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🚀 What if I told you Remote Desktop Manager is getting an MCP server? But wait, there's more! You'll be able to run commands inside RDP connections through Devolutions Agent and our brand new RDP virtual channel extension! Here's a sneak peek 👀👇

Marc-André Moreau

5,622 subscribers

16,220 次观看 • 1 年前 •via X (Twitter)

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So here is new local privilege escalation zero-day I discovered, not patched yet too :). In simple terms, if you have a service like RDP that exposes an RPC server, there many system services running as SYSTEM connect to it as RPC clients. If that service is turned off (RDP is off by default), it seems that any other process in Windows can expose the same RPC server using the same endpoint. Now all the RPC calls from that SYSTEM processes will come to this fake server and If the process that deployed the server has SeImpersonatePrivilege, it can escalate to SYSTEM by impersonate the RPC client. In the white paper below, I describe five exploit paths you can abuse. However it's architecture problem and maybe there are more. It's Not A Potato

So here is new local privilege escalation zero-day I discovered, not patched yet too :). In simple terms, if you have a service like RDP that exposes an RPC server, there many system services running as SYSTEM connect to it as RPC clients. If that service is turned off (RDP is off by default), it seems that any other process in Windows can expose the same RPC server using the same endpoint. Now all the RPC calls from that SYSTEM processes will come to this fake server and If the process that deployed the server has SeImpersonatePrivilege, it can escalate to SYSTEM by impersonate the RPC client. In the white paper below, I describe five exploit paths you can abuse. However it's architecture problem and maybe there are more. It's Not A Potato

Haidar

51,299 次观看 • 4 个月前

NEW: Former FBI Special Agent says there is “No Doubt” the information gathered by Epstein looks like an “intelligence collection operation.” “I think there's no doubt…He went after people or he had connections to people that had connections to national security or huge technological advances. An intel operation would greatly benefit and be able to not only understand what otherworld leaders are doing, but be able to influence what they're doing.” LA Times Media Group LA Times Studios

NEW: Former FBI Special Agent says there is “No Doubt” the information gathered by Epstein looks like an “intelligence collection operation.” “I think there's no doubt…He went after people or he had connections to people that had connections to national security or huge technological advances. An intel operation would greatly benefit and be able to not only understand what otherworld leaders are doing, but be able to influence what they're doing.” LA Times Media Group LA Times Studios

Catherine Herridge

164,790 次观看 • 6 个月前

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!

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

142,137 次观看 • 1 年前

BREAKING: OpenAI has officially released Agent Mode, allowing users to spin up a virtual desktop and take action. I got early access to ChatGPT Agent Mode and want to share my thoughts. Agent Mode lets you delegate tasks like searching or browsing to an agent inside a virtual desktop inside ChatGPT. You can spin up multiple little “workers” to fire off tasks and keep tabs as they chug through your to-do list AT THE SAME TIME. If it gets stuck or goes off track, you can take over manually. The UI is friendly and keeps the reasoning transparent, so you’re not left guessing what it’s doing or why. It’s not perfect and doesn’t give you as many artifacts as other players in the space, but a strong platform for “let’s see how much I can hand off and supervise”, and a first step toward managing fleets of AI workers instead of pinging a single chatbot for answers. If you’re on ChatGPT Pro, Plus, or Team, look for Agent Mode in the tools dropdown.

BREAKING: OpenAI has officially released Agent Mode, allowing users to spin up a virtual desktop and take action. I got early access to ChatGPT Agent Mode and want to share my thoughts. Agent Mode lets you delegate tasks like searching or browsing to an agent inside a virtual desktop inside ChatGPT. You can spin up multiple little “workers” to fire off tasks and keep tabs as they chug through your to-do list AT THE SAME TIME. If it gets stuck or goes off track, you can take over manually. The UI is friendly and keeps the reasoning transparent, so you’re not left guessing what it’s doing or why. It’s not perfect and doesn’t give you as many artifacts as other players in the space, but a strong platform for “let’s see how much I can hand off and supervise”, and a first step toward managing fleets of AI workers instead of pinging a single chatbot for answers. If you’re on ChatGPT Pro, Plus, or Team, look for Agent Mode in the tools dropdown.

