Video yükleniyor...

Video Yüklenemedi

Ana Sayfaya Dön

Support for Agent Plugins is live in Cursor (and I made a plugin for searching X!) Agent Plugins combine Skills and MCP servers into a single package Think about them like an Ikea furniture kit: your table comes with instructions, parts, and tools. You use the instructions to understand...

mattyp's profile picture

matt palmer

48,035 subscribers

39,554 görüntüleme • 8 gün önce •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

Introducing the context course: a free course on doing ML with agent context. You will learn how to train models, optimize inferences, and build datasets, all by defining harness context with`SKILLS.md`, Plugins, MCP, Subagents, and Hooks. The course includes: - Weekly live AMA on YouTube - Weekly practical projects for ML with context - Instructions in Pi, Codex, Claude, and Opencode - Tutorials and guides on fundamentals - Interactive Quizzes Learn to give AI agents the right knowledge, tools, and structure to actually get work done. Skills, MCP servers, plugins, multi-agent workflows, and building an agent from scratch. Join here:
0:30

Introducing the context course: a free course on doing ML with agent context. You will learn how to train models, optimize inferences, and build datasets, all by defining harness context with`SKILLS.md`, Plugins, MCP, Subagents, and Hooks. The course includes: - Weekly live AMA on YouTube - Weekly practical projects for ML with context - Instructions in Pi, Codex, Claude, and Opencode - Tutorials and guides on fundamentals - Interactive Quizzes Learn to give AI agents the right knowledge, tools, and structure to actually get work done. Skills, MCP servers, plugins, multi-agent workflows, and building an agent from scratch. Join here:

Ben Burtenshaw

16,905 görüntüleme • 3 ay önce

dbt Agent Skills are now open source. MCP gives agents access to dbt tools and governed context. Agent Skills teach them how to use those tools like a real dbt practitioner. Blog: Repo:
0:32

dbt Agent Skills are now open source. MCP gives agents access to dbt tools and governed context. Agent Skills teach them how to use those tools like a real dbt practitioner. Blog: Repo:

dbt

35,061 görüntüleme • 6 ay önce

ICYMI: We launched Data Agent Kit, a unified, open-source collection of data engineering and data science skills, tools, and plugins that integrate into the environments practitioners already use—VS Code, Claude Code, Codex, Antigravity CLI, and more →
0:56

ICYMI: We launched Data Agent Kit, a unified, open-source collection of data engineering and data science skills, tools, and plugins that integrate into the environments practitioners already use—VS Code, Claude Code, Codex, Antigravity CLI, and more →

Google Cloud Tech

24,626 görüntüleme • 2 ay önce

A Crash Course on Building AI Agents! Here's what it covers: - What is an AI agent - Connecting agents to tools - Overview of MCP - Replacing tools with MCP servers - Setting up observability and tracing All with 100% open-source tools!
32:57

A Crash Course on Building AI Agents! Here's what it covers: - What is an AI agent - Connecting agents to tools - Overview of MCP - Replacing tools with MCP servers - Setting up observability and tracing All with 100% open-source tools!

Akshay 🚀

115,943 görüntüleme • 1 yıl önce

MCP, Vibe code, and Autonomous Computer-use AI agents are all the rage. 8 insane releases in the last 48 hours: 1. Vy AI agent sees your screen, understands your apps, and takes actions using your accounts and your tools. No plugins or setups. 100% free to try.
0:31

MCP, Vibe code, and Autonomous Computer-use AI agents are all the rage. 8 insane releases in the last 48 hours: 1. Vy AI agent sees your screen, understands your apps, and takes actions using your accounts and your tools. No plugins or setups. 100% free to try.

