Spaces:
Running
Running
File size: 72,688 Bytes
c8480c4 d6f0d3b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 |
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta name="description" content="A comprehensive guide to understanding AI protocols: Function Calling, MCP, and A2A - the building blocks of modern AI systems that enable tool usage, data access, and agent collaboration.">
<meta name="keywords" content="Function Calling, Model Context Protocol, MCP, Agent-to-Agent, A2A, AI protocols, AI integration, AI tools">
<title>Understanding AI Protocols: Function Calling, MCP, and A2A | The Future of AI Integration</title>
<link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/tailwind.min.css" rel="stylesheet">
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@fortawesome/[email protected]/css/all.min.css">
<style>
body {
font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
line-height: 1.6;
}
.protocol-card {
transition: transform 0.3s, box-shadow 0.3s;
}
.protocol-card:hover {
transform: translateY(-5px);
box-shadow: 0 15px 25px rgba(0, 0, 0, 0.1);
}
.diagram {
max-width: 100%;
height: auto;
border-radius: 8px;
margin: 20px 0;
border: 1px solid #e2e8f0;
}
.code-block {
font-family: 'Courier New', Courier, monospace;
white-space: pre-wrap;
word-break: break-all;
}
.hinglish {
color: #4f46e5;
font-style: italic;
}
.section-divider {
height: 4px;
background: linear-gradient(90deg, #6366f1, #8b5cf6, #d946ef);
border-radius: 2px;
margin: 30px 0;
}
.highlight-box {
border-left: 4px solid #6366f1;
padding-left: 1rem;
}
header {
background: linear-gradient(135deg, #4f46e5, #7c3aed);
color: white;
}
.gradient-text {
-webkit-background-clip: text;
background-clip: text;
color: transparent;
background-image: linear-gradient(90deg, #6366f1, #8b5cf6, #d946ef);
}
</style>
</head>
<body class="bg-gray-50">
<!-- Header Section -->
<header class="py-16 px-4 mb-8 bg-gradient-to-r from-blue-600 via-indigo-700 to-purple-800 text-white">
<div class="container mx-auto">
<div class="max-w-4xl mx-auto text-center">
<span class="inline-block px-3 py-1 bg-blue-500 bg-opacity-30 rounded-full text-sm font-semibold tracking-wider mb-4">THE FUTURE OF AI INTEGRATION</span>
<h1 class="text-4xl md:text-6xl font-bold mb-6 leading-tight">Understanding AI Protocols</h1>
<h2 class="text-xl md:text-2xl font-medium mb-8 text-blue-100">Function Calling, MCP, and A2A: The Building Blocks of Modern AI Systems</h2>
<p class="text-xl text-center max-w-3xl mx-auto text-gray-100">Discover how modern AI systems communicate and interact with the external world through these revolutionary protocols — explained with clarity and technical depth.</p>
<div class="mt-10">
<a href="#introduction" class="inline-block px-6 py-3 bg-white text-indigo-700 font-semibold rounded-lg shadow-md hover:bg-indigo-50 transition-colors mr-4">Start Reading</a>
<a href="#comparison" class="inline-block px-6 py-3 bg-transparent border-2 border-white text-white font-semibold rounded-lg hover:bg-white hover:bg-opacity-10 transition-colors">Compare Protocols</a>
</div>
</div>
</div>
</header>
<!-- Navigation Bar -->
<nav class="sticky top-0 bg-white shadow-md py-3 px-6 z-50 mb-8">
<div class="container mx-auto flex justify-between items-center">
<a href="#" class="font-bold text-xl text-indigo-700 hidden md:block">AI Protocol Guide</a>
<ul class="flex flex-wrap justify-center space-x-1 md:space-x-6 mx-auto md:mx-0">
<li><a href="#introduction" class="px-3 py-2 rounded-lg hover:bg-indigo-100 hover:text-indigo-700 transition-colors font-medium">Introduction</a></li>
<li><a href="#function-calling" class="px-3 py-2 rounded-lg hover:bg-indigo-100 hover:text-indigo-700 transition-colors font-medium">Function Calling</a></li>
<li><a href="#mcp" class="px-3 py-2 rounded-lg hover:bg-indigo-100 hover:text-indigo-700 transition-colors font-medium">MCP</a></li>
<li><a href="#a2a" class="px-3 py-2 rounded-lg hover:bg-indigo-100 hover:text-indigo-700 transition-colors font-medium">A2A</a></li>
<li><a href="#comparison" class="px-3 py-2 rounded-lg hover:bg-indigo-100 hover:text-indigo-700 transition-colors font-medium">Comparison</a></li>
<li><a href="#examples" class="px-3 py-2 rounded-lg hover:bg-indigo-100 hover:text-indigo-700 transition-colors font-medium">Examples</a></li>
</ul>
</div>
</nav>
<main class="container mx-auto px-4 mb-16">
<!-- Introduction Section -->
<section id="introduction" class="mb-16">
<h2 class="text-3xl font-bold mb-6 gradient-text">Introduction: How AI Gets Its Superpowers</h2>
<div class="bg-white rounded-xl shadow-md p-6 mb-8">
<p class="mb-4 text-lg">
You've likely used AI systems like ChatGPT or Claude, but have you ever wondered why they're limited to just conversation? Why can't they take meaningful actions in the real world? The fundamental limitation of traditional Large Language Models (LLMs) has been their inability to interact with the outside world - they can generate impressive text but can't directly impact their environment.
</p>
<p class="mb-4 text-lg">
This is where three revolutionary protocols are changing everything:
</p>
<div class="grid grid-cols-1 md:grid-cols-3 gap-6 mb-8">
<div class="protocol-card bg-blue-50 p-5 rounded-xl shadow-sm flex flex-col hover:shadow-lg transition-all duration-300">
<div class="text-blue-600 text-3xl mb-3"><i class="fas fa-wrench"></i></div>
<h3 class="text-xl font-bold mb-2">Function Calling</h3>
<p class="text-gray-700 flex-grow">
Teaching AI to use tools - Enabling models to recognize when to use external tools and APIs, and how to structure the necessary parameters.
</p>
</div>
<div class="protocol-card bg-purple-50 p-5 rounded-xl shadow-sm flex flex-col hover:shadow-lg transition-all duration-300">
<div class="text-purple-600 text-3xl mb-3"><i class="fas fa-database"></i></div>
<h3 class="text-xl font-bold mb-2">MCP (Model Context Protocol)</h3>
<p class="text-gray-700 flex-grow">
Connecting AI to data sources - Standardizing how AI systems access and interact with information repositories and external knowledge.
