AI Protocols: Why You Should Care About MCP and A2A Now

Ever feel like you’re drowning in AI acronyms? MCP, A2A, LLM, RAG… the list grows daily. It’s tempting to adopt a “wait and see” approach with all this new technology. After all, standards need time to settle before they become truly useful, right?

Not always.

When a technology is being adopted rapidly and has transformative potential, waiting could leave you playing an expensive game of catch-up. This is exactly what’s happening with Model Context Protocol (MCP) and Agent to Agent (A2A) Protocol.

Let’s break down what these protocols are, how quickly they’re being adopted, and whether you should care about them right now.

Model Context Protocol (MCP): The Universal Translator for LLMs

What is it?

MCP is essentially a universal protocol that lets large language models (LLMs) talk to external resources. Created by Anthropic engineers David Soria Parra and Justin Spahr-Summers and released as an open standard in November 2024, it enables seamless integration between AI models and developer tools.

Think of it as middleware that eliminates the need to write custom code for every integration. Instead of building dedicated connectors for each tool in your stack, you can wire everything through configuration. For developers, this is game-changing.

Adoption rate: Fast and furious

The adoption of MCP has been nothing short of explosive:

• IDE integration: VS Code, Cursor, Windsurf, Zed, and Neovim all implemented MCP by early 2025, with JetBrains following shortly after.

• CI/CD adoption: CircleCI, Bitrise, and GitHub have launched MCP servers for automation workflows.

• Community enthusiasm: Over 1,000 community-built MCP servers emerged by February 2025, covering everything from databases to ticketing systems.

• Even the competitors want in: OpenAI, Google Cloud, AWS, and Microsoft have added MCP support despite competing with Anthropic.

• Enterprise traction: Companies like Block (Square), Apollo, and Replit have integrated MCP, with Fortune 500 companies reporting 5-10% ROI improvements and 30% reductions in integration costs.

The protocol isn’t perfect. Its security model is still evolving, and it lacks multi-modal support. But it’s good enough to deliver substantial value today, and its open governance model positions it for continued growth.

Agent to Agent (A2A) Protocol: Making AI Collaboration Possible

What is it?

Google’s A2A Protocol, launched in April 2025, is an open standard designed to enable communication between AI agents across different frameworks and vendors. It standardizes how AI agents interact through:

• Capability discovery: Agents advertise their functions via JSON-based “agent cards”
• Task management: Defines how tasks are created, tracked, and completed
• Collaboration protocols: Supports clarifying questions and artifact sharing
• Experience negotiation: Allows agents to agree on interaction modes (text, forms, etc.)

In simple terms, A2A is what will enable your customer service bot to seamlessly collaborate with your inventory management system and your logistics planner.

Adoption rate: Early but promising

Though newer than MCP, A2A has quickly garnered support from over 50 organizations across technology, enterprise software, and consulting sectors:

• Tech heavyweights: Salesforce, SAP, ServiceNow, MongoDB, Atlassian, and Box
• AI specialists: Cohere, LangChain, Articul8
• Financial players: PayPal, Stripe
• Consulting partners: Accenture, BCG, Deloitte, KPMG, and McKinsey

This coalition is betting that standardized agent interoperability will transform enterprise workflows. While it’s early days, the momentum suggests A2A could become the foundation for the next generation of business automation.

Should you care right now?

Your answer depends on your role and how you interact with AI tools:

For developers:

MCP: Yes, absolutely. If you’re integrating AI into development workflows, MCP can save you significant time and effort today. The ecosystem is already rich enough to be immediately useful.

A2A: Worth tracking closely. If you’re building multi-agent systems, aligning with A2A early could future-proof your architecture.

For business leaders:

MCP: Yes, if your teams use AI-augmented development. The efficiency gains are already being realized by early adopters.

A2A: Begin planning. While implementations are still emerging, this protocol could reshape enterprise automation in the next 6-12 months.

For everyone else:

Both protocols represent something bigger than themselves: the standardization and maturation of AI infrastructure. Just as HTTP enabled the web to flourish, these standards will accelerate AI adoption by making integration and interoperability simpler.

The train is leaving the station. Whether you hop on now or wait for the next one is up to you—but understand that in rapidly evolving technologies, the cost of waiting often exceeds the cost of early adoption.

What AI standards is your organization tracking or implementing? The conversation is just beginning.