Allie K. Miller

155,943 次观看 • 1 年前

What if your AI agent could purchase a domain, set up a website, and earn you 3% cash back at the same time? The agentic credit card was built for intelligent, secure spending. Just connect an AI agent to the Robinhood Banking MCP server, select your preferences, and you're all set. Watch our Product Manager, Arjun Malhotra, explain the process. Learn more here: Terms Apply. See rewards program for full details:

What if your AI agent could purchase a domain, set up a website, and earn you 3% cash back at the same time? The agentic credit card was built for intelligent, secure spending. Just connect an AI agent to the Robinhood Banking MCP server, select your preferences, and you're all set. Watch our Product Manager, Arjun Malhotra, explain the process. Learn more here: Terms Apply. See rewards program for full details:

Robinhood

6,299,956 次观看 • 2 个月前

🤯 Building computer-vision applications is never going to be the same again. As Andrej Karpathy says, "English is going to be the new programming-language", and we just made that happen for programming visual AI. 👨‍💻 This past month, the VLM Run team cooked up something magical that I'm especially proud of - a natural-language interface to build and run computer vision workflows (object-detection, OCR, parsing, and so much more) – all via our new VLM Run MCP server. 🔌 It works with any MCP-compatible AI agent (Claude, OpenAI, Cursor, etc.) and abstracts complex visual workflows into simple English commands. No need to write Python or fiddle with bespoke computer-vision code – just say what you want your agent to do, and it does it. Here’s a glimpse into what you can build today ( ☑️ Image AI agents – run detection, tagging, blurring, cropping, and more traditional CV tasks with English ☑️ Document AI agents – extract totals from invoices, search visual content, or act on what’s found ☑️ Video AI agents – understand scene content, trim clips, add subtitles, and create ready-to-share edits ☑️ And best-of-all, it's fully programmable with English. 🧑‍🍳 MCP Showcase: 📚 MCP Cookbooks: 📚 MCP Docs: #computervision #ai #agents #llm #vlm #mcp #vibecoding #genai

🤯 Building computer-vision applications is never going to be the same again. As Andrej Karpathy says, "English is going to be the new programming-language", and we just made that happen for programming visual AI. 👨‍💻 This past month, the VLM Run team cooked up something magical that I'm especially proud of - a natural-language interface to build and run computer vision workflows (object-detection, OCR, parsing, and so much more) – all via our new VLM Run MCP server. 🔌 It works with any MCP-compatible AI agent (Claude, OpenAI, Cursor, etc.) and abstracts complex visual workflows into simple English commands. No need to write Python or fiddle with bespoke computer-vision code – just say what you want your agent to do, and it does it. Here’s a glimpse into what you can build today ( ☑️ Image AI agents – run detection, tagging, blurring, cropping, and more traditional CV tasks with English ☑️ Document AI agents – extract totals from invoices, search visual content, or act on what’s found ☑️ Video AI agents – understand scene content, trim clips, add subtitles, and create ready-to-share edits ☑️ And best-of-all, it's fully programmable with English. 🧑‍🍳 MCP Showcase: 📚 MCP Cookbooks: 📚 MCP Docs: #computervision #ai #agents #llm #vlm #mcp #vibecoding #genai

Sudeep Pillai

17,789 次观看 • 1 年前

𝗡𝗼𝘁𝗲𝗯𝗼𝗼𝗸𝗟𝗠 + 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲: 𝗕𝘂𝗶𝗹𝗱 𝗔𝗡𝗬𝗧𝗛𝗜𝗡𝗚. 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝘆𝗼𝘂𝗿 𝗲𝗻𝘁𝗶𝗿𝗲 𝗡𝗼𝘁𝗲𝗯𝗼𝗼𝗸𝗟𝗠 𝗳𝗿𝗼𝗺 𝗖𝗹𝗮𝘂𝗱𝗲. 𝗡𝗼 𝗰𝗹𝗶𝗰𝗸𝗶𝗻𝗴. 𝗡𝗼 𝘀𝘄𝗶𝘁𝗰𝗵𝗶𝗻𝗴 𝘁𝗮𝗯𝘀. There's a free MCP server that connects NotebookLM to Claude. Here's what you can automate: → Generate podcast audio with one prompt → Create infographics automatically → Build video views in seconds → Run deep research across 122+ notebooks → Query all your sources at once Claude organizes everything in clean tables. NotebookLM's UI is messy tiny icons. Setup takes 5 minutes. Full remote control from Claude desktop. Save this video, you'll never touch NotebookLM's interface again. Want the SOP? DM me. 💬