</p>
</div>
<div class="protocol-card bg-pink-50 p-5 rounded-xl shadow-sm flex flex-col hover:shadow-lg transition-all duration-300">
<div class="text-pink-600 text-3xl mb-3"><i class="fas fa-comments"></i></div>
<h3 class="text-xl font-bold mb-2">A2A (Agent-to-Agent)</h3>
<p class="text-gray-700 flex-grow">
Enabling AI collaboration - Creating a standardized way for different AI systems to communicate and work together regardless of their underlying frameworks.
</p>
</div>
</div>
<p class="text-lg">
Through these three technologies, AI systems are evolving from mere "smart chatbots" into genuine digital assistants capable of taking meaningful action in the world. These protocols represent the critical evolution from isolated models to interconnected, capable assistants that can understand, access information, and collaborate to solve complex problems.
</p>
<div class="mt-6 bg-blue-50 p-5 rounded-lg border-l-4 border-blue-500">
<h4 class="font-bold text-lg mb-2">Why This Matters</h4>
<p>These protocols aren't just technical specifications—they're the foundation of a new era in AI capability. As they mature and become widely adopted, we'll see AI systems that can seamlessly integrate with our digital infrastructure, access the information they need, and collaborate with specialized systems to accomplish complex tasks that no single AI could handle alone.</p>
</div>
</div>
</section>
<div class="section-divider"></div>
<!-- Function Calling Section -->
<section id="function-calling" class="mb-16">
<h2 class="text-3xl font-bold mb-6 gradient-text">Function Calling: Giving AI Tools to Work With</h2>
<div class="bg-white rounded-xl shadow-md p-6 mb-8">
<h3 class="text-2xl font-semibold mb-4">Basic Concept: What is Function Calling?</h3>
<p class="mb-4 text-lg">
Function calling is the ability for an AI model to recognize when it needs to use an external tool or API, and to generate the proper structured arguments for that function call. It's essentially teaching AI when and how to use tools to accomplish tasks beyond simple text generation.
</p>
<div class="bg-blue-50 p-6 rounded-lg mb-6 border-l-4 border-blue-500">
<h4 class="text-xl font-bold mb-3">Analogy: The New Intern</h4>
<p class="text-lg">
Imagine you've hired a new intern at your office. You've shown them all the available tools - Excel for spreadsheets, Email for communication, the printer for documents, etc. Now, whenever a task comes up, the intern decides which tool is appropriate. If they need to create a report, they use Excel. If they need to send a message, they use Email.
</p>
<p class="text-lg mt-3">
Similarly, with function calling, you tell the AI what functions are available (along with their descriptions and required parameters), and the AI decides when to use them and with what parameters based on the user's request.
</p>
</div>
<h3 class="text-2xl font-semibold mb-4">How Function Calling Works</h3>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6 mb-6">
<div>
<ol class="list-decimal pl-6 space-y-3">
<li class="text-lg">
<strong>Define Functions:</strong> Developers define available functions with their names, descriptions, and required parameters.
</li>
<li class="text-lg">
<strong>User Input:</strong> A user asks a question like "What's the weather in London?"
</li>
<li class="text-lg">
<strong>AI Analysis:</strong> The AI recognizes this requires external data and determines the weather function is appropriate.
</li>
<li class="text-lg">
<strong>Parameter Generation:</strong> The AI structures the necessary parameters (location="London").
</li>
<li class="text-lg">
<strong>Function Execution:</strong> Your system executes the function (calls the weather API).
</li>
<li class="text-lg">
<strong>Response Integration:</strong> The AI incorporates the result into a natural, conversational response.
</li>
</ol>
</div>
<div class="bg-white rounded-lg shadow-md p-4">
<h4 class="text-lg font-semibold mb-2">Visual Representation:</h4>
<div class="diagram bg-blue-50 p-4 rounded-lg">
<pre class="code-block text-sm">
┌─────────────┐ ┌─────────────┐ ┌─────────────┐
│ │ │ │ │ │
│ User │─────▶│ AI Model │─────▶│ Function │
│ │ asks │ │ calls│ │
└─────────────┘ └─────────────┘ └─────────────┘
│ │
│ │
▼ ▼
"I need to use function_name()
the weather parameters
function"
│
│
▼
┌─────────────┐
│ │
│ Result │
│ │
└─────────────┘
│
│
▼
┌─────────────┐
│ │
│ AI Response │
│ │
└─────────────┘
</pre>
</div>
</div>
</div>
<h3 class="text-2xl font-semibold mb-4">Technical Implementation: Function Definition</h3>
<p class="mb-4 text-lg">
Functions are defined in JSON Schema format, providing the AI with a clear structure of available tools:
</p>
<div class="bg-gray-100 p-4 rounded-lg mb-6 overflow-x-auto shadow-inner">
<pre class="code-block text-sm">
{
"name": "get_weather",
"description": "Get current weather for a specific location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "City name (e.g., London, New York, Tokyo)"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"description": "Temperature unit"
}
},
"required": ["location"]
}
}</pre>
</div>
<h3 class="text-2xl font-semibold mb-4">Function Call Output</h3>
<p class="mb-4 text-lg">
When the AI determines a function call is needed, it generates a structured output like this:
</p>
<div class="bg-gray-100 p-4 rounded-lg mb-6 overflow-x-auto shadow-inner">
<pre class="code-block text-sm">
{
"function": "get_weather",
"parameters": {
"location": "London",
"unit": "celsius"
}
}</pre>
</div>
<h3 class="text-2xl font-semibold mb-4">Advantages and Limitations</h3>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6 mb-6">
<div class="bg-green-50 p-5 rounded-lg border border-green-200 hover:shadow-md transition-all duration-300">
<h4 class="font-bold text-lg mb-2 text-green-800">Advantages</h4>
<ul class="list-disc pl-5 space-y-2">
<li><strong>Easy implementation:</strong> Simple to set up with most AI APIs</li>
