Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

We're introducing: CranL CLI—deploy to the cloud using only one prompt. With exclusive and effective features that help you make your life easier and better. Download: Docs: MCP configuration: Start deploying using prompts NOW!

Cranlcom's profile picture

CranL

3,546 subscribers

61,625 görüntüleme • 4 ay önce •via X (Twitter)

EğitimSağlık & İyilikBilim & Teknoloji
LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Today, we’re releasing CranL, the best way to deploy your projects. Deploy your projects using github repo, one click, free and unlimited traffic. Along with multiple regions: - USA 🇺🇸 - Saudi Arabia 🇸🇦 - Germany 🇩🇪 - India 🇮🇳 And so many other regions coming soon. Try it now: CranL—The easiest, best, cheapest way to deploy your projects.
0:20

Today, we’re releasing CranL, the best way to deploy your projects. Deploy your projects using github repo, one click, free and unlimited traffic. Along with multiple regions: - USA 🇺🇸 - Saudi Arabia 🇸🇦 - Germany 🇩🇪 - India 🇮🇳 And so many other regions coming soon. Try it now: CranL—The easiest, best, cheapest way to deploy your projects.

CranL

959,309 görüntüleme • 4 ay önce

Introducing Deep Graph Codebase to MCP with One Click... Now Available for Gemini CLI too! 🤩 Transform any public GitHub repository into an AI-ready Code Graph by simply changing the URL from to This instantly prepares the repository for seamless integration with AI assistants. It's that easy! You can now use repositories like ollama as a code graph within any project using Gemini CLI... just add the MCP Server JSON configuration to your .gemini/settings.json file
1:01

Introducing Deep Graph Codebase to MCP with One Click... Now Available for Gemini CLI too! 🤩 Transform any public GitHub repository into an AI-ready Code Graph by simply changing the URL from to This instantly prepares the repository for seamless integration with AI assistants. It's that easy! You can now use repositories like ollama as a code graph within any project using Gemini CLI... just add the MCP Server JSON configuration to your .gemini/settings.json file

Daniel San

51,534 görüntüleme • 1 yıl önce

Gemini CLI now integrates with FastMCP, Python's leading library for building MCP servers! Effortlessly connect your custom MCP tools and prompts, directly to Gemini CLI! Read the announcement→
0:23

Gemini CLI now integrates with FastMCP, Python's leading library for building MCP servers! Effortlessly connect your custom MCP tools and prompts, directly to Gemini CLI! Read the announcement→

Google Cloud Tech

29,480 görüntüleme • 8 ay önce

GitHub agents are live on Zola. using MCP servers (git-mcp), you can chat with any repo, fetch docs, search code, and more. demo with prompt-kit repo
0:29

GitHub agents are live on Zola. using MCP servers (git-mcp), you can chat with any repo, fetch docs, search code, and more. demo with prompt-kit repo

Ibelick

10,964 görüntüleme • 1 yıl önce

With @Figma's MCP server, you can now make changes directly to your files using GitHub Copilot CLI or Visual Studio Code. ✨ Try it out 👇
1:01

With @Figma's MCP server, you can now make changes directly to your files using GitHub Copilot CLI or Visual Studio Code. ✨ Try it out 👇

GitHub

140,772 görüntüleme • 3 ay önce

Introducing Gemini CLI extensions, a new framework that allows you to customize Gemini CLI and connect it to the tools you use most—all from the command line. No more context-switching. Start using your favorite tools directly in your workflow today →
0:33

Introducing Gemini CLI extensions, a new framework that allows you to customize Gemini CLI and connect it to the tools you use most—all from the command line. No more context-switching. Start using your favorite tools directly in your workflow today →

Google Cloud Tech

80,461 görüntüleme • 8 ay önce

Introducing Junction Views in Mappls App to make your drive safer with smarter navigation! Start using now - download from More at: MapmyIndia Mappls Mappls App
0:45

Introducing Junction Views in Mappls App to make your drive safer with smarter navigation! Start using now - download from More at: MapmyIndia Mappls Mappls App

Rohan Verma

856,250 görüntüleme • 3 yıl önce

Analyze code and scan for vulnerabilities using natural language in your terminal 🔎 → Endor Labs built a Gemini CLI Extension that acts as an MCP server to help you maintain secure dependencies.
0:35

Analyze code and scan for vulnerabilities using natural language in your terminal 🔎 → Endor Labs built a Gemini CLI Extension that acts as an MCP server to help you maintain secure dependencies.

