Microsoft supports A2A and MCP protocols, ushering in a new era for intelligent agents: when AI learns to "team up to fight monsters."

New Advances in Microsoft's Intelligent Agent Technology: From "Dialect Islands" to "Mandarin Revolution"#

Before the morning sun fully bathes Microsoft's headquarters in Seattle, engineers have already ignited the "Industrial Revolution" of the intelligent agent world with lines of code—Azure AI Foundry and Copilot Studio officially support A2A and MCP protocols. It's like unifying the Mandarin language for intelligent agents that originally spoke different dialects, allowing the "German-accented" financial robots in SAP systems and the "Silicon Valley-accented" collaboration assistants in Slack to finally sit at the same conference table and chat. (Imagine if Qin Shi Huang saw this scene, he would probably exclaim, "What was my unification of characters back then? This is true·same script!")

How powerful is the impact of this protocol revolution? In four months, 230,000 enterprises have settled in Copilot Studio, equivalent to 1,916 development teams "building Lego" on the Microsoft platform every day. Previously, integrating SAP and Oracle systems required three months of custom development; now, with the A2A protocol, it's as easy as creating a WeChat group—send a request @ the relevant intelligent agents, and in minutes, a "multinational task force" is formed. The MCP protocol is even comparable to equipping large models with a universal USB interface, calling external services is as simple as plugging in a USB drive, and mom no longer has to worry about my API integration.

A2A and MCP Protocols: The "WeChat" and "Mini Programs" of the Intelligent Agent World#

If we compare intelligent agents to workers, A2A is their corporate WeChat—specifically solving the problem of "who to find for work." Through standardized Agent Cards, each intelligent agent can showcase skill tags: for example, "proficient in SAP financial modules," "skilled in Slack message analysis." Need to procure internationally? Just create a group chat that includes the SAP procurement robot, Oracle inventory manager, and Teams communication assistant, @ everyone to send tasks, achieving efficiency that is more than ten times higher than human cross-timezone meetings.

MCP, on the other hand, is the "mini program store" for intelligent agents, specifically solving the problem of "how to use tools effectively." Previously, calling the PayPal interface with large models required writing 200 lines of adaptation code; now, it's like opening a "payment mini program" in WeChat, filling in a JSON parameter to complete the payment. A multinational company used this trick to connect 23 localized services for their customer service robot within two weeks—previously, this workload would have been enough to keep a team of programmers up all night.

2. Comparison of Old and New Technologies: From "Handcrafted Workshops" to "Smart Factories"#

Function Calling VS MCP
Function Calling is like a craftsman customizing tools—each LLM vendor has its own handle design (interface specification), and to chop vegetables, you first need to find a blacksmith (developer) to make the knife. MCP, however, directly invented the standardized Swiss Army knife, allowing any base model, whether GPT or Claude, to plug and play various tool modules. Data shows that after adopting MCP, the speed of functional integration increased fourfold, and the error rate dropped by 92%—this difference is comparable to the distinction between hand-peeling an apple and using an automatic peeler.

RAG VS A2A
RAG technology is like equipping a top student with a mobile library; when knowledge is needed, they flip through books for information. A2A, on the other hand, builds a circle of expert friends for the top student, allowing them to consult various experts directly online when faced with difficulties. A law firm's intelligent agent simultaneously employs both strategies: first using RAG to retrieve legal texts, then using A2A to create a group to consult the accounting robot on tax clauses, completing what originally required eight hours of contract review in just 20 minutes—truly the "strongest brain" combination in the AI realm.

3. Developer Delight: From "996 Firefighting" to "Coffee Time Innovation"#

Previously, developing cross-system intelligent agents was like laying railway tracks in a maze: SAP used ABAP language, Slack used Node.js, Oracle used PL/SQL... just connecting these three systems could give programmers three gray hairs. Now, A2A+MCP delivers a set of standardized tracks, allowing developers to focus solely on business logic. A bakery chain used ready-made modules to build an intelligent agent in three days, synchronously handling Meituan orders, inventory alerts, and employee scheduling—the boss joked, "At this efficiency, my dough rises slower than this!"

The "Swordplay" of Protocols: A2A vs ANP's Various Skills#

When the A2A protocol is making waves in the intelligent agent world, some always ask, "How is this different from IBM's ANP (Agent Negotiation Protocol) back in the day?" It's like asking which is better, WeChat or Telegram—though both are communication tools, their gameplay is worlds apart.

1. Martial Arts Competition vs Arranged Marriage#

ANP resembles a martial arts competition in ancient dramas, where each communication must undergo a complex process of "testing-offering-negotiating-signing." When two intelligent agents meet, they must first introduce themselves: "I am the SAP financial module, processing millions of orders annually, seeking to match with the Oracle inventory system..." Just establishing a connection consumes half a battery's worth of energy.