<li><strong>Direct integration:</strong> Works within existing LLM frameworks</li>
<li><strong>Flexibility:</strong> Can connect to virtually any API or service</li>
<li><strong>Structured output:</strong> Guarantees valid parameter formats</li>
<li><strong>Rapid adoption:</strong> Widely supported across major AI providers</li>
</ul>
</div>
<div class="bg-red-50 p-5 rounded-lg border border-red-200 hover:shadow-md transition-all duration-300">
<h4 class="font-bold text-lg mb-2 text-red-800">Limitations</h4>
<ul class="list-disc pl-5 space-y-2">
<li><strong>Tight coupling:</strong> Function logic embedded in AI reasoning</li>
<li><strong>Limited interoperability:</strong> Not standardized across systems</li>
<li><strong>Scaling challenges:</strong> Complex with many functions</li>
<li><strong>Vendor dependence:</strong> Implementation varies by AI provider</li>
<li><strong>Limited context:</strong> Functions may lack broader system awareness</li>
</ul>
</div>
</div>
<h3 class="text-2xl font-semibold mb-4">Real-World Applications</h3>
<div class="grid grid-cols-1 md:grid-cols-3 gap-4 mb-6">
<div class="bg-blue-50 p-4 rounded-lg hover:shadow-md transition-all duration-300">
<div class="text-blue-600 text-xl mb-2"><i class="fas fa-calendar-alt"></i></div>
<h4 class="font-bold mb-1">Calendar Management</h4>
<p>Scheduling meetings, setting reminders, and managing appointments based on natural language requests.</p>
</div>
<div class="bg-blue-50 p-4 rounded-lg hover:shadow-md transition-all duration-300">
<div class="text-blue-600 text-xl mb-2"><i class="fas fa-shopping-cart"></i></div>
<h4 class="font-bold mb-1">E-commerce</h4>
<p>Searching for products, checking inventory, and placing orders through conversational interfaces.</p>
</div>
<div class="bg-blue-50 p-4 rounded-lg hover:shadow-md transition-all duration-300">
<div class="text-blue-600 text-xl mb-2"><i class="fas fa-cloud-sun"></i></div>
<h4 class="font-bold mb-1">Information Retrieval</h4>
<p>Fetching weather forecasts, news updates, stock prices, and other real-time data on demand.</p>
</div>
</div>
<div class="mt-6 bg-indigo-50 p-5 rounded-lg border-l-4 border-indigo-500">
<h4 class="font-bold text-lg mb-2">Historical Context</h4>
<p>Function calling was first introduced by OpenAI in June 2023, marking a significant advancement in making AI systems more useful for practical applications. Since then, it has been widely adopted across the industry and has become a fundamental capability in modern AI systems.</p>
</div>
</div>
</section>
<div class="section-divider"></div>
<!-- MCP Section -->
<section id="mcp" class="mb-16">
<h2 class="text-3xl font-bold mb-6 gradient-text">Model Context Protocol (MCP): The Universal Data Connector</h2>
<div class="bg-white rounded-xl shadow-md p-6 mb-8">
<h3 class="text-2xl font-semibold mb-4">Basic Concept: What is MCP?</h3>
<p class="mb-4 text-lg">
The Model Context Protocol (MCP) is an open standard designed to connect AI systems with various data sources in a standardized way. Developed by Anthropic in November 2024, MCP creates a universal interface for AI systems to access content repositories, business tools, and development environments without custom integrations for each source.
</p>
<div class="bg-purple-50 p-6 rounded-lg mb-6 border-l-4 border-purple-500">
<h4 class="text-xl font-bold mb-3">Analogy: The Universal Port</h4>
<p class="text-lg">
Think of MCP as the USB-C port of the AI world. Just as your laptop can connect to any device—monitors, hard drives, phones—through a single standardized USB-C port, MCP allows AI systems to connect to any data source—Google Drive, GitHub, databases, etc.—through a single standardized protocol.
</p>
<p class="text-lg mt-3">
This standardization eliminates the need for custom integrations with each data source, dramatically simplifying how AI systems access and interact with external information.
</p>
</div>
<h3 class="text-2xl font-semibold mb-4">How MCP Works</h3>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6 mb-6">
<div>
<h4 class="text-lg font-semibold mb-2">MCP Architecture:</h4>
<ol class="list-decimal pl-6 space-y-3">
<li class="text-lg">
<strong>MCP Hosts:</strong> Applications like Claude Desktop or AI tools that need to access external data
</li>
<li class="text-lg">
<strong>MCP Clients:</strong> Protocol clients that maintain connections with MCP servers
</li>
<li class="text-lg">
<strong>MCP Servers:</strong> Lightweight programs that expose specific capabilities through the MCP protocol
</li>
<li class="text-lg">
<strong>Data Sources:</strong> Local files, databases, or remote services that MCP servers connect to
</li>
</ol>
</div>
<div class="bg-white rounded-lg shadow-md p-4">
<h4 class="text-lg font-semibold mb-2">Visual Representation:</h4>
<div class="diagram bg-purple-50 p-4 rounded-lg">
<pre class="code-block text-sm">
┌──────────────┐ ┌──────────────┐
│ │ │ │
│ AI Model │◄─────►│ MCP Client │
│ (Claude, etc)│ │ │
└──────────────┘ └──────────────┘
│
│ MCP Protocol
▼
┌─────────────────────────────────┐
│ │
│ MCP Servers │
│ │
└─────────────────────────────────┘
│ │ │
│ │ │
▼ ▼ ▼
┌─────────┐ ┌─────────┐ ┌─────────┐
│ │ │ │ │ │
│ Google │ │ GitHub │ │ Custom │
│ Drive │ │ Server │ │ Database│
│ │ │ │ │ │
└─────────┘ └─────────┘ └─────────┘</pre>
</div>
</div>
</div>
<h3 class="text-2xl font-semibold mb-4">Technical Implementation</h3>
<p class="mb-4 text-lg">
The communication between MCP servers and clients follows a standardized HTTP-based protocol. Here's how it works in practice:
</p>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6 mb-6">
<div class="bg-gray-100 p-4 rounded-lg overflow-x-auto shadow-inner">
<h4 class="font-bold mb-2">MCP Server Request Example:</h4>
<pre class="code-block text-sm">
POST /v1/service/files/list HTTP/1.1
Content-Type: application/json
{
"path": "/documents/project-alpha",
"recursive": true,
"include_content": false
}</pre>
</div>
<div class="bg-gray-100 p-4 rounded-lg overflow-x-auto shadow-inner">
