Manthan Patel’s Post

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I teach AI Agents and Lead Gen | Lead Gen Man(than) | 100K+ students

2025 is the Year of Anthropic's MCP and Google's A2A. Everyone's talking about AI agents, but few understand the protocols that power them. 2025 is witnessing two pivotal protocols with two outstanding standards that aren't competitors, but complementary layers in the AI infrastructure: 𝗠𝗖𝗣 (𝗠𝗼𝗱𝗲𝗹 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹) by Anthropic • Creates vertical connections between applications and AI models • Flow: Application → Model → External Tools/Data • Solves context window limitations and standardizes tool access • Think of it as the nervous system connecting your brain to your body's tools 𝗔𝟮𝗔 (𝗔𝗴𝗲𝗻𝘁-𝘁𝗼-𝗔𝗴𝗲𝗻𝘁 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹) by Google • Enables horizontal communication between independent AI agents • Flow: Agent ↔ Agent (peer-to-peer) • Solves agent interoperability and complex multi-specialist workflows • Think of it as the language that lets different experts collaborate on your behalf Beyond technicality, each protocol has its core strengths. 𝗪𝗵𝗲𝗻 𝘁𝗼 𝘂𝘀𝗲 𝗠𝗖𝗣: • Building document Q&A systems • Creating code assistance tools • Developing personal data assistants • Needing fine-grained control over context 𝗪𝗵𝗲𝗻 𝘁𝗼 𝘂𝘀𝗲 𝗔𝟮𝗔: • Orchestrating multi-agent workflows • Automating cross-department processes • Creating agent marketplaces • Building distributed problem-solving systems Both protocols are gaining significant traction: 𝗠𝗖𝗣 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺: • Backed by major LLM providers (Anthropic, OpenAI, Google) • Strong developer tooling and SDKs • Focus on model-tool integration • Open-source with growing community support 𝗔𝟮𝗔 𝗘𝗰𝗼𝘀𝘆𝘀𝘁𝗲𝗺: • 50+ enterprise partners at launch • Emphasis on business workflow integration • Strong multimodal capabilities • Built for enterprise-grade applications Top AI solutions integrate both MCP and A2A to maximize their potential. • Use MCP to give your models access to tools and data • Use A2A to orchestrate collaboration between specialized agents • Think in layers: model-tool integration AND agent-agent communication Over to you: What tasks for AI agent do you think would benefit the most for A2A Protocol over MCP?

  • MCP vs A2A
Amey Borkar

Data Science Intern @DSM-Firmenich | 2x Microsoft Azure Certified | Machine Learning, Deep Learning, Natural Language Processing, Generative AI, Python, Statistics, SQL, AWS | Teaching Assistant

2w

💡 Great insight

Nilupul Manodya

Designing Smart Systems for People Who Move Fast | Software Engineer (AI)

2w

Nice Visuals !

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Gino S.

🚀 "Let’s Iterate for an Elevated Project "DM" GLO25."🚀

2w

Bedankt voor het delen, Manthan

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Jeramie Baker

"Self-Taught Innovator | AI & Cybersecurity Visionary | Problem-Solver Driving Human-Centric Tech Solutions, Pattern & Anomaly Recognition, Cross Disciple Thinker" #AGIpossible #AIMaster #AIEthics #AGISconcepts #AIRights

2w

Still see issues with the system, but that's my take. Oh well. I expect them to address it later... I would work for them if they considered my experience with tech over my life vs creds.

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Eric Martin

Helping CIOs eliminate vendor waste + recover 6–7 figures from $1M+ tech stacks

2w

Manthan, you've laid out the AI hierarchy like a tech survival guide, MCP the brains and A2A the glue holding the specialists together. Makes me wonder, how long until AI agents start discussing office politics while optimizing workflows?

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Dan Mullin

Sales Solutions Consultant @ LinkedIn | Helping companies GTM on LinkedIn | Dad joke enthusiast

2w

This is great - what did you use for the graphic

Alex Cinovoj

AI Automation Architect | Voice AI | SMB Workflows | SaaS Builder | I help small business owners replace expensive admin labor and win more clients by building voice-powered AI agents that never miss a lead.

2w

Thanks for sharing, Manthan

Abdallah Haj Deeb Saken

CEO | Trismart Group | Visionary Leader in Technology, Infrastructure & Digital Transformation | IFC/JIoD Certified Director

2w

2025 is a new era in shaping the future with AI

Md Ayan

Tech Enthusiast | Exploring the Tech World with AI ML | Building EvolvX AI , NURA

2w

How do MCP and A2A address state synchronization and consistency across distributed AI agents and models ?

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