A2A, however, directly opens "flash marriage mode": through standardized Agent Cards, both parties instantly understand each other's skill trees, like scanning a QR code to add a WeChat friend and directly entering a work group—one logistics company tested that using A2A to connect warehouse robots and transportation systems was 17 times faster than ANP, leaving programmers so moved they exclaimed, "Finally, no more watching intelligent agents 'puffing each other up!'"

2. Swiss Army Knife vs Professional Tool Kit#

In complex negotiation scenarios, ANP indeed has unique skills. For instance, when a multinational trade intelligent agent needs to dynamically adjust tariff schemes, ANP's multi-round negotiation mechanism allows the buying and selling AIs to bargain like Wall Street traders. However, such "high-end scenarios" are as rare in reality as black hairs in a programmer's head—not absent, just scarce. In contrast, A2A's standardized interface is like equipping intelligent agents with NFC sensing chips: when Fujitsu's quality inspection robot encounters unfamiliar devices, it can directly "tap" to call the other party's data, providing a smooth experience that even ANP enthusiasts must admire.

3. Developer's Dilemma#

Using ANP is like hiring a private tailor to customize a suit—every stitch is meticulous but takes at least three months; whereas A2A is like walking into Uniqlo, getting a full set of intelligent agent "battle gear" in five minutes. Microsoft's developer logs show that implementing cross-platform negotiations with ANP requires an average of over 2,000 lines of code, while the equivalent functionality with A2A only requires calling three preset modules. No wonder some engineers joke, "Since using A2A, my Ctrl+C/V keys have gathered dust!"

4. Ecological Niche Competition#

Interestingly, this protocol battle is fostering new technological integrations. A certain e-commerce platform packaged ANP's "bargaining algorithm" as an MCP plugin, and after integrating into the A2A ecosystem, the promotion robot instantly gained "mind-reading" abilities—able to quickly connect to payment systems while also engaging in limited-time bargaining with customer agents. It's like equipping the Flash with Zhuge Liang's brain, helping the company earn an extra 200 million during the 618 sales period, with the marketing manager excitedly sending 20 red envelopes to the tech team (each worth 6.18 yuan).

Protocol Comparison Easter Egg

A2A: The "social butterfly" of the intelligent agent world, adept at organizing group play
ANP: The "old fox" at the negotiation table, specializing in interest games
MCP: The "Doraemon" in the tool library, providing whatever is needed
Traditional API: The "foreign friend" needing translation, communication relies entirely on gestures

The "Side Effects" of the Protocol Revolution: When AI Starts Taking Over the "Middleman" Jobs#

This wave of standardization has also brought interesting industry tremors:

System Integrators Turned Comedians: Vendors who previously relied on customized integrations are now turning to become protocol trainers (after all, their "unique skills" are no longer appealing post-standardization)
Programmers Enter "Lego Master" Mode: 70% of development time has shifted from writing code to selecting modules, with one developer joking, "Now going to work feels like playing 'Minecraft,' just missing giving the intelligent agents diamond armor!"
Corporate CIOs Suffering from "Choice Paralysis": With so many ready-made modules in the protocol ecosystem, choosing a payment interface is like ordering takeout—PayPal or Stripe? That's the question.

Future Outlook: When Protocols Become the "Air and Water" of Intelligent Agents#

Microsoft CEO Nadella predicts, "A2A+MCP will become the oxygen of the intelligent agent world, just as TCP/IP did for the internet." Already, 90% of the Fortune 500 have integrated this system, staging a real-life version of the "Avengers":

In Fujitsu's factory, quality inspection AI uses MCP to call robotic arms, increasing defect detection speed to the blink of a human eye.
PayPal's risk control intelligent agent consults logistics AI through A2A, with cross-border fraud identification rates soaring by 300%.
A certain hospital uses MCP+medical AI to achieve "one-stop service" for CT analysis, medical record retrieval, and drug recommendations, reducing patient wait times from 2 hours to 5 minutes.

The most exquisite aspect of this protocol revolution is that it is neither disruptive innovation nor incremental improvement, but rather like equipping the intelligent agent world with standardized screws—when all parts fit seamlessly, assembling rockets becomes as simple as building Lego. Perhaps looking back a decade from now, 2025 will be remembered as the "Year of Intelligent Agents," with A2A and MCP being the keys to opening a new era. Just like a netizen joked, "Humans ignited civilization with fire, now AI ignites wisdom with protocols—please bring an AI protocol package for the next industrial revolution!"

This "love-hate" relationship between protocols is a microcosm of the evolution of intelligent agent technology. As A2A breaks down barriers with standardization, ANP continues to delve deep in specific areas, and MCP quietly weaves a network of tools—they collectively paint an epic picture of AI transitioning from solitary combat to collaborative legions. Just like a Microsoft engineer wrote on GitHub's message board: "Don't ask which protocol is better; excellent intelligent agents, we need them all!"