<h4 class="font-bold mb-2">MCP Server Response Example:</h4>
<pre class="code-block text-sm">
HTTP/1.1 200 OK
Content-Type: application/json
{
"files": [
{
"name": "requirements.txt",
"path": "/documents/project-alpha/requirements.txt",
"type": "file",
"size": 1245,
"last_modified": "2023-09-15T14:32:10Z"
},
{
"name": "README.md",
"path": "/documents/project-alpha/README.md",
"type": "file",
"size": 8732,
"last_modified": "2023-09-10T09:15:22Z"
}
]
}</pre>
</div>
</div>
<h3 class="text-2xl font-semibold mb-4">Advantages and Limitations</h3>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6 mb-6">
<div class="bg-green-50 p-5 rounded-lg border border-green-200 hover:shadow-md transition-all duration-300">
<h4 class="font-bold text-lg mb-2 text-green-800">Advantages</h4>
<ul class="list-disc pl-5 space-y-2">
<li><strong>Clean separation:</strong> Decouples AI models from data sources</li>
<li><strong>Standardized protocol:</strong> Ensures consistent data exchange patterns</li>
<li><strong>Universal connectivity:</strong> One protocol for multiple data sources</li>
<li><strong>Enhanced security:</strong> Data remains within controlled infrastructure</li>
<li><strong>Vendor flexibility:</strong> Switch between AI providers without changing data access</li>
<li><strong>Privacy-preserving:</strong> Minimizes data exposure to external systems</li>
</ul>
</div>
<div class="bg-red-50 p-5 rounded-lg border border-red-200 hover:shadow-md transition-all duration-300">
<h4 class="font-bold text-lg mb-2 text-red-800">Limitations</h4>
<ul class="list-disc pl-5 space-y-2">
<li><strong>Primarily data-focused:</strong> Better for data access than complex interactions</li>
<li><strong>Emerging ecosystem:</strong> Still developing comprehensive tooling</li>
<li><strong>Implementation complexity:</strong> Requires more setup than simple function calling</li>
<li><strong>Learning curve:</strong> New paradigm for many developers</li>
<li><strong>Adoption challenges:</strong> Requires ecosystem buy-in to reach full potential</li>
</ul>
</div>
</div>
<h3 class="text-2xl font-semibold mb-4">Real-World Applications</h3>
<div class="grid grid-cols-1 md:grid-cols-3 gap-4 mb-6">
<div class="bg-purple-50 p-4 rounded-lg hover:shadow-md transition-all duration-300">
<div class="text-purple-600 text-xl mb-2"><i class="fas fa-code"></i></div>
<h4 class="font-bold mb-1">IDE Integration</h4>
<p>Accessing code repositories to assist with development, providing context-aware suggestions, and helping navigate complex codebases.</p>
</div>
<div class="bg-purple-50 p-4 rounded-lg hover:shadow-md transition-all duration-300">
<div class="text-purple-600 text-xl mb-2"><i class="fas fa-building"></i></div>
<h4 class="font-bold mb-1">Enterprise Data</h4>
<p>Extracting information from company documents and internal knowledge bases while maintaining security and access controls.</p>
</div>
<div class="bg-purple-50 p-4 rounded-lg hover:shadow-md transition-all duration-300">
<div class="text-purple-600 text-xl mb-2"><i class="fas fa-database"></i></div>
<h4 class="font-bold mb-1">Knowledge Management</h4>
<p>Collecting data from different sources to provide a unified view, enabling AI to synthesize information across repositories.</p>
</div>
</div>
<div class="mt-6 bg-purple-50 p-5 rounded-lg border-l-4 border-purple-500">
<h4 class="font-bold text-lg mb-2">MCP Ecosystem</h4>
<p class="text-lg">
The MCP ecosystem is growing rapidly with pre-built servers already available for many popular services including Google Drive, Slack, GitHub, Git, Postgres, and Puppeteer. Major companies like Block and Apollo have already integrated MCP into their systems, demonstrating its enterprise readiness.
</p>
<p class="mt-3">
As the protocol matures, we can expect to see an explosion of MCP servers for various data sources, making it increasingly easy for AI systems to access the information they need in a standardized way.
</p>
</div>
<div class="mt-6 bg-indigo-50 p-5 rounded-lg border-l-4 border-indigo-500">
<h4 class="font-bold text-lg mb-2">Historical Context</h4>
<p>The Model Context Protocol was launched by Anthropic in November 2024, marking a significant step forward in standardizing how AI systems access external data. It represents a shift from the ad-hoc integrations of early AI systems toward a more structured, interoperable approach to AI-data connectivity.</p>
</div>
</div>
</section>
<div class="section-divider"></div>
<!-- A2A Section -->
<section id="a2a" class="mb-16">
<h2 class="text-3xl font-bold mb-6 gradient-text">Agent-to-Agent (A2A): Enabling AI Collaboration</h2>
<div class="bg-white rounded-xl shadow-md p-6 mb-8">
<h3 class="text-2xl font-semibold mb-4">Basic Concept: What is A2A?</h3>
<p class="mb-4 text-lg">
The Agent-to-Agent (A2A) protocol is an open standard developed by Google in April 2025 that enables communication between different AI agents, regardless of which framework or vendor created them. A2A facilitates secure, standardized communication between independent AI systems, allowing them to collaborate on complex tasks.
</p>
<div class="bg-pink-50 p-6 rounded-lg mb-6 border-l-4 border-pink-500">
<h4 class="text-xl font-bold mb-3">Analogy: The Universal Phone Network</h4>
<p class="text-lg">
Think of A2A as the cellular network of the AI world. Just as phones from different manufacturers—iPhones, Samsung, Xiaomi—can all communicate with each other through a standardized cellular protocol, A2A allows AI agents built by different companies and frameworks to seamlessly communicate with one another.
</p>
<p class="text-lg mt-3">
This universal communication layer means that specialized AI agents can work together regardless of who built them or what underlying technology they use. Just as you don't need to worry about whether your friend has the same phone brand when calling them, with A2A, AI systems don't need to be built on the same framework to collaborate effectively.
