Era	Why It Matters
User access & control	Centralised through platform gatekeepers
(Google, Amazon, Meta, etc.)	Decentralised, agent-mediated, user-driven	Empowers users to control workflows and data, bypassing traditional gatekeepers.
Integration model	Proprietary, custom APIs; high vendor lock-in	Open, standardised protocols (MCP/A2A); plug-and-play	Dramatically lowers integration barriers, enabling rapid innovation and flexibility.
Workflow orchestration	Aggregator-controlled, rigid user journeys	Distributed, dynamic agent collaboration	Shifts workflow control from platforms to intelligent agent teams.
Data ownership	Aggregators collect, silo, and monetise user data	Data accessed on-demand, with user/org control	Users/enterprises retain more control and privacy over their data assets.
Ecosystem openness	High barriers to entry, limited interoperability	Low barriers, high interoperability, open ecosystem	Fosters competition, diversity, and new business models across the digital landscape.

Here’s how MCP and A2A are redefining AI’s capabilities

Source: DailyDoseofDS.com

Source: DailyDoseofDS.com

1. From isolated models to connected ecosystems

   1. MCP acts as a universal adapter for AI-to-tool interactions, standardising how agents access databases, APIs, and software (like USB-C for AI).

   2. A2A enables dynamic collaboration between specialised agents (e.g., research, analysis, and writing agents coordinating tasks).

   Together, they break the “integration bottleneck” where each tool/agent required custom code.

   
   

2. Complementary roles

   1. MCP = Vertical Integration (agent ↔ tool):

      • Example: An agent uses MCP to query a CRM.

   2. A2A = Horizontal Integration (agent ↔ agent):

      • Example: A sales agent delegates pricing analysis to a specialist agent via A2A.

   
   

3. Business and technical implications

   1. Plug-and-play AI let developers to compose systems from modular agents/tools instead of building monolithic models.

   2. Reduced vendor lock-in with standards let enterprises mix agents from Google, Anthropic, etc., while preserving security.

   
   

4. New challenges

   1. State management in dynamic workflows

   2. Cost optimisation for agent reasoning

   3. Authentication across distributed systems

   
   

5. Emergent use cases

   1. Self-organising supply chains

   2. AI “symphonies” of 100+ collaborating agents

      
      

6. Enterprise impact

   Early adopters report ~40% faster workflow automation using MCP/A2A hybrids. Source: Microsoft blo

   
   

The road ahead

While promising, this shift is still evolving. Adoption hurdles remain with the risk that competing protocols could fragment the ecosystem.

This shift is as big as the move from mainframes to cloud computing.

Their success hinges on widespread protocol adoption and solving new challenges in agentic system design.