Google for Developers

40,408 görüntüleme • 5 ay önce

Gemini CLI can automate your computer using MCP 🔥 Add Windows MCP (or macOS MCP) to Gemini CLI and you can tell it what to do autonomously. Gemini then takes control of your entire system to achieve the goal you've set. Links below
0:27

Gemini CLI can automate your computer using MCP 🔥 Add Windows MCP (or macOS MCP) to Gemini CLI and you can tell it what to do autonomously. Gemini then takes control of your entire system to achieve the goal you've set. Links below

Paul Couvert

131,661 görüntüleme • 11 ay önce

Introducing the official Supabase MCP Server! Supabase MCP Server allows you to read and write to your database, create new projects, apply migrations, and more, right from your favorite AI tools! You can start using them in Cursor or Windsurf today!
1:47

Introducing the official Supabase MCP Server! Supabase MCP Server allows you to read and write to your database, create new projects, apply migrations, and more, right from your favorite AI tools! You can start using them in Cursor or Windsurf today!

Supabase

193,114 görüntüleme • 1 yıl önce

We're publishing: CranL S3—The easiest, fastest, cheapest solution for storage🗃️. Now you can create storage buckets, works with AWS SDK, boto3, rclone, and more. If you're on Pro plan -> you've got 5GB storage If you're on Enterprise plan -> you've got 50GB storage Start using CranL now, and enjoy the expirment!
0:49

We're publishing: CranL S3—The easiest, fastest, cheapest solution for storage🗃️. Now you can create storage buckets, works with AWS SDK, boto3, rclone, and more. If you're on Pro plan -> you've got 5GB storage If you're on Enterprise plan -> you've got 50GB storage Start using CranL now, and enjoy the expirment!

CranL

40,072 görüntüleme • 3 ay önce

Analyzing your marketing data just became easier with Datagran. Use Claude, Replit, Cursor or any other platform that supports MCP to query your ad insights and create apps or dashboards. To start using it, just add our MCP URL which you can find on our website.
0:52

Analyzing your marketing data just became easier with Datagran. Use Claude, Replit, Cursor or any other platform that supports MCP to query your ad insights and create apps or dashboards. To start using it, just add our MCP URL which you can find on our website.

Carlos Mendez

188,280 görüntüleme • 6 ay önce

Make your wildest ideas a reality ✨ Introducing Womp Spark 💡 - the first revolutionary AI workflow bringing your prompts to prints. Bring your visions to life. Prompt. Generate. Edit. Print. Available now, only on Womp
0:37

Make your wildest ideas a reality ✨ Introducing Womp Spark 💡 - the first revolutionary AI workflow bringing your prompts to prints. Bring your visions to life. Prompt. Generate. Edit. Print. Available now, only on Womp

Womp

104,791 görüntüleme • 8 ay önce

Gemini Code Assist now shares the same technology with Gemini CLI! In VS Code, place any prompt into the chat window using agent mode, and Code Assist will work to write tests, fix errors, build out features, or migrate your code →
1:13

Gemini Code Assist now shares the same technology with Gemini CLI! In VS Code, place any prompt into the chat window using agent mode, and Code Assist will work to write tests, fix errors, build out features, or migrate your code →

Google Cloud Tech

62,344 görüntüleme • 11 ay önce

Raydium LaunchLab MCP, by Hey Anon Using this MCP, your agent is able to deploy a memecoin via Raydium From image generation, curating a name/ticker, deploying, and dev buying - it is the full stack. Available via x402, ERC 8004, and our API:
0:25

Raydium LaunchLab MCP, by Hey Anon Using this MCP, your agent is able to deploy a memecoin via Raydium From image generation, curating a name/ticker, deploying, and dev buying - it is the full stack. Available via x402, ERC 8004, and our API:

Hey Anon

22,068 görüntüleme • 3 ay önce

Claude Code performs a complete analysis of Gemini-CLI and OpenAI Codex using Deep Graph MCP... one command to implement Claude Code automatically pulls two popular AI assistant repos and performs deep architectural analysis to determine which one is actually better built. Single command to implement: claude mcp add "Deep Graph MCP" npx -- -y mcp-code-graph@latest google-gemini/gemini-cli openai/codex The results might surprise you 👇
1:23

Claude Code performs a complete analysis of Gemini-CLI and OpenAI Codex using Deep Graph MCP... one command to implement Claude Code automatically pulls two popular AI assistant repos and performs deep architectural analysis to determine which one is actually better built. Single command to implement: claude mcp add "Deep Graph MCP" npx -- -y mcp-code-graph@latest google-gemini/gemini-cli openai/codex The results might surprise you 👇

Daniel San

68,001 görüntüleme • 1 yıl önce

Deploying your own server has never been easier! 1. Sign up. 2. Add funds with any cryptocurrency. 3. Click & deploy your server/s/ instantly! Try De Cloud today and revolutionize your cloud experience:
0:41

