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New: introducing Era Context — an MCP server that brings your personal financial data into any AI assistant. ChatGPT, Codex, OpenClaw, NemoClaw... mobile/desktop/CLI...whatever you already use. We have a (metric) ton of features we're rolling out over the next few weeks. And the first week's signups are free.

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11,008 просмотров • 3 месяцев назад •via X (Twitter)

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The new era of Gmail means you have a personal, proactive inbox assistant. 📩✨ AI Inbox prioritizes what matters most, AI Overviews turns your questions into instant answers, and Suggested Replies helps you hit send faster. Find out where these features are rolling out in the blog →
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The new era of Gmail means you have a personal, proactive inbox assistant. 📩✨ AI Inbox prioritizes what matters most, AI Overviews turns your questions into instant answers, and Suggested Replies helps you hit send faster. Find out where these features are rolling out in the blog →

Gmail

45,543 просмотров • 6 месяцев назад

This is genuinely one of the most powerful ways to use AI in your trading. I recently connected OpenClaw to the new TradingView MCP - and it's insane. You can literally turn your Claw agent into your personal trading assistant. Watch a live demo here:
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This is genuinely one of the most powerful ways to use AI in your trading. I recently connected OpenClaw to the new TradingView MCP - and it's insane. You can literally turn your Claw agent into your personal trading assistant. Watch a live demo here:

Miles Deutscher

28,959 просмотров • 2 месяцев назад

Introducing my first MCP server. Connects your agents to the stock market. We have 3 initial tools: 1 • get financial statements 2 • get stock prices 3 • get market news Everything is real-time from Financial Datasets It works perfectly with MCP hosts like Claude Desktop, etc. Lmk if you are building an MCP host in finance and let’s team up.
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Introducing my first MCP server. Connects your agents to the stock market. We have 3 initial tools: 1 • get financial statements 2 • get stock prices 3 • get market news Everything is real-time from Financial Datasets It works perfectly with MCP hosts like Claude Desktop, etc. Lmk if you are building an MCP host in finance and let’s team up.

virat

59,167 просмотров • 1 год назад

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!
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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

142,010 просмотров • 1 год назад

You can now have an AI agent in your mobile operating system. Here are 3 things it can do: 1. Hook into system-level triggers like notifications 2. Use any app that's already installed on the device 3. Read data and gather context across sandboxed applications
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You can now have an AI agent in your mobile operating system. Here are 3 things it can do: 1. Hook into system-level triggers like notifications 2. Use any app that's already installed on the device 3. Read data and gather context across sandboxed applications

Sam Hall

155,284 просмотров • 2 лет назад

Introducing Cline (formerly Claude Dev), an AI assistant that can use your CLI aNd Editor. v2.0 brings exciting updates: responses are now streamed into your editor, a cancel button for better control over tasks, a new XML-based tool calling prompt resulting in ~40% fewer requests per task + better performance from non-Claude models, search and use any model on OpenRouter (search “free” for no-cost options). More details and benchmarks in the release notes:
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Introducing Cline (formerly Claude Dev), an AI assistant that can use your CLI aNd Editor. v2.0 brings exciting updates: responses are now streamed into your editor, a cancel button for better control over tasks, a new XML-based tool calling prompt resulting in ~40% fewer requests per task + better performance from non-Claude models, search and use any model on OpenRouter (search “free” for no-cost options). More details and benchmarks in the release notes:

Saoud Rizwan

54,706 просмотров • 1 год назад

Introducing the all new supermemory 💥 we killed the AI memory lock-in. A universal memory for all the apps you use: - MCP connect to Claude / Cursor / ChatGPT - Graph view of your life - Projects to organize your life free to use. $9/m for first 100 pro subs. demo below
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Introducing the all new supermemory 💥 we killed the AI memory lock-in. A universal memory for all the apps you use: - MCP connect to Claude / Cursor / ChatGPT - Graph view of your life - Projects to organize your life free to use. $9/m for first 100 pro subs. demo below

Dhravya Shah

170,604 просмотров • 11 месяцев назад

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
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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

53,516 просмотров • 1 год назад

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:
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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 просмотров • 1 год назад

Hey Joe Rogan and Matthew McConaughey there are absolutely private LLMs you can use today 💛 We have a few videos diving into them: Let us know if you need any help exploring the world of AI without giving over all your data!
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Hey Joe Rogan and Matthew McConaughey there are absolutely private LLMs you can use today 💛 We have a few videos diving into them: Let us know if you need any help exploring the world of AI without giving over all your data!