</p>
</div>
<h3 class="text-2xl font-semibold mb-4">How A2A Works</h3>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6 mb-6">
<div>
<h4 class="text-lg font-semibold mb-2">Key Components:</h4>
<ol class="list-decimal pl-6 space-y-3">
<li class="text-lg">
<strong>Agent Cards:</strong> Public metadata files that describe an agent's capabilities, skills, and endpoint URL, enabling discovery and interaction
</li>
<li class="text-lg">
<strong>A2A Server:</strong> An agent that implements the A2A protocol methods and can receive and process requests from other agents
</li>
<li class="text-lg">
<strong>A2A Client:</strong> An application or agent that consumes A2A services by sending requests to A2A servers
</li>
<li class="text-lg">
<strong>Tasks:</strong> Work units that progress through different states (submitted, working, completed, etc.) as they're processed by agents
</li>
<li class="text-lg">
<strong>Messages:</strong> Communication turns containing various content types including text, structured data, forms, and media
</li>
</ol>
</div>
<div class="bg-white rounded-lg shadow-md p-4">
<h4 class="text-lg font-semibold mb-2">Visual Representation:</h4>
<div class="diagram bg-pink-50 p-4 rounded-lg">
<pre class="code-block text-sm">
┌───────────────┐ ┌───────────────┐
│ │ │ │
│ Agent A │ │ Agent B │
│ (LangChain) │ │ (CrewAI) │
│ │ │ │
└───────┬───────┘ └───────┬───────┘
│ │
│ │
│ │
│ │
▼ ▼
┌───────────────┐ ┌───────────────┐
│ │ A2A │ │
│ A2A Client │◄────Protocol─────►│ A2A Server │
│ │ │ │
└───────────────┘ └───────────────┘
▲
│
│
│
┌──────┴──────┐
│ │
│ Agent Card │
│ │
└─────────────┘</pre>
</div>
</div>
</div>
<h3 class="text-2xl font-semibold mb-4">Technical Implementation</h3>
<p class="mb-4 text-lg">
The technical implementation of A2A involves several key components that work together to enable seamless agent communication:
</p>
<div class="grid grid-cols-1 gap-6 mb-6">
<div class="bg-gray-100 p-4 rounded-lg overflow-x-auto shadow-inner">
<h4 class="font-bold mb-2">Agent Card Example (/.well-known/agent.json):</h4>
<pre class="code-block text-sm">
{
"name": "Travel Planning Agent",
"version": "1.0.0",
"description": "An agent that helps plan travel itineraries",
"endpoint": "https://travel-agent.example.com/a2a",
"capabilities": ["streaming", "pushNotifications"],
"auth": {
"type": "bearer"
},
"skills": [
{
"name": "flight_search",
"description": "Search for flights between airports on specific dates"
},
{
"name": "hotel_booking",
"description": "Find and book hotels in various destinations"
}
]
}</pre>
</div>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6">
<div class="bg-gray-100 p-4 rounded-lg overflow-x-auto shadow-inner">
<h4 class="font-bold mb-2">A2A Task Request Example:</h4>
<pre class="code-block text-sm">
POST /a2a/tasks/send HTTP/1.1
Content-Type: application/json
{
"taskId": "task_12345",
"message": {
"role": "user",
"parts": [
{
"text": "I need to plan a trip to Goa next month"
}
]
}
}</pre>
</div>
<div class="bg-gray-100 p-4 rounded-lg overflow-x-auto shadow-inner">
<h4 class="font-bold mb-2">A2A Task Response Example:</h4>
<pre class="code-block text-sm">
HTTP/1.1 200 OK
Content-Type: application/json
{
"task": {
"taskId": "task_12345",
"status": "working",
"messages": [
{
"role": "user",
"parts": [
{
"text": "I need to plan a trip to Goa next month"
}
]
},
{
"role": "agent",
"parts": [
{
"text": "I'll help you plan your trip to Goa! To get started, could you please provide:"
},
{
"data": {
"form": {
"fields": [
{"name": "travel_dates", "label": "When exactly are you planning to travel?"},
{"name": "budget", "label": "What's your approximate budget?"},
{"name": "interests", "label": "What activities are you interested in?"}
]
}
}
}
]
}
]
}
}</pre>
</div>
</div>
</div>
<h3 class="text-2xl font-semibold mb-4">Advantages and Limitations</h3>
<div class="grid grid-cols-1 md:grid-cols-2 gap-6 mb-6">
<div class="bg-green-50 p-5 rounded-lg border border-green-200 hover:shadow-md transition-all duration-300">
<h4 class="font-bold text-lg mb-2 text-green-800">Advantages</h4>
<ul class="list-disc pl-5 space-y-2">
<li><strong>Framework-agnostic:</strong> Works across different AI frameworks and platforms</li>
<li><strong>Rich communication:</strong> Supports text, forms, files, audio/video, and structured data</li>
<li><strong>Enterprise-ready:</strong> Secure, cross-organizational collaboration with authentication</li>
<li><strong>Capability discovery:</strong> Agents can advertise their abilities through Agent Cards</li>
<li><strong>Real-time updates:</strong> Streaming support for complex, long-running tasks</li>
<li><strong>Standardized protocol:</strong> Consistent implementation across different systems</li>
</ul>
</div>
<div class="bg-red-50 p-5 rounded-lg border border-red-200 hover:shadow-md transition-all duration-300">
<h4 class="font-bold text-lg mb-2 text-red-800">Limitations</h4>
<ul class="list-disc pl-5 space-y-2">
<li><strong>Complex implementation:</strong> More involved setup compared to simpler protocols</li>
<li><strong>Nascent ecosystem:</strong> Still early in adoption cycle with evolving standards</li>
<li><strong>Higher overhead:</strong> Requires more infrastructure and computational resources</li>
<li><strong>Coordination challenges:</strong> Managing complex multi-agent workflows</li>
<li><strong>Security considerations:</strong> Requires careful implementation of authentication</li>
</ul>
</div>
</div>
<h3 class="text-2xl font-semibold mb-4">Real-World Applications</h3>
<div class="grid grid-cols-1 md:grid-cols-3 gap-4 mb-6">
<div class="bg-pink-50 p-4 rounded-lg hover:shadow-md transition-all duration-300">
<div class="text-pink-600 text-xl mb-2"><i class="fas fa-users"></i></div>
<h4 class="font-bold mb-1">Multi-Agent Systems</h4>
<p>Dividing complex tasks between multiple specialized agents, allowing each to focus on their area of expertise while collaborating on the overall solution.</p>
</div>
<div class="bg-pink-50 p-4 rounded-lg hover:shadow-md transition-all duration-300">
<div class="text-pink-600 text-xl mb-2"><i class="fas fa-building"></i></div>
<h4 class="font-bold mb-1">Cross-Organization</h4>
<p>Enabling secure collaboration between AI agents from different companies or departments, while maintaining appropriate access controls and data privacy.</p>
</div>
<div class="bg-pink-50 p-4 rounded-lg hover:shadow-md transition-all duration-300">
<div class="text-pink-600 text-xl mb-2"><i class="fas fa-project-diagram"></i></div>
<h4 class="font-bold mb-1">Workflow Automation</h4>
<p>Automating complex business processes by coordinating specialized agents that handle different aspects of the workflow, from data processing to decision-making.</p>
</div>
</div>
<div class="mt-6 bg-pink-50 p-5 rounded-lg border-l-4 border-pink-500">
<h4 class="font-bold text-lg mb-2">A2A Support for Major Frameworks</h4>
<p class="text-lg">
A2A protocol is already supported by major AI frameworks including LangGraph, CrewAI, Semantic Kernel, Marvin, Genkit, and LlamaIndex. This widespread adoption makes it easier for developers to build interoperable multi-agent systems without worrying about compatibility issues.
</p>
<p class="mt-3">
As the protocol continues to mature, we can expect to see even more frameworks and platforms adding A2A support, further expanding the ecosystem of collaborative AI agents.