Deploying your own server has never been easier! 1. Sign up. 2. Add funds with any cryptocurrency. 3. Click & deploy your server/s/ instantly! Try De Cloud today and revolutionize your cloud experience:

De Cloud

27,698 görüntüleme • 2 yıl önce

2020–2022: Ah man! I didn’t know Rust or the Anchor framework. Deploying Solana programs was hard. 2022–2024: We got ChatGPT and could generate programs—but I still had to set up everything: Solana CLI, Cargo, Anchor... 2025: Now I can deploy any Solana program using OctoMCP—just plug it in and type the idea. ✅ Deployed Vault program from Claude MCP host using OctoMCP:
1:37

2020–2022: Ah man! I didn’t know Rust or the Anchor framework. Deploying Solana programs was hard. 2022–2024: We got ChatGPT and could generate programs—but I still had to set up everything: Solana CLI, Cargo, Anchor... 2025: Now I can deploy any Solana program using OctoMCP—just plug it in and type the idea. ✅ Deployed Vault program from Claude MCP host using OctoMCP:

OctonetAI

92,309 görüntüleme • 1 yıl önce

In case you missed it, earlier this week we launched "MCP: Build Rich-Context AI Apps with Anthropic." Enroll now and: ✅ Explore how MCP standardizes access to tools and data for AI applications, its underlying architecture, and how it simplifies the integration of new tools and connections to external systems (e.g., GitHub repos, Google Docs, local files). ✅ Build and deploy an MCP server that provides tools, resources, and prompts, and add it to the configuration of AI applications, such as Claude Desktop, to extend them. ✅ Build an MCP-compatible application that hosts multiple MCP clients, each maintaining 1-to-1 connection to an MCP server. Join in for free:
1:09

In case you missed it, earlier this week we launched "MCP: Build Rich-Context AI Apps with Anthropic." Enroll now and: ✅ Explore how MCP standardizes access to tools and data for AI applications, its underlying architecture, and how it simplifies the integration of new tools and connections to external systems (e.g., GitHub repos, Google Docs, local files). ✅ Build and deploy an MCP server that provides tools, resources, and prompts, and add it to the configuration of AI applications, such as Claude Desktop, to extend them. ✅ Build an MCP-compatible application that hosts multiple MCP clients, each maintaining 1-to-1 connection to an MCP server. Join in for free:

DeepLearning.AI

23,829 görüntüleme • 1 yıl önce

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!
2:43

New course: MCP: Build Rich-Context AI Apps with Anthropic. Learn to build AI apps that access tools, data, and prompts using the Model Context Protocol in this short course, created in partnership with Anthropic Anthropic and taught by Elie Schoppik Elie Schoppik, its Head of Technical Education. Connecting AI applications to external systems that bring rich context to LLM-based applications has often meant writing custom integrations for each use case. MCP is an open protocol that standardizes how LLMs access tools, data, and prompts from external sources, and simplifies how you provide context to your LLM-based applications. For example, you can provide context via third-party tools that let your LLM make API calls to search the web, access data from local docs, retrieve code from a GitHub repo, and so on. MCP, developed by Anthropic, is based on a client-server architecture that defines the communication details between an MCP client, hosted inside the AI application, and an MCP server that exposes tools, resources, and prompt templates. The server can be a subprocess launched by the client that runs locally or an independent process running remotely. In this hands-on course, you'll learn the core architecture behind MCP. You’ll create an MCP-compatible chatbot, build and deploy an MCP server, and connect the chatbot to your MCP server and other open-source servers. Here’s what you’ll do: - Understand why MCP makes AI development less fragmented and standardizes connections between AI applications and external data sources - Learn the core components of the client-server architecture of MCP and the underlying communication mechanism - Build a chatbot with custom tools for searching academic papers, and transform it into an MCP-compatible application - Build a local MCP server that exposes tools, resources, and prompt templates using FastMCP, and test it using MCP Inspector - Create an MCP client inside your chatbot to dynamically connect to your server - Connect your chatbot to reference servers built by Anthropic’s MCP team, such as filesystem, which implements filesystem operations, and fetch, which extracts contents from the web as markdown - Configure Claude Desktop to connect to your server and others, and explore how it abstracts away the low-level logic of MCP clients - Deploy your MCP server remotely and test it with the Inspector or other MCP-compatible applications - Learn about the roadmap for future MCP development, such as multi-agent architecture, MCP registry API, server discovery, authorization, and authentication MCP is an exciting and important technology that lets you build rich-context AI applications that connect to a growing ecosystem of MCP servers, with minimal integration work. Please sign up here!

Andrew Ng

141,952 görüntüleme • 1 yıl önce