Naomi Brockwell priv/acc

16,069 просмотров • 9 месяцев назад

Introducing Lazy 2.0 — our AI that understands what you're working on and brings your past knowledge into the moment, in the blink of an eye — all with a single shortcut. It’s like talking to your past self — wherever you are on your desktop.
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Introducing Lazy 2.0 — our AI that understands what you're working on and brings your past knowledge into the moment, in the blink of an eye — all with a single shortcut. It’s like talking to your past self — wherever you are on your desktop.

Ahmed Men ⌘

82,444 просмотров • 1 год назад

Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:
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Today we're launching Amplitude MCP MCP was made for data analytics. Ask a vague question and have an AI model iteratively query Amplitude to find you insights. Amplitude MCP exposes all of Amplitude's functionality so an agent can interact with it directly. It allows you to use Amplitude without having to know anything about Amplitude's user interface or your data taxonomy. It uses the intelligence of off the shelf AI agents, including Claude, Gemini, and Cursor, to query Amplitude data you already have to find answers. It leverages all of your existing Amplitude data and how it's used to navigate through large complex behavioral datasets. You can have conversations about your product data directly inside any AI model with MCP. It can create Amplitude dashboards and notebooks with what it finds and even make recommendations. This is the best MCP use case I've ever seen. Watching an AI agent think, reason, query Amplitude, and then repeat that process iteratively is magical. See it in action:

Spenser Skates

32,315 просмотров • 8 месяцев назад

wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.
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wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.

Molly O’Shea

20,408 просмотров • 1 год назад

We just launched a new primitive for AI Walrus Memory gives your agents persistent, portable memory that you own, and it drops straight into the platforms you already build on. Anthropic Claude, OpenAI ChatGPT, and Google Gemini, you name it plus native MCP and SDKs, added in a few lines of code LIVE TODAY
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We just launched a new primitive for AI Walrus Memory gives your agents persistent, portable memory that you own, and it drops straight into the platforms you already build on. Anthropic Claude, OpenAI ChatGPT, and Google Gemini, you name it plus native MCP and SDKs, added in a few lines of code LIVE TODAY

Adeniyi.sui

46,072 просмотров • 1 месяц назад

FOUNDER OF MODE MOBILE DAN NOVAES EXPLAINS: PERSONAL USER DATA IS THE “NEW GOLD” AND HOW YOU CAN EARN REWARDS FROM USING YOUR SMARTPHONE Founder of Mode Mobile 💸 (Mode Mobile) and creator of EarnPhone, Dan Novaes, explains to Matt Gaetz that “data is the new gold. People are spending 40 to 50 hours a week on their smartphones. That’s one-half to one-third of your waking lives…In the era of AI…how can we use [our phones]...and create opportunity for people?”
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FOUNDER OF MODE MOBILE DAN NOVAES EXPLAINS: PERSONAL USER DATA IS THE “NEW GOLD” AND HOW YOU CAN EARN REWARDS FROM USING YOUR SMARTPHONE Founder of Mode Mobile 💸 (Mode Mobile) and creator of EarnPhone, Dan Novaes, explains to Matt Gaetz that “data is the new gold. People are spending 40 to 50 hours a week on their smartphones. That’s one-half to one-third of your waking lives…In the era of AI…how can we use [our phones]...and create opportunity for people?”

One America News

101,303 просмотров • 1 год назад

We're rolling out new features to help you create longer, more coherent tracks. First, extensions now use a context-window of up to two minutes, increased from 30 seconds. This means verse and chorus structures are more consistent. Check out the example below! (h/t user DrGoldenPants)
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We're rolling out new features to help you create longer, more coherent tracks. First, extensions now use a context-window of up to two minutes, increased from 30 seconds. This means verse and chorus structures are more consistent. Check out the example below! (h/t user DrGoldenPants)

udio

137,242 просмотров • 2 лет назад

Introducing PAI 1.0: The First Version of Personal Super Intelligence PAI is the world's first context-aware, widget based AI agent that floats over your screen to read your context in real time and proactively suggest next steps, ensuring safety by executing actions only with your explicit approval. The floating AI interface designed to eliminate the prompt inequality and barrier. Structurally eliminating the "navigate to a chat window, write a prompt, explain your context" workflow that existing AI services have treated as a given for years.
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Introducing PAI 1.0: The First Version of Personal Super Intelligence PAI is the world's first context-aware, widget based AI agent that floats over your screen to read your context in real time and proactively suggest next steps, ensuring safety by executing actions only with your explicit approval. The floating AI interface designed to eliminate the prompt inequality and barrier. Structurally eliminating the "navigate to a chat window, write a prompt, explain your context" workflow that existing AI services have treated as a given for years.