𝗡𝗼𝘁𝗲𝗯𝗼𝗼𝗸𝗟𝗠 + 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲: 𝗕𝘂𝗶𝗹𝗱 𝗔𝗡𝗬𝗧𝗛𝗜𝗡𝗚. 𝗖𝗼𝗻𝘁𝗿𝗼𝗹 𝘆𝗼𝘂𝗿 𝗲𝗻𝘁𝗶𝗿𝗲 𝗡𝗼𝘁𝗲𝗯𝗼𝗼𝗸𝗟𝗠 𝗳𝗿𝗼𝗺 𝗖𝗹𝗮𝘂𝗱𝗲. 𝗡𝗼 𝗰𝗹𝗶𝗰𝗸𝗶𝗻𝗴. 𝗡𝗼 𝘀𝘄𝗶𝘁𝗰𝗵𝗶𝗻𝗴 𝘁𝗮𝗯𝘀. There's a free MCP server that connects NotebookLM to Claude. Here's what you can automate: → Generate podcast audio with one prompt → Create infographics automatically → Build video views in seconds → Run deep research across 122+ notebooks → Query all your sources at once Claude organizes everything in clean tables. NotebookLM's UI is messy tiny icons. Setup takes 5 minutes. Full remote control from Claude desktop. Save this video, you'll never touch NotebookLM's interface again. Want the SOP? DM me. 💬

Julian Goldie SEO

91,941 次观看 • 7 个月前

MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.

MCP is mind-blowing. Here is a genius setup that will earn you a promotion with your manager. I have multiple data sources: data in S3, MySQL, and local files. Using Spice (an open-source project), I can co-locate all of that data behind a single SQL endpoint and augment it using MCP. Before, accessing data was slow, and I had to make multiple requests to get anything. After using Spice, I can query the data much faster (since it's mirrored locally), and I don't have to worry about where the data is coming from. Spice acts as an MCP server, so I can connect to it from my IDE or the Claude Desktop app and have access to all the data. But even more cool than that: Spice also acts as an MCP client, so it can connect to other MCP servers. This is where things get really interesting! Watch the video. I'm querying multiple data sources from my IDE and using the Google Maps MCP server for driving directions.

Santiago

142,696 次观看 • 1 年前

“I think it helped that Rob and I were both in similar places in our lives — I mean, not the dark version, but you know… He had a brand-new baby, and I had a baby. I think we’re both really lucky with our partners [Suki Waterhouse and Cooke Maroney]. We’re able to explore kind of what it should be — and what it is!”

Robert Pattinson Photos | Fansite

126,947 次观看 • 9 个月前

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

New Course: ACP: Agent Communication Protocol Learn to build agents that communicate and collaborate across different frameworks using ACP in this short course built with IBM Research's BeeAI, and taught by Sandi Besen, AI Research Engineer & Ecosystem Lead at IBM, and Nicholas Renotte, Head of AI Developer Advocacy at IBM. Building a multi-agent system with agents built or used by different teams and organizations can become challenging. You may need to write custom integrations each time a team updates their agent design or changes their choice of agentic orchestration framework. The Agent Communication Protocol (ACP) is an open protocol that addresses this challenge by standardizing how agents communicate, using a unified RESTful interface that works across frameworks. In this protocol, you host an agent inside an ACP server, which handles requests from an ACP client and passes them to the appropriate agent. Using a standardized client-server interface allows multiple teams to reuse agents across projects. It also makes it easier to switch between frameworks, replace an agent with a new version, or update a multi-agent system without refactoring the entire system. In this course, you’ll learn to connect agents through ACP. You’ll understand the lifecycle of an ACP Agent and how it compares to other protocols, such as MCP (Model Context Protocol) and A2A (Agent-to-Agent). You’ll build ACP-compliant agents and implement both sequential and hierarchical workflows of multiple agents collaborating using ACP. Through hands-on exercises, you’ll build: - A RAG agent with CrewAI and wrap it inside an ACP server. - An ACP Client to make calls to the ACP server you created. - A sequential workflow that chains an ACP server, created with Smolagents, to the RAG agent. - A hierarchical workflow using a router agent that transforms user queries into tasks, delegated to agents available through ACP servers. - An agent that uses MCP to access tools and ACP to communicate with other agents. You’ll finish up by importing your ACP agents into the BeeAI platform, an open-source registry for discovering and sharing agents. ACP enables collaboration between agents across teams and organizations. By the end of this course, you’ll be able to build ACP agents and workflows that communicate and collaborate regardless of framework. Please sign up here:

