A2A and MCP protocol for Agentic AI LangGraph Claude Cursor

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2.61 GB | 15min 11s | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English​

Files Included :

Spoiler

1 -MCP Introduction.mp4 (29.93 MB)
2 -MCP Vs Non MCP connection.mp4 (17.01 MB)
3 -MCP Architecture.mp4 (15.26 MB)
4 -MCP Communication between components.mp4 (37.57 MB)
1 -Project intro.mp4 (57.86 MB)
2 -Project setup.mp4 (20.75 MB)
3 -Gemini API Key.mp4 (8.69 MB)
4 -OpenAI API Key.mp4 (5.45 MB)
1 -Code flow exchange Agent.mp4 (37.23 MB)
10 -User Input Validation.mp4 (15.91 MB)
2 -Project init.mp4 (5.29 MB)
3 -Exchange Agent code.mp4 (58.75 MB)
4 -Agent Response format.mp4 (11.6 MB)
5 -Agent Flow overview.mp4 (26.9 MB)
6 -Conversion init code.mp4 (29.02 MB)
7 -LangGraph init code.mp4 (39.05 MB)
8 -Agent stream response method.mp4 (46.25 MB)
9 -Agent response format.mp4 (62.64 MB)
1 -Event processing intro.mp4 (23.52 MB)
2 -Agent card details.mp4 (88.7 MB)
3 -Exchange executor code.mp4 (58.38 MB)
4 -Exchange execute code.mp4 (129.2 MB)
1 -A2A server create.mp4 (85.33 MB)
1 -A2A client send payload format.mp4 (47.62 MB)
2 -Print json response format.mp4 (35.11 MB)
3 -Single turn request1.mp4 (111.57 MB)
4 -Main Method call.mp4 (62.12 MB)
5 -Streaming message response.mp4 (50.47 MB)
6 -Multi turn message response.mp4 (94.13 MB)
1 -Demo Setup.mp4 (39.87 MB)
2 -Demo Single turn message with A2A.mp4 (76.29 MB)
3 -Demo Streaming message with A2A.mp4 (65.79 MB)
4 -Demo Multi turn message with A2A.mp4 (82.95 MB)
1 -Claude desktop install.mp4 (31.6 MB)
2 -Cursor IDE install.mp4 (42.74 MB)
3 -Node JS installation.mp4 (12.85 MB)
4 -MCP server Smithery AI.mp4 (19.24 MB)
5 -MCP server integration claude.mp4 (39.63 MB)
6 -Visual studio install.mp4 (10.13 MB)
1 -MCP server with Fire crawl and Claude client.mp4 (15.35 MB)
2 -Youtube summarisation with MCP and Claude.mp4 (5.97 MB)
3 -Cursor MCP Setting.mp4 (12.65 MB)
4 -Cursor MCP Demo.mp4 (4.22 MB)
5 -MCP CLI installation with UV.mp4 (13.18 MB)
6 -Create MCP server calculator.mp4 (8.51 MB)
7 -Demo calculator.mp4 (10.88 MB)
1 -MCP tool inspector overview.mp4 (9.36 MB)
2 -Weather API Key.mp4 (13.34 MB)
3 -Serper API key.mp4 (6.57 MB)
4 -Weather API Demo.mp4 (32.44 MB)
5 -Stock prices with Serper API.mp4 (21.89 MB)
1 -Custom MCP server architecture.mp4 (48.71 MB)
2 -Custom MCP server code.mp4 (65.58 MB)
3 -Custom MCP server demo with claude.mp4 (27.16 MB)
4 -Custom MCP server demo with Cursor.mp4 (33.88 MB)
1 -LangGraph MCP architecture.mp4 (34.4 MB)
2 -Create MCP server.mp4 (14.33 MB)
3 -Create PY Client.mp4 (45.72 MB)
4 -DemoLangGraph with MCP server.mp4 (69.48 MB)
1 -A2A Introduction.mp4 (8.72 MB)
2 -A2A Agent use cases.mp4 (29.76 MB)
3 -A2A vs MCP.mp4 (28.35 MB)
1 -Visual studio install.mp4 (14.54 MB)
1 -Project Introduction.mp4 (22.89 MB)
10 -Client Agent code.mp4 (55.08 MB)
11 -Demo Agentic AI with A2A protocol.mp4 (53.76 MB)
2 -Agent card overview.mp4 (24.64 MB)
3 -Project setup with UV.mp4 (14.16 MB)
4 -Agent skill and Agent card code.mp4 (46.17 MB)
5 -Agent executor overview.mp4 (45.48 MB)
6 -Agent executor code.mp4 (39.19 MB)
7 -A2A server overview.mp4 (18.49 MB)
8 -A2A server code.mp4 (24.86 MB)
9 -Run A2A server.mp4 (20.42 MB)

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Screenshot

Spoiler

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[0dayddl]

Last updated 7/2025 Created by Rahul Raj MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 89 Lectures ( 15h 33m ) | Size: 7 GB​

Crash course on A2A & MCP Protocols: Building Multi-Agent Systems with LangGraph, Claude & Cursor

What you'll learn
Grasp the core principles of A2A and MCP protocols for agent communication.
Build and manage multi-agent workflows efficiently using the LangGraph framework.
Integrate Claude and Cursor to enhance agent capabilities in real-world projects.
Use LangGraph's advanced features for custom agent and logic.

Requirements
python

Description
Unlock the power of next-generation automation and multi-agent orchestration with our comprehensive course on the A2A (Agent-to-Agent) and MCP (Multi-Agent Coordination Protocol) protocols, leveraging LangGraph, Claude, and Cursor. This hands-on course is designed for developers, AI enthusiasts, and professionals who want to master advanced AI workflows and practical agent collaboration.We'll start by demystifying the foundations of A2A and MCP protocols-essential tools for scalable, secure, and efficient communication between AI agents. You'll get an in-depth look at their real-world applications and integration strategies.Through practical demonstrations, you'll learn how to use LangGraph to design and deploy robust agent networks that communicate and coordinate tasks. The course covers building custom agent workflows with Claude, a leading LLM, and integrating Cursor for streamlined code generation and automation.You'll gain hands-on experience by building real projects that implement A2A and MCP, guiding you from concept to deployment. The course emphasizes best practices for reliability, security, and scalability. By the end, you'll have the skills to create, manage, and scale advanced AI agent systems for various domains-whether in automation, process optimization, or innovative AI-driven apps.No prior experience with A2A, MCP, or LangGraph is required-just a willingness to learn and experiment. Join us to future-proof your skills and be at the forefront of agent-driven AI solutions!

Who this course is for
Agentic AI

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