Unwind AI

74,626 görüntüleme • 1 yıl önce

Agent-in-the-browser unlocks superpowers. The magic really shines when you bring your own model, system prompts, and MCP tools into the mix. Hence, AgentBoard 🪄. Your models, keys, and settings. Integration with remote MCP servers and — this is where it gets really fun — ability to register and allow the agent to call custom ~WebMCP tools that execute in context of the page. Chrome Web Store: Code:
3:51

Agent-in-the-browser unlocks superpowers. The magic really shines when you bring your own model, system prompts, and MCP tools into the mix. Hence, AgentBoard 🪄. Your models, keys, and settings. Integration with remote MCP servers and — this is where it gets really fun — ability to register and allow the agent to call custom ~WebMCP tools that execute in context of the page. Chrome Web Store: Code:

Ilya Grigorik

22,961 görüntüleme • 10 ay önce

🧠 Want to give your coding agent new capabilities? Use Agent Skills in Visual Studio Code! Agent skills let you package instructions and resources into reusable capabilities for your agent. Skills can be loaded on demand and called directly from chat using slash commands like /skill-name. Learn more:
0:26

🧠 Want to give your coding agent new capabilities? Use Agent Skills in Visual Studio Code! Agent skills let you package instructions and resources into reusable capabilities for your agent. Skills can be loaded on demand and called directly from chat using slash commands like /skill-name. Learn more:

Visual Studio Code

55,133 görüntüleme • 5 ay önce

This is Repo Prompt 2.0 A fully integrated agent, that makes it seamless to use RP's powerful MCP tools, with a built-in oracle and context builder. A first class experience showcasing how much better and efficient your agents can be with good context engineering tools.
4:35

This is Repo Prompt 2.0 A fully integrated agent, that makes it seamless to use RP's powerful MCP tools, with a built-in oracle and context builder. A first class experience showcasing how much better and efficient your agents can be with good context engineering tools.

eric provencher

38,921 görüntüleme • 5 ay önce

New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:
1:48

New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

Andrew Ng

81,696 görüntüleme • 11 ay önce

Subagents have arrived in Gemini CLI! 🤖🚀 Create your own custom subagents in Gemini CLI! Subagents are specialized, expert agents that the main agent can delegate work to. 📦- Subagents have their own set of tools, MCP servers, system instructions, and context window. 🏷️- Use Agent to explicitly delegate to a subagent 🧹- Keeps the main context window clean ⚡️- Speed up work by running agents in parallel Read more in the launch blog below 👇
0:33

Subagents have arrived in Gemini CLI! 🤖🚀 Create your own custom subagents in Gemini CLI! Subagents are specialized, expert agents that the main agent can delegate work to. 📦- Subagents have their own set of tools, MCP servers, system instructions, and context window. 🏷️- Use Agent to explicitly delegate to a subagent 🧹- Keeps the main context window clean ⚡️- Speed up work by running agents in parallel Read more in the launch blog below 👇

Jack Wotherspoon

222,006 görüntüleme • 4 ay önce

Explore the dart_mcp package, a powerful framework for building Model Context Protocol (MCP) servers and clients in Dart, enabling you to connect AI models to resources, tools, and create custom workflows.
3:06

Explore the dart_mcp package, a powerful framework for building Model Context Protocol (MCP) servers and clients in Dart, enabling you to connect AI models to resources, tools, and create custom workflows.

Flutter

23,167 görüntüleme • 3 ay önce

🇺🇸 xAI launched Grok Build, a coding agent that runs directly from your terminal, now in early beta for SuperGrok and X Premium Plus subscribers. It lets you plan and approve changes before anything runs, works with tools you already use like MCP servers and plugins, and can spin up multiple subagents working in parallel on larger tasks. Some users say it's already competing with Claude Code and GitHub Copilot Workspace. Source: xAI
0:43

🇺🇸 xAI launched Grok Build, a coding agent that runs directly from your terminal, now in early beta for SuperGrok and X Premium Plus subscribers. It lets you plan and approve changes before anything runs, works with tools you already use like MCP servers and plugins, and can spin up multiple subagents working in parallel on larger tasks. Some users say it's already competing with Claude Code and GitHub Copilot Workspace. Source: xAI