</p>
</div>
<div class="mt-6 bg-indigo-50 p-5 rounded-lg border-l-4 border-indigo-500">
<h4 class="font-bold text-lg mb-2">Historical Context</h4>
<p>The Agent-to-Agent protocol was launched by Google in April 2025 at Google Cloud Next, representing the next evolutionary step in AI system integration. While Function Calling enabled tool use and MCP standardized data access, A2A completes the picture by enabling AI systems to work together in coordinated teams, much like human specialists collaborate on complex projects.</p>
</div>
</div>
</section>
<div class="section-divider"></div>
<!-- Comparison Section -->
<section id="comparison" class="mb-16">
<h2 class="text-3xl font-bold mb-6 gradient-text">Comparison: Understanding the Protocol Ecosystem</h2>
<div class="bg-white rounded-xl shadow-md p-6 mb-8">
<div class="overflow-x-auto">
<table class="w-full text-left border-collapse shadow-lg">
<thead>
<tr class="bg-gradient-to-r from-blue-100 via-purple-100 to-pink-100">
<th class="p-4 border border-gray-300">Feature</th>
<th class="p-4 border border-gray-300 text-blue-700">Function Calling</th>
<th class="p-4 border border-gray-300 text-purple-700">MCP</th>
<th class="p-4 border border-gray-300 text-pink-700">A2A</th>
</tr>
</thead>
<tbody>
<tr class="hover:bg-gray-50 transition-colors">
<td class="p-4 border border-gray-300 font-semibold bg-gray-50">Primary Purpose</td>
<td class="p-4 border border-gray-300">Tool usage and external function execution</td>
<td class="p-4 border border-gray-300">Standardized data access and retrieval</td>
<td class="p-4 border border-gray-300">Agent-to-agent communication and collaboration</td>
</tr>
<tr class="hover:bg-gray-50 transition-colors">
<td class="p-4 border border-gray-300 font-semibold bg-gray-50">Developed By</td>
<td class="p-4 border border-gray-300">OpenAI (June 2023), later adopted by Anthropic and others</td>
<td class="p-4 border border-gray-300">Anthropic (November 2024)</td>
<td class="p-4 border border-gray-300">Google (April 2025)</td>
</tr>
<tr class="hover:bg-gray-50 transition-colors">
<td class="p-4 border border-gray-300 font-semibold bg-gray-50">Architecture</td>
<td class="p-4 border border-gray-300">Direct model-to-function integration</td>
<td class="p-4 border border-gray-300">Client-server architecture</td>
<td class="p-4 border border-gray-300">Distributed agent-to-agent network</td>
</tr>
<tr class="hover:bg-gray-50 transition-colors">
<td class="p-4 border border-gray-300 font-semibold bg-gray-50">Standardization</td>
<td class="p-4 border border-gray-300">Limited - Vendor-specific implementations</td>
<td class="p-4 border border-gray-300">High - Open protocol with consistent standards</td>
<td class="p-4 border border-gray-300">High - Open protocol with formal specification</td>
</tr>
<tr class="hover:bg-gray-50 transition-colors">
<td class="p-4 border border-gray-300 font-semibold bg-gray-50">Communication</td>
<td class="p-4 border border-gray-300">One-way (model identifies and calls functions)</td>
<td class="p-4 border border-gray-300">Two-way (client-server interaction)</td>
<td class="p-4 border border-gray-300">Multi-directional (agent network communication)</td>
</tr>
<tr class="hover:bg-gray-50 transition-colors">
<td class="p-4 border border-gray-300 font-semibold bg-gray-50">Discovery</td>
<td class="p-4 border border-gray-300">Not built-in (functions must be pre-defined)</td>
<td class="p-4 border border-gray-300">Via MCP servers and service discovery</td>
<td class="p-4 border border-gray-300">Via Agent Cards and capability advertising</td>
</tr>
<tr class="hover:bg-gray-50 transition-colors">
<td class="p-4 border border-gray-300 font-semibold bg-gray-50">Implementation Complexity</td>
<td class="p-4 border border-gray-300">Low - Simple JSON schema definitions</td>
<td class="p-4 border border-gray-300">Medium - Requires server setup and configuration</td>
<td class="p-4 border border-gray-300">High - Involves complex agent coordination</td>
</tr>
<tr class="hover:bg-gray-50 transition-colors">
<td class="p-4 border border-gray-300 font-semibold bg-gray-50">Best For</td>
<td class="p-4 border border-gray-300">Simple tool integration and single-agent tasks</td>
<td class="p-4 border border-gray-300">Enterprise data access and knowledge retrieval</td>
<td class="p-4 border border-gray-300">Complex multi-agent systems and workflows</td>
</tr>
</tbody>
</table>
</div>
<h3 class="text-2xl font-semibold mt-8 mb-4">Evolution Timeline</h3>
<div class="relative bg-gray-100 p-4 rounded-lg my-6">
<div class="h-2 bg-gradient-to-r from-blue-500 via-purple-500 to-pink-500 rounded-full mb-6"></div>
<div class="grid grid-cols-3 gap-4">
<div class="text-center">
<div class="bg-blue-100 rounded-full h-12 w-12 flex items-center justify-center mx-auto mb-2">
<i class="fas fa-wrench text-blue-600"></i>
</div>
<h4 class="font-bold mb-1">Function Calling</h4>
<p class="text-sm">Basic tool usage</p>
<p class="text-xs text-gray-500">(Launched June 2023)</p>
</div>
<div class="text-center">
<div class="bg-purple-100 rounded-full h-12 w-12 flex items-center justify-center mx-auto mb-2">
<i class="fas fa-database text-purple-600"></i>
</div>
<h4 class="font-bold mb-1">MCP</h4>
<p class="text-sm">Standardized data access</p>
<p class="text-xs text-gray-500">(Launched Nov 2024)</p>
</div>
<div class="text-center">
<div class="bg-pink-100 rounded-full h-12 w-12 flex items-center justify-center mx-auto mb-2">
<i class="fas fa-comments text-pink-600"></i>
</div>
<h4 class="font-bold mb-1">A2A</h4>
<p class="text-sm">Agent communication</p>
<p class="text-xs text-gray-500">(Launched April 2025)</p>
</div>
</div>
</div>
<h3 class="text-2xl font-semibold mb-4">How They Work Together</h3>
<p class="mb-4 text-lg">
These three technologies are complementary rather than competitive - they don't replace each other but instead work together. In fact, a sophisticated AI system might leverage all three protocols simultaneously to achieve maximum capability:
</p>
<div class="bg-gradient-to-r from-blue-50 via-purple-50 to-pink-50 p-6 rounded-lg mb-6 shadow-md">
<h4 class="text-xl font-bold mb-3">Complementary Nature</h4>
<ul class="list-disc pl-6 space-y-2 text-lg">
<li><strong>Function Calling</strong> provides the basic mechanics for a single agent to use tools and APIs, forming the foundation of AI capability</li>
<li><strong>MCP</strong> standardizes how agents access external data sources, enabling consistent information retrieval across different repositories</li>
<li><strong>A2A</strong> enables those agents to communicate with other specialized agents, creating collaborative networks of AI systems</li>
</ul>
<div class="mt-6">
<h5 class="font-semibold mb-2">Example Integration:</h5>
<div class="diagram bg-white p-4 rounded-lg">
<pre class="code-block text-sm">
┌───────────────────────────────────────────────────────────┐
│ User Request │
└───────────────────────┬───────────────────────────────────┘
│
▼
┌───────────────────────────────────────────────────────────┐
│ Primary Agent │
│ │
│ ┌─────────────────┐ ┌────────────────┐ │
│ │ Function Calling│ │ MCP │ │
│ │ (Tool Use) │ │ (Data Access) │ │
│ └─────────────────┘ └────────────────┘ │
└──────────────────────────┬────────────────────────────────┘
│
│ A2A Protocol
▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│ │ │ │ │ │
│ Specialist │ │ Specialist │ │ Specialist │
│ Agent A │ │ Agent B │ │ Agent C │
│ │ │ │ │ │
└─────────────────┘ └─────────────────┘ └─────────────────┘</pre>
</div>
</div>
</div>
<div class="mt-8 bg-indigo-50 p-6 rounded-lg border-l-4 border-indigo-500">
<h4 class="text-xl font-bold mb-3">The Future of AI Integration</h4>
<p class="text-lg">
As these protocols continue to mature and gain wider adoption, we're witnessing the emergence of a new paradigm in AI system design. Rather than monolithic models trying to do everything, we're moving toward ecosystems of specialized AI agents that can seamlessly work together through standardized protocols.