Andrew Ng

105,343 次观看 • 1 年前

there's a lot of content around AI agents but no one is showing you how to actually design them to work reliably that's why I made a full walkthrough breaking down how I think through agent design, using a contract chatbot as an example... inside, I cover: – why I prefer static workflows over free-roaming agents – how I use multiple choice prompts to control next steps – the exact guardrails I use to avoid hallucinations – how the agent answers legal questions and structures outputs into Supabase if you want to see how I actually build agents that don’t break like + reply “agent” and I’ll DM it to you (must be following)

there's a lot of content around AI agents but no one is showing you how to actually design them to work reliably that's why I made a full walkthrough breaking down how I think through agent design, using a contract chatbot as an example... inside, I cover: – why I prefer static workflows over free-roaming agents – how I use multiple choice prompts to control next steps – the exact guardrails I use to avoid hallucinations – how the agent answers legal questions and structures outputs into Supabase if you want to see how I actually build agents that don’t break like + reply “agent” and I’ll DM it to you (must be following)

Tyler

50,606 次观看 • 1 年前

🌎What an unforgettable ride, Panama! Our journey here has been absolutely incredible — amazing energy, inspiring connections, and major milestones achieved for BlockDAG! 🚀✨ A huge THANK YOU to everyone who made this event unforgettable. Panama, you’ll always be a part of our story. But we’re just getting started… Next stop: DUBAI! 🇦🇪 Get ready — we’re taking things to a whole new level!

🌎What an unforgettable ride, Panama! Our journey here has been absolutely incredible — amazing energy, inspiring connections, and major milestones achieved for BlockDAG! 🚀✨ A huge THANK YOU to everyone who made this event unforgettable. Panama, you’ll always be a part of our story. But we’re just getting started… Next stop: DUBAI! 🇦🇪 Get ready — we’re taking things to a whole new level!

BlockDAG Network

13,461 次观看 • 1 年前

happy friday. sneak peek at some new features i'm building for the bankr agent: > sandboxed filesystem (your agent gets its own secure file system in the browser. you control what it can access. no agent running loose on your actual computer) > skill uploads (plugin new capabilities so your agent learns new things) > cli download & access > secure environment variables for api keys > github integration (connect your repo for reads and writes directly from your agent) all of this runs in a secure browser environment. no desktop app. no messy configuration. no downloading agent harnesses from the terminal. just a sandbox you control. in the video: i download an audit skill, run it against a smart contract, and save the report straight to the filesystem. then i ask the agent to pull all my 2026 transactions and write a csv for my accountant.

happy friday. sneak peek at some new features i'm building for the bankr agent: > sandboxed filesystem (your agent gets its own secure file system in the browser. you control what it can access. no agent running loose on your actual computer) > skill uploads (plugin new capabilities so your agent learns new things) > cli download & access > secure environment variables for api keys > github integration (connect your repo for reads and writes directly from your agent) all of this runs in a secure browser environment. no desktop app. no messy configuration. no downloading agent harnesses from the terminal. just a sandbox you control. in the video: i download an audit skill, run it against a smart contract, and save the report straight to the filesystem. then i ask the agent to pull all my 2026 transactions and write a csv for my accountant.

deployer

45,638 次观看 • 4 个月前

WELCOME TO METACADIA! 🌏 Our community is thriving, it’s only right they have a world to call their own. We’ve teamed up with the big brains at Passage to bring you a brand new immersive virtual hub. We’ll be hosting community hangouts, events, and a whole lot more. But first: an exclusive OG's meet-up hosted by russ.base.eth. Get ready to explore!

METACADE

14,981 次观看 • 1 年前

A 100% open-source alternative to n8n! Sim is a drag-and-drop open-source platform to build and deploy Agentic workflows. - Runs 100% locally - Works with any local LLM I used it to build a finance assistance app & connected it to Telegram in minutes. The workflow is simple: - You ask a finance question through Telegram - An Intent Classifier figures out if it's finance-related - If not, you get a polite redirect - If yes, the Finance Agent kicks in Here's what's happening under the hood: The Finance Agent uses Firecrawl for web searches and accesses stock data via Alpha Vantage's API through MCP servers. A Response Agent compiles the info and delivers it. In Sim, every tool or agent you need is available as a block. Just drag them onto the canvas and connect them. Sim agents also support integration with MCP, which is exactly what we did to connect our agent with Alpha Vantage's API. And it's simple to extend. If you want to track crypto or need portfolio analysis, you can just add another Agent. Sim allows easy feature additions without disrupting existing functionality. I have shared the link to Sim's official, open-source GitHub repo in the replies!