Mario Nawfal

99,324 görüntüleme • 2 ay önce

using tools, Cursor Agent have the capability to reason about when it should - read & write code - search your codebase - call MCP servers - run terminal commands an example where it connects to a postgres database, runs a query and writes to file
0:25

using tools, Cursor Agent have the capability to reason about when it should - read & write code - search your codebase - call MCP servers - run terminal commands an example where it connects to a postgres database, runs a query and writes to file

eric zakariasson

34,917 görüntüleme • 1 yıl önce

Most AI agents stop at chat. Agent Max is built for what comes after. Max tools. Max control and configurability. Max production readiness. Your agent can use: • any tools, APIs, MCP, and workflows • built-in knowledge: docs/website • multi-model: OpenAI, Claude, Gemini... • agent-to-agent handoffs • human-in-the-loop • logs, usage tracking, environments, and RBAC • enterprise controls for SOC2/GDPR/HIPAA/ISO needs • hosted chat UI, API, Skill in agents, Slack, WhatsApp, Teams, Voice, and more Agent Max is live now in BuildShip for everyone. Give it a try, or comment/DM to book a demo if you want help setting up your first agent.
1:15

Most AI agents stop at chat. Agent Max is built for what comes after. Max tools. Max control and configurability. Max production readiness. Your agent can use: • any tools, APIs, MCP, and workflows • built-in knowledge: docs/website • multi-model: OpenAI, Claude, Gemini... • agent-to-agent handoffs • human-in-the-loop • logs, usage tracking, environments, and RBAC • enterprise controls for SOC2/GDPR/HIPAA/ISO needs • hosted chat UI, API, Skill in agents, Slack, WhatsApp, Teams, Voice, and more Agent Max is live now in BuildShip for everyone. Give it a try, or comment/DM to book a demo if you want help setting up your first agent.

BuildShip

75,886 görüntüleme • 1 ay önce

I released the first alpha of Datasette Agent - a conversational AI assistant for Datasette that can answer questions about data in SQLite databases, and can be extended with plugins to add extra tools and features Here's a demo
4:11

I released the first alpha of Datasette Agent - a conversational AI assistant for Datasette that can answer questions about data in SQLite databases, and can be extended with plugins to add extra tools and features Here's a demo

Simon Willison

22,054 görüntüleme • 2 ay önce

introducing Managed Agents on the Gemini API - in one API call, you get agent that comes with a remote Linux environment hosted by Google, ready to scale - you can define custom instructions, skills, and tools in Markdown
0:41

introducing Managed Agents on the Gemini API - in one API call, you get agent that comes with a remote Linux environment hosted by Google, ready to scale - you can define custom instructions, skills, and tools in Markdown

Google AI Studio

148,463 görüntüleme • 2 ay 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

142,130 görüntüleme • 1 yıl önce

To use MCP in Cursor 1⃣Add an MCP in settings 2⃣In Composer, select "Agent Mode" 3⃣Cursor will run the MCP tool based on your prompt Testing more MCPs — updates and a guide coming soon. Follow me for updates Available MCP servers in comments 👇
0:23

To use MCP in Cursor 1⃣Add an MCP in settings 2⃣In Composer, select "Agent Mode" 3⃣Cursor will run the MCP tool based on your prompt Testing more MCPs — updates and a guide coming soon. Follow me for updates Available MCP servers in comments 👇

