MCP தொடக்கக்காரர்களுக்கான என்பது மாடல் சூழல் புரொட்டோகால் (MCP) - ஏஐ மாதிரிகள் மற்றும் கிளையன்ட் பயன்பாடுகளுக்கு இடையேயான தொடர்புக்கான ஒரு முறைமையான枠架ந்துறை மற்றும் திறந்த மூல கல்வி பாடத்திட்டம் ஆகும். இந்த சேமிப்பகத்தில் பல தொகுப்புக் மொழிகளில் செயல்பாட்டு குறியீட்டு உதாரணங்களுடன் விரிவான கற்றல் பொருட்கள் உள்ளன. இது ஒரு ஆவணமயமாக்கப்பட்ட சேமிப்பகம். பெரும்பான்மையான அமைப்பு தனித்தனியான மாதிரித் திட்டங்கள் மற்றும் ஆய்வுக்கூடங்களில் நிகழ்கிறது. மாதிரித் திட்டங்கள் உள்ளன: - 03-GettingStarted/samples/ - மொழி-சார்ந்த உதாரணங்கள் - 03-GettingStarted/01-first-server/solution/ - முதல் சேவையக செயல்பாடுகள் - 03-GettingStarted/02-client/solution/ - கிளையன்ட் செயல்பாடுகள் - 11-MCPServerHandsOnLabs/ - விரிவான தரவுத்தள ஒருமைமை ஆய்வுக்கூடங்கள் ஒவ்வொரு மாதிரித் திட்டத்திற்கும் தனித்தனியான அமைப்புச் செவ்வியல் உள்ளன:
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కొత్తవారికి MCP అనేది Model Context Protocol (MCP) నేర్చుకోవడానికి ఓపెన్-సోర్స్ విద్యా పరీక్షాంశం - ఇది AI మోడల్స్ మరియు క్లయింట్ అప్లికేషన్స్ మధ్య పరస్పర చర్యలకు ఒక ప్రమాణీకృత నేపథ్యం. ఈ రిపాజిటరీలో వివిధ ప్రోగ్రామింగ్ భాషలలో హ్యాండ్స్-ఆన్ కోడ్ ఉదాహరణలతో సమగ్ర అధ్యయన పదార్థాలు అందుబాటులో ఉన్నాయి. ఇది డాక్యుమెంటేషన్-ఆధారిత రిపాజిటరీ. ఎక్కువ సెటప్ ప్రత్యేక నమూనా ప్రాజెక్టులు మరియు ల్యాబ్స్లో జరుగుతుంది. నమూనా ప్రాజెక్టులు ఈ చోట్ల ఉంటాయి: - 03-GettingStarted/samples/ - భాషకు ప్రత్యేక ఉదాహరణలు - 03-GettingStarted/01-first-server/solution/ - మొదటి సర్వర్ అమలు - 03-GettingStarted/02-client/solution/ - క్లయింట్ అమలు - 11-MCPServerHandsOnLabs/ - సమగ్ర డేటాబేస్ ఏకీకరణ ల్యాబ్స్ ప్రతి నమూనా ప్రాజెక్టుకు…
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MCP para sa Mga Baguhan ay isang open-source na pang-edukasyong kurikulum para matutunan ang Model Context Protocol (MCP) - isang pinagsanib na balangkas para sa mga interaksyon sa pagitan ng mga AI model at mga kliyenteng aplikasyon. Ang repository na ito ay nagbibigay ng malawak na materyales sa pag-aaral kasama ang mga halimbawa ng kodigo sa maraming programming languages. Ito ay isang dokumentasyong nakatuon na repository. Karamihan sa setup ay ginagawa sa mga indibidwal na halimbawang proyekto at mga labs.
