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... 1:2:28
Building a CRM with AI – Live Coding Session w. Make

Lovable

1+ months ago 2K views

A live demonstration showcases the integration of Lovable, an AI-driven tool, with Make to create a custom CRM system. The session focuses on building essential CRM functionalities, including the ability to enrich customer data and automate outreach processes using AI. Participants learn about the importance of personalization in CRM and how automated tools can streamline workflows. The integration highlights the potential for AI in improving customer relationship management by using intelligent automation to enhance user experience and efficiency in managing customer interactions and data enrichment.
60:09 - 60:13

Overview of using AI algorithms for customer outreach and relevant interactions.

Lovable AI Machine Learning Tech & Hardware
... 24:26
Claude MCP has Changed AI Forever - Here's What You NEED to Know

Cole Medin

1+ months ago 13K views

mCP, developed by Anthropic, standardizes how tools are provided to AI agents, providing unprecedented ease for developers. This protocol enables the integration of diverse services into AI applications, enhancing productivity significantly. mCP's persistent significance distinguishes it from fleeting AI trends, providing real value over time, and facilitating better-designed AI agents. The speaker emphasizes the importance of adopting mCP to harness its capabilities effectively while illustrating its practical application in real-time projects with examples and a walkthrough of integration with common tools and platforms, including Python and n8n workflows.
05:37 - 05:55

mCP servers standardize AI tool integration, improving compatibility across frameworks.

Natural Language Processing (NLP) AI Trends
... 1:28:27
MCP AI Agents: Automate ANYTHING…

Julian Goldie SEO

1+ months ago 2K views

Automating workflows using mCP AI agents simplifies complex tasks by integrating seamlessly with various applications, making setup easier than traditional methods. The mCP (Model Context Protocol) serves as a universal plug for connecting AI systems, allowing for the execution of API requests and real-time updates without extensive coding. This video outlines how to set up mCP tools, integrate them with Visual Studio Code, and use Google Gemini to enhance functionalities, thereby improving workflow efficiencies while reducing setup complexities. Key features and benefits of mCP servers are highlighted, emphasizing their role in automating processes across different platforms.
02:00 - 03:00

Demonstration of using API integrations with mCP to automate tasks.

Machine Learning AI Startups
... 28:48
I built an AI App with Loveable & n8n (No-Code Tutorial)

AI Workshop

1+ months ago 2K views

This video tutorial demonstrates how to create a complete SaaS platform utilizing no-code tools like Lovable and Nend. By combining these tools, a full-stack application is developed without writing any code. The AI coach, functioning as the backend agent, interacts with users through a beautiful front-end UI. The setup includes receiving queries from users, processing them via an AI agent, and returning insightful responses, demonstrating how modern tools facilitate rapid application development. A step-by-step approach is provided to inspire viewers to leverage no-code platforms for building their applications.
03:35 - 03:45

Demonstration of user interaction where AI processes a career-related query.

Loveable Machine Learning Education
... 26:3
What is MCP & How to Use It with AI Agents in n8n (Full Tutorial!)

AI Workshop

1+ months ago 3K views

mCP provides AI agents with a universal key to access diverse tools and data resources, streamlining interactions with AI systems. It allows seamless access to content repositories and APIs that previously required manual connections, thereby offering flexibility and scalability for AI agents. The video illustrates various demos of mCP functionality, including scraping data from websites and accessing tools dynamically. This integration marks a significant advancement in how AI agents interact with external resources, reducing time-consuming setups and enhancing operational efficiency in AI applications.
03:22 - 03:31

FIR Craw mCP simplifies access to web data tools.

n8n Machine Learning Education
... 14:20
Claude MCP Workflow: Proof That AI AGENTS Will Change Work Forever?

All About AI

1+ months ago 8K views

Model Context Protocol (mCP) effectively connects diverse tools like email, Stripe, and Supabase to streamline workflows in applications using Cloud Code. The integration allows users to execute tasks such as processing payments and managing customer outreach efficiently. With a focus on practical examples, the setup of servers and connection of tools through mCP demonstrates how powerful these AI applications can be for enhancing productivity, providing real-life use cases that showcase its capabilities in everyday scenarios. The potential for further expansion and better integration of AI tools highlights the significant impact of mCP in workflow automation.
04:40 - 05:40

Recording payments in the database using Supabase through Cloud Code.

Nvidia Machine Learning Research & Innovations
... 37:21
Connect N8N AI Agents to EVERYTHING using MCP?

Simon Scrapes | AI Agents & Automation

1+ months ago 6K views

Connectivity and integration of AI agents with tools through the Model Context Protocol (mCP) revolutionizes automation in businesses. This unified standard simplifies interactions with various data sources, enabling seamless web scraping, real-time updates, and executing commands in a user-friendly manner. The potential of mCP is evidenced by its ability to reduce setup complexity and enhance efficiency by allowing AI systems to interact with multiple applications without deep API knowledge. Step-by-step guidance is provided to demonstrate mCP's setup and capabilities, highlighting examples such as scraping web pages and utilizing Google Maps for user assistance.
01:09 - 01:12

Overview of mCP's role in simplifying AI complex workflows and integrations.

AI cloud services AI Startups
... 37:21
Connect N8N AI Agents to EVERYTHING using MCP?

Simon Scrapes | AI Agents & Automation

1+ months ago 6K views

Connectivity and integration of AI agents with tools through the Model Context Protocol (mCP) revolutionizes automation in businesses. This unified standard simplifies interactions with various data sources, enabling seamless web scraping, real-time updates, and executing commands in a user-friendly manner. The potential of mCP is evidenced by its ability to reduce setup complexity and enhance efficiency by allowing AI systems to interact with multiple applications without deep API knowledge. Step-by-step guidance is provided to demonstrate mCP's setup and capabilities, highlighting examples such as scraping web pages and utilizing Google Maps for user assistance.
01:09 - 01:12

Overview of mCP's role in simplifying AI complex workflows and integrations.

AI cloud services AI Startups