Melvin Vivas

68,971 görüntüleme • 1 yıl önce

HERMES AGENT WITHOUT TOOLS IS A CHATBOT. WITH THEM IT BUILDS 3D TOWERS IN BLENDER, CHECKS STOCK PRICES, AND DRIVES VS CODE. tonbi JUST DROPPED THE FULL GUIDE. module 6 of his 10-part Hermes masterclass. best breakdown of the tool layer anyone has published. what you need to know: TOOLS vs SKILLS vs MCP skills = instructions (markdown, loaded into context) tools = callable functions (Python, agent emits call, Hermes executes) MCP = adapters to external systems (Blender, Stripe, Linear, Notion) every tool has three parts: → the function (does the real work) → the schema (what the model sees to decide when to call it) → the registry (makes the tool exist in the agent) the model never runs the function directly. it emits a structured request (tool name + JSON args). Hermes executes and returns the result. if the tool fails, the error goes back as JSON. the agent recovers instead of crashing. TOOL SETS CONTROL THE SURFACE hermes chat --tool-sets web # only web tools loaded. no files, no terminal. hermes chat --tool-sets safe # read-only: web search, vision, image gen. # no file writes. no terminal. no code execution. mid-session: /tools enable video /tools disable terminal or toggle in the dashboard: hermes dashboard → Skills → Tool Sets MCP SERVERS two transport types: STDIO (local subprocess) or HTTP (remote endpoint). add a server: hermes mcp # or ask: "add the MCP server for Blender" filter tools with include/exclude per server. keep only what you trust. security: → OAuth 2.1 PKCE (no long-lived tokens in config) → package scanning via api.osv. dev before launch → all MCP calls go through approval gates HERMES AS MCP SERVER hermes mcp serve exposes 10 tools via FastMCP. connect VS Code Copilot or Cursor to your running Hermes instance. BUILD YOUR OWN TOOL He built a stock price tool live: → Python function calling Finnhub API → schema with name, description, parameters → registered in tool_sets.py → agent calls it automatically when relevant any repeating API call in your workflow can become a native tool. full Hermes architecture deep-dive in the article 👇
26:15

HERMES AGENT WITHOUT TOOLS IS A CHATBOT. WITH THEM IT BUILDS 3D TOWERS IN BLENDER, CHECKS STOCK PRICES, AND DRIVES VS CODE. tonbi JUST DROPPED THE FULL GUIDE. module 6 of his 10-part Hermes masterclass. best breakdown of the tool layer anyone has published. what you need to know: TOOLS vs SKILLS vs MCP skills = instructions (markdown, loaded into context) tools = callable functions (Python, agent emits call, Hermes executes) MCP = adapters to external systems (Blender, Stripe, Linear, Notion) every tool has three parts: → the function (does the real work) → the schema (what the model sees to decide when to call it) → the registry (makes the tool exist in the agent) the model never runs the function directly. it emits a structured request (tool name + JSON args). Hermes executes and returns the result. if the tool fails, the error goes back as JSON. the agent recovers instead of crashing. TOOL SETS CONTROL THE SURFACE hermes chat --tool-sets web # only web tools loaded. no files, no terminal. hermes chat --tool-sets safe # read-only: web search, vision, image gen. # no file writes. no terminal. no code execution. mid-session: /tools enable video /tools disable terminal or toggle in the dashboard: hermes dashboard → Skills → Tool Sets MCP SERVERS two transport types: STDIO (local subprocess) or HTTP (remote endpoint). add a server: hermes mcp # or ask: "add the MCP server for Blender" filter tools with include/exclude per server. keep only what you trust. security: → OAuth 2.1 PKCE (no long-lived tokens in config) → package scanning via api.osv. dev before launch → all MCP calls go through approval gates HERMES AS MCP SERVER hermes mcp serve exposes 10 tools via FastMCP. connect VS Code Copilot or Cursor to your running Hermes instance. BUILD YOUR OWN TOOL He built a stock price tool live: → Python function calling Finnhub API → schema with name, description, parameters → registered in tool_sets.py → agent calls it automatically when relevant any repeating API call in your workflow can become a native tool. full Hermes architecture deep-dive in the article 👇

YanXbt

32,680 görüntüleme • 2 ay önce

Big launch today: Custom MCP integrations for Replit Agent! 🚀 You can now connect Replit Agent to remote MCP servers, letting it pull context and take actions across your tools- so it can build, update, and act with deeper context than ever. Use cases this unlocks for you: - Build a webpage from content stored in Notion - Update tasks in Linear/Jira automatically - Build an app based on content in your Miro board We can’t wait to see what you build with it. ✨
3:42

Big launch today: Custom MCP integrations for Replit Agent! 🚀 You can now connect Replit Agent to remote MCP servers, letting it pull context and take actions across your tools- so it can build, update, and act with deeper context than ever. Use cases this unlocks for you: - Build a webpage from content stored in Notion - Update tasks in Linear/Jira automatically - Build an app based on content in your Miro board We can’t wait to see what you build with it. ✨

Replit ⠕

53,075 görüntüleme • 8 ay önce