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Yeni Başlayanlar için MCP, Model Context Protocol (MCP) - AI modelleri ile istemci uygulamalar arasındaki etkileşimler için standart bir çerçeve olan MCP'yi öğrenmek için açık kaynaklı bir eğitim müfredatıdır. Bu depo, birden çok programlama dilinde pratik kod örnekleriyle kapsamlı öğrenme malzemeleri sunar. Bu, belge odaklı bir depodur. Çoğu kurulum bireysel örnek projeler ve laboratuvarlar içinde gerçekleşir. Örnek projeler aşağıdaki konumlardadır: - 03-GettingStarted/samples/ - Dil spesifik örnekler - 03-GettingStarted/01-first-server/solution/ - İlk sunucu uygulamaları - 03-GettingStarted/02-client/solution/ - İstemci uygulamaları - 11-MCPServerHandsOnLabs/ -…
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MCP для початківців — це відкритий навчальний курс для вивчення Протоколу Контексту Моделі (MCP) — стандартизованої рамки для взаємодії між AI-моделями та клієнтськими додатками. Цей репозиторій надає комплексні навчальні матеріали з практичними прикладами коду на кількох мовах програмування. Це репозиторій, орієнтований на документацію. Більшість налаштувань відбувається у кожному окремому прикладі проекту та лабораторії. Прикладні проєкти знаходяться в: - 03-GettingStarted/samples/ - Приклади для конкретних мов - 03-GettingStarted/01-first-server/solution/ - Перші реалізації серверів - 03-GettingStarted/02-client/solution/ - Клієнтські реалізації - 11-MCPServerHandsOnLabs/ - Комплексні лабораторії…
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MCP برائے مبتدیان ماڈل کانٹیکسٹ پروٹوکول (MCP) سیکھنے کے لیے ایک اوپن سورس تعلیمی نصاب ہے - جو AI ماڈلز اور کلائنٹ ایپلیکیشنز کے مابین تعاملات کے لیے ایک معیاری فریم ورک ہے۔ یہ ریپوزٹری مختلف پروگرامنگ زبانوں میں عملی کوڈ کی مثالوں کے ساتھ جامع تعلیمی مواد فراہم کرتی ہے۔ یہ ایک دستاویزی مرکزیت والی ریپوزٹری ہے۔ زیادہ تر سیٹ اپ نمونہ پروجیکٹس اور لیبز کے اندر ہوتا ہے۔ نمونہ پروجیکٹس درج ذیل جگہوں پر موجود ہیں: - 03-GettingStarted/samples/…
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MCP dành cho người mới bắt đầu là một chương trình học mở nguồn về giao thức Model Context Protocol (MCP) - một khuôn khổ tiêu chuẩn hóa cho sự tương tác giữa các mô hình AI và các ứng dụng khách. Kho lưu trữ này cung cấp tài liệu học tập toàn diện với các ví dụ mã thực hành trên nhiều ngôn ngữ lập trình. Đây là kho tài liệu tập trung. Hầu hết việc thiết lập diễn…
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Python bindings for Playwright. The client in playwright/_impl/ talks to the Node.js driver in playwright/driver/ over a pipe. Everything comes from microsoft/playwright at the commit in DRIVER_VERSION: the driver, the generated API and the code that we port. .upstream/ is a full clone of it (gitignored). Read upstream code there. Do not edit, commit or switch branches in it. You need Python 3.10+, git, Node.js and npm. When DRIVER_VERSION changes, for example after a pull, run python scripts/upstream.py checkout and…
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These rules say how to write tests/async/{page,library} and tests/sync/{page,library} from tests/page and tests/library in microsoft/playwright, at the commit in DRIVER_VERSION. Use them at each roll, for every new or changed upstream test. The upstream tests are in .upstream/, the checkout at that commit. The steps of a roll are in the playwright-roll skill. The port is line by line, with zero deviations. A reviewer reads the .spec.ts file and the two .py files side by side. Each upstream statement maps…
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Instructions for AI coding agents working in the .NET codebase. See ./.github/skills/build-and-test/SKILL.md for detailed instructions on building, testing, and linting projects. See ./.github/skills/project-structure/SKILL.md for an overview of the project structure. See ./.github/skills/pull-requests/SKILL.md for guidance on writing PR descriptions and handling/resolving PR review comments. The framework integrates with Microsoft.Extensions.AI and Microsoft.Extensions.AI.Abstractions (external NuGet packages) using types like IChatClient, FunctionInvokingChatClient, AITool, AIFunction, ChatMessage, and AIContent. When developing or reviewing code, verify adherence to these key design principles: Samples (in ./samples/ folder) should…
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This file documents the structure and conventions of the .NET samples so that agents (AI or human) can maintain them without rediscovering decisions. 1. Progressive complexity: Sections 01→05 build from "hello world" to production. Within 01-get-started, projects are numbered 01–05 and each step adds exactly one concept.
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Instructions for AI coding agents working in the Python codebase. Key Documentation: - DEV_SETUP.md - Development environment setup and available poe tasks - CODING_STANDARD.md - Canonical Python engineering and API-design standards - samples/SAMPLE_GUIDELINES.md - Sample structure and guidelines - Python function-calling loop specification - Required behavior, scenario-to-test mapping, coverage gaps, and extra validation for function-loop changes Agent Skills (.github/skills/) — detailed, task-specific instructions loaded on demand: - python-development — Python development workflow and routing to the canonical standards and task-specific…
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Agent-to-Agent (A2A) protocol support for inter-agent communication. A2A protocol metadata is stored under additional_properties["a2a"]. The legacy a2a_metadata key remains readable and is dual-written during the compatibility period defined by spec 005. Consuming legacy-only input emits FutureWarning; new callers should write only the canonical a2a key.
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AG-UI protocol integration for building agent UIs with the AG-UI standard. - AgentFrameworkAgent - Wraps agents for AG-UI compatibility - AgentFrameworkWorkflow - Wraps native Workflow objects, or accepts workflow_factory(thread_id) for thread-scoped workflow instances without subclassing - AGUIChatClient - Chat client that speaks AG-UI protocol - AGUIHttpService - HTTP service for AG-UI endpoints - agent_framework_messages_to_agui_host_history() - Converts persisted Agent Framework messages to bounded AG-UI Host history while retaining MCP widget payloads and model replay metadata - AGUIEventConverter - Converts between Agent…
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