</p>
<p class="text-lg mt-3">
This shift mirrors how human organizations work - with specialists in different domains collaborating to solve complex problems. The combination of Function Calling, MCP, and A2A creates the foundation for truly capable AI systems that can understand user needs, access relevant information, and coordinate specialized expertise to deliver comprehensive solutions.
</p>
</div>
</div>
</section>
<div class="section-divider"></div>
<!-- Real-World Examples Section -->
<section id="examples" class="mb-16">
<h2 class="text-3xl font-bold mb-6 gradient-text">Real-World Examples: Practical Applications in Action</h2>
<div class="bg-white rounded-xl shadow-md p-6 mb-8">
<div class="grid grid-cols-1 md:grid-cols-3 gap-8">
<!-- Function Calling Example -->
<div class="bg-blue-50 p-6 rounded-xl">
<div class="text-blue-600 text-3xl mb-4"><i class="fas fa-calendar-check"></i></div>
<h3 class="text-xl font-bold mb-3">Function Calling Example</h3>
<h4 class="font-semibold mb-2">Meeting Scheduler</h4>
<div class="bg-white rounded-lg p-4 mb-4">
<p class="italic mb-2">User asks:</p>
<p class="bg-gray-100 p-3 rounded">"Schedule a meeting with the marketing team next Tuesday at 2 PM about the new campaign."</p>
</div>
<div class="bg-blue-100 p-4 rounded-lg mb-4">
<p class="font-semibold mb-1">AI identifies:</p>
<ul class="list-disc pl-5 space-y-1">
<li>Need to create calendar event</li>
<li>Calls <code>create_meeting</code> function</li>
<li>Passes attendees, time, topic details</li>
</ul>
</div>
<div class="bg-white rounded-lg p-4">
<p class="italic mb-2">AI responds:</p>
<p class="bg-gray-100 p-3 rounded">"I've scheduled a meeting with the marketing team for Tuesday, May 3rd at 2:00 PM titled 'New Campaign Discussion'. Calendar invites have been sent to all team members."</p>
</div>
</div>
<!-- MCP Example -->
<div class="bg-purple-50 p-6 rounded-xl">
<div class="text-purple-600 text-3xl mb-4"><i class="fas fa-code-branch"></i></div>
<h3 class="text-xl font-bold mb-3">MCP Example</h3>
<h4 class="font-semibold mb-2">Code Assistant</h4>
<div class="bg-white rounded-lg p-4 mb-4">
<p class="italic mb-2">User asks:</p>
<p class="bg-gray-100 p-3 rounded">"Can you help me understand how the authentication system works in our codebase? I'm specifically looking for how password reset is handled."</p>
</div>
<div class="bg-purple-100 p-4 rounded-lg mb-4">
<p class="font-semibold mb-1">AI uses MCP to:</p>
<ul class="list-disc pl-5 space-y-1">
<li>Connect to GitHub via MCP server</li>
<li>Search repository for auth code</li>
<li>Access password reset implementation</li>
<li>Read documentation and tests</li>
</ul>
</div>
<div class="bg-white rounded-lg p-4">
<p class="italic mb-2">AI responds:</p>
<p class="bg-gray-100 p-3 rounded">"I've analyzed your codebase. The password reset workflow is implemented in `auth/password_reset.py`. It uses a token-based system with a 24-hour expiry. Here's how it works: [detailed explanation with code references]"</p>
</div>
</div>
<!-- A2A Example -->
<div class="bg-pink-50 p-6 rounded-xl">
<div class="text-pink-600 text-3xl mb-4"><i class="fas fa-plane"></i></div>
<h3 class="text-xl font-bold mb-3">A2A Example</h3>
<h4 class="font-semibold mb-2">Travel Planning System</h4>
<div class="bg-white rounded-lg p-4 mb-4">
<p class="italic mb-2">User asks:</p>
<p class="bg-gray-100 p-3 rounded">"I want to plan a 5-day trip to Kerala next month for my anniversary. We love nature and good food. Budget is around ₹50,000."</p>
</div>
<div class="bg-pink-100 p-4 rounded-lg mb-4">
<p class="font-semibold mb-1">Multi-agent collaboration:</p>
<ul class="list-disc pl-5 space-y-1">
<li>Primary agent uses A2A to connect to:</li>
<li>Travel Agent (flight/hotel options)</li>
<li>Local Expert Agent (Kerala activities)</li>
<li>Budget Manager Agent (cost optimization)</li>
<li>Agents coordinate via A2A protocol</li>
</ul>
</div>
<div class="bg-white rounded-lg p-4">
<p class="italic mb-2">Coordinated response:</p>
<p class="bg-gray-100 p-3 rounded">"I've created a complete Kerala itinerary for your anniversary with flights from Delhi (₹12,000), boutique eco-resort in Munnar (₹20,000), guided nature walks, authentic Kerala cuisine experiences, and a romantic backwater cruise - all within your ₹50,000 budget. Would you like to see the day-by-day plan?"</p>
</div>
</div>
</div>
<h3 class="text-2xl font-semibold mt-10 mb-4">Advanced Use Case: Integrating All Three</h3>
<div class="bg-gradient-to-r from-blue-50 via-purple-50 to-pink-50 p-6 rounded-xl">
<h4 class="text-xl font-bold mb-3">Enterprise Knowledge Assistant</h4>
<div class="bg-white rounded-lg p-4 mb-6">
<p class="italic mb-2">Executive asks:</p>
<p class="bg-gray-100 p-3 rounded">"I need a comprehensive analysis of our Q1 sales performance compared to projections, with recommendations for Q2 strategy. Include relevant market trends and competitor analysis. Schedule a meeting with the sales directors to review your findings."</p>
</div>
<div class="grid grid-cols-1 md:grid-cols-3 gap-4 mb-6">
<div class="bg-blue-100 p-4 rounded-lg">
<p class="font-semibold mb-1">Function Calling Role:</p>
<ul class="list-disc pl-5 space-y-1 text-sm">
<li>Creates meeting invitation</li>
<li>Generates PDF report</li>
<li>Sends notifications</li>
</ul>
</div>
<div class="bg-purple-100 p-4 rounded-lg">