A 100% open-source alternative to n8n! Sim is a drag-and-drop open-source platform to build and deploy Agentic workflows. - Runs 100% locally - Works with any local LLM I used it to build a finance assistance app & connected it to Telegram in minutes. The workflow is simple: - You ask a finance question through Telegram - An Intent Classifier figures out if it's finance-related - If not, you get a polite redirect - If yes, the Finance Agent kicks in Here's what's happening under the hood: The Finance Agent uses Firecrawl for web searches and accesses stock data via Alpha Vantage's API through MCP servers. A Response Agent compiles the info and delivers it. In Sim, every tool or agent you need is available as a block. Just drag them onto the canvas and connect them. Sim agents also support integration with MCP, which is exactly what we did to connect our agent with Alpha Vantage's API. And it's simple to extend. If you want to track crypto or need portfolio analysis, you can just add another Agent. Sim allows easy feature additions without disrupting existing functionality. I have shared the link to Sim's official, open-source GitHub repo in the replies!

Avi Chawla

115,816 次观看 • 10 个月前

Here's a longer version of Walz “expansion of Israel” comment, with a bit more context before and after: “Iran, or I– uh– Israel's ability to be able to defend itself is absolutely fundamental. Getting its hostages back: fundamental. And ending the humanitarian crisis in Gaza. But the expansion of Israel and its proxies is an absolute, fundamental necessity for the United States [to] have the steady leadership there. You saw it experienced today, where, along with our Israeli partners and our coalition, able to stop the incoming attack. But what's fundamental here is that steady leadership is gonna to matter.”

Here's a longer version of Walz “expansion of Israel” comment, with a bit more context before and after: “Iran, or I– uh– Israel's ability to be able to defend itself is absolutely fundamental. Getting its hostages back: fundamental. And ending the humanitarian crisis in Gaza. But the expansion of Israel and its proxies is an absolute, fundamental necessity for the United States [to] have the steady leadership there. You saw it experienced today, where, along with our Israeli partners and our coalition, able to stop the incoming attack. But what's fundamental here is that steady leadership is gonna to matter.”

Decensored News

16,799 次观看 • 1 年前

Claude just became a craacked video game designer. With the launch of Unreal Engine's MCP server last week, you can now build entire video games just by talking to Claude. I spent the past few days building with it, and I'm telling you, this is going to forever change how video games get made and who gets to make them. In this video I show you exactly how to set up the Unreal Engine MCP yourself and run through three demos: building a full playable city, cloning a real city from Google Earth, and creating custom buildings in Blender. Here's the agent harness I mention too: Intro What I built in a few hours Setting up the Unreal MCP server Fixing the port 8000 connection issue The agent harness that avoids the pitfalls Demo 1: Building a city with City Sample Demo 2: Cloning a real city from Google Earth with Cesium Demo 3: Custom buildings with Blender headless Outro

Claude just became a craacked video game designer. With the launch of Unreal Engine's MCP server last week, you can now build entire video games just by talking to Claude. I spent the past few days building with it, and I'm telling you, this is going to forever change how video games get made and who gets to make them. In this video I show you exactly how to set up the Unreal Engine MCP yourself and run through three demos: building a full playable city, cloning a real city from Google Earth, and creating custom buildings in Blender. Here's the agent harness I mention too: Intro What I built in a few hours Setting up the Unreal MCP server Fixing the port 8000 connection issue The agent harness that avoids the pitfalls Demo 1: Building a city with City Sample Demo 2: Cloning a real city from Google Earth with Cesium Demo 3: Custom buildings with Blender headless Outro

Pat Simmons

530,640 次观看 • 2 个月前

Our design team has been hard at work developing an incredible story and art to bring the GameGPT Universe to life. So we decided it’s time for another sneak peek. Last time our character sheet was still in early development. This time we wanted to give you a little more! Our first full color character is finally here. What could his story be? Tell us what you think this character is all about in the replies below 👇 Get ready for even more sneak peeks and reveals as we lead up to permit round 3 and our Genesis NFT Mint! Follow us for more as more NFT reveals are just around the corner.

Our design team has been hard at work developing an incredible story and art to bring the GameGPT Universe to life. So we decided it’s time for another sneak peek. Last time our character sheet was still in early development. This time we wanted to give you a little more! Our first full color character is finally here. What could his story be? Tell us what you think this character is all about in the replies below 👇 Get ready for even more sneak peeks and reveals as we lead up to permit round 3 and our Genesis NFT Mint! Follow us for more as more NFT reveals are just around the corner.

GameGPT by PRISM

68,336 次观看 • 2 年前