<p class="font-semibold mb-1">MCP Role:</p>
<ul class="list-disc pl-5 space-y-1 text-sm">
<li>Accesses sales data from Salesforce</li>
<li>Retrieves forecasts from internal systems</li>
<li>Searches meeting records for context</li>
</ul>
</div>
<div class="bg-pink-100 p-4 rounded-lg">
<p class="font-semibold mb-1">A2A Role:</p>
<ul class="list-disc pl-5 space-y-1 text-sm">
<li>Engages Data Analyst Agent for trends</li>
<li>Consults Strategy Agent for recommendations</li>
<li>Coordinates with Scheduling Agent</li>
</ul>
</div>
</div>
<div class="bg-white rounded-lg p-4">
<p class="italic mb-2">Integrated response:</p>
<p class="bg-gray-100 p-3 rounded mb-2">"I've prepared a comprehensive Q1 sales analysis showing we exceeded targets in enterprise sales (112%) but underperformed in SMB sector (85%). Based on market analysis and competitor data, I've outlined three strategic recommendations for Q2.</p>
<p class="bg-gray-100 p-3 rounded mb-2">A meeting is scheduled with all sales directors for Thursday at 10 AM, and I've attached the full report to the invitation. Would you like me to highlight any specific sections during the meeting?"</p>
<p class="text-sm text-gray-600"><i class="fas fa-paperclip mr-1"></i> Q1_Sales_Analysis_Report.pdf</p>
</div>
</div>
</div>
</section>
</main>
<!-- Footer Section -->
<footer class="bg-gradient-to-r from-gray-900 via-indigo-900 to-gray-900 text-white py-12 px-4">
<div class="container mx-auto">
<div class="grid grid-cols-1 md:grid-cols-3 gap-8 mb-8">
<div>
<h3 class="text-2xl font-bold mb-4">AI Protocol Guide</h3>
<p class="text-gray-300 mb-4">
A comprehensive guide to understanding the revolutionary protocols that are transforming AI from simple chatbots into powerful digital assistants capable of real-world action.
</p>
<div class="flex space-x-4">
<a href="#" class="text-gray-300 hover:text-white transition-colors" title="Follow us on Twitter" aria-label="Twitter"><i class="fab fa-twitter"></i><span class="sr-only">Twitter</span></a>
<a href="#" class="text-gray-300 hover:text-white transition-colors" title="Connect on LinkedIn" aria-label="LinkedIn"><i class="fab fa-linkedin"></i><span class="sr-only">LinkedIn</span></a>
<a href="#" class="text-gray-300 hover:text-white transition-colors" title="View source on GitHub" aria-label="GitHub"><i class="fab fa-github"></i><span class="sr-only">GitHub</span></a>
</div>
</div>
<div>
<h3 class="text-xl font-semibold mb-4">Quick Links</h3>
<ul class="space-y-2">
<li><a href="#introduction" class="text-gray-300 hover:text-white transition-colors"><i class="fas fa-chevron-right mr-2 text-xs"></i>Introduction</a></li>
<li><a href="#function-calling" class="text-gray-300 hover:text-white transition-colors"><i class="fas fa-chevron-right mr-2 text-xs"></i>Function Calling</a></li>
<li><a href="#mcp" class="text-gray-300 hover:text-white transition-colors"><i class="fas fa-chevron-right mr-2 text-xs"></i>Model Context Protocol</a></li>
<li><a href="#a2a" class="text-gray-300 hover:text-white transition-colors"><i class="fas fa-chevron-right mr-2 text-xs"></i>Agent-to-Agent Protocol</a></li>
<li><a href="#comparison" class="text-gray-300 hover:text-white transition-colors"><i class="fas fa-chevron-right mr-2 text-xs"></i>Protocol Comparison</a></li>
</ul>
</div>
<div>
<h3 class="text-xl font-semibold mb-4">Resources</h3>
<ul class="space-y-2">
<li><a href="https://platform.openai.com/docs/guides/function-calling" class="text-gray-300 hover:text-white transition-colors" target="_blank" rel="noopener"><i class="fas fa-external-link-alt mr-2 text-xs"></i>OpenAI Function Calling Docs</a></li>
<li><a href="https://modelcontextprotocol.io" class="text-gray-300 hover:text-white transition-colors" target="_blank" rel="noopener"><i class="fas fa-external-link-alt mr-2 text-xs"></i>Model Context Protocol</a></li>
<li><a href="https://github.com/google/A2A" class="text-gray-300 hover:text-white transition-colors" target="_blank" rel="noopener"><i class="fas fa-external-link-alt mr-2 text-xs"></i>A2A Protocol (GitHub)</a></li>
</ul>
</div>
</div>
<div class="border-t border-gray-700 pt-8 text-center">
<p class="text-gray-400">© 2025 AI Protocol Guide. All rights reserved.</p>
<p class="text-gray-500 text-sm mt-2">Last updated: May 2025 | All protocol information verified with official documentation</p>
<p class="text-indigo-400 font-semibold mt-3">Crafted by OEvortex</p>
</div>
</div>
</footer>
<script>
// Smooth scrolling for anchor links
document.querySelectorAll('a[href^="#"]').forEach(anchor => {
anchor.addEventListener('click', function (e) {
e.preventDefault();
document.querySelector(this.getAttribute('href')).scrollIntoView({
behavior: 'smooth'
});
});
});
// Highlight active section in navigation
window.addEventListener('scroll', function() {
const sections = document.querySelectorAll('main section');
const navLinks = document.querySelectorAll('nav a');
let currentSection = '';
sections.forEach(section => {
const sectionTop = section.offsetTop;
const sectionHeight = section.clientHeight;
if (pageYOffset >= (sectionTop - 200)) {
currentSection = section.getAttribute('id');
}
});
navLinks.forEach(link => {
link.classList.remove('text-indigo-700', 'bg-indigo-100');
if (link.getAttribute('href') === `#${currentSection}`) {
link.classList.add('text-indigo-700', 'bg-indigo-100');
}
});
});
</script>
</body>
</html>
|