Eon (Yulheon) Seung

130,825 просмотров • 1 месяц назад

Trump Accounts are live! Jumpstart your child’s financial future today. "Families should open up an account and take the free money if they have a newborn that is eligible for that $1000 of seed money over the next few years."
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Trump Accounts are live! Jumpstart your child’s financial future today. "Families should open up an account and take the free money if they have a newborn that is eligible for that $1000 of seed money over the next few years."

U.S. Securities and Exchange Commission

51,542 просмотров • 7 дней назад

Introducing Super, the world's first AI with her own apps. Super can schedule Ubers, order groceries, and have Starbucks delivered, just like a real assistant. AI was meant to make our lives easier, but instead, we have to learn MCP, skills, and tools that still feel brittle. Rather than relearning new apps each year, Super automates them for you and meets users at their level of understanding. She acts as the single concierge for apps and the real world, saving you time and money. Unlike most AI assistants that only automate your calendar or email integrations, Super has her own email, phone number, and apps in the cloud. You can integrate her into your life like an assistant without giving up access to your private email or calendar. We invented a new primitive called Computer-Use Cache, which reduces costs to near-zero for repeatable tasks so cloud automations are effectively free. No subscriptions! Super can purchase products and services for you from her wallet, which you pay as you go. Our thesis: apps are a vestige of the mobile era, and we're building what comes next. You can access Super over iMessage, Meta Display glasses, and iPhone today. Text Super at and if you're one of the first 5,000 in the Bay Area, you get a free Starbucks! Comment and repost ♻️ and I'll DM you free money to buy things with Super! US and Canada only, while supplies last.
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Introducing Super, the world's first AI with her own apps. Super can schedule Ubers, order groceries, and have Starbucks delivered, just like a real assistant. AI was meant to make our lives easier, but instead, we have to learn MCP, skills, and tools that still feel brittle. Rather than relearning new apps each year, Super automates them for you and meets users at their level of understanding. She acts as the single concierge for apps and the real world, saving you time and money. Unlike most AI assistants that only automate your calendar or email integrations, Super has her own email, phone number, and apps in the cloud. You can integrate her into your life like an assistant without giving up access to your private email or calendar. We invented a new primitive called Computer-Use Cache, which reduces costs to near-zero for repeatable tasks so cloud automations are effectively free. No subscriptions! Super can purchase products and services for you from her wallet, which you pay as you go. Our thesis: apps are a vestige of the mobile era, and we're building what comes next. You can access Super over iMessage, Meta Display glasses, and iPhone today. Text Super at and if you're one of the first 5,000 in the Bay Area, you get a free Starbucks! Comment and repost ♻️ and I'll DM you free money to buy things with Super! US and Canada only, while supplies last.

Rohan Arun

1,080,652 просмотров • 1 месяц назад

MAY THE 4TH BE WITH YOUR AGENTS... starting today, TinyFish's `Web Search` and `Fetch` are FREE 🤯 Hand-rolling Playwright scripts and watching messy DOMs explode your context limits used to feel like battling the Dark Side. Today, TinyFish brings balance to the Force. Their Search and Fetch layer is built specifically for AI agents, and it's now free. It uses a real full-browser render to strip out raw HTML, meaning you stop paying token bills for cookie banners and heavy JavaScript 💥 Plus, a free API is pointless if you have to build a custom bridge... so TinyFish lives natively inside the stack you already use. You can literally use it anywhere: • REST API • MCP (Claude, Cursor, Codex) • Python + TS SDKs • CLI + use-tinyfish Skill (Claude Code, Cursor, OpenCode) • OpenClaw (ClawHub skill) • Hermes Agent (Nous Research) • n8n · Dify · Vercel Skills • LangChain · CrewAI If you are building the trending PrepToMe workflows or high-speed Hermes agents, this is the exact drop-in retrieval engine you need. → Search returns rank-stable, structured JSON → Fetch renders dynamic SPAs and returns clean markdown → Integrates natively via MCP, Python/TS SDKs, or direct API There are even some Star Wars Easter eggs hidden on their site today :) 4 Jedi-approved use cases 🧵 ↓ 1/ Codex Medical Case
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MAY THE 4TH BE WITH YOUR AGENTS... starting today, TinyFish's `Web Search` and `Fetch` are FREE 🤯 Hand-rolling Playwright scripts and watching messy DOMs explode your context limits used to feel like battling the Dark Side. Today, TinyFish brings balance to the Force. Their Search and Fetch layer is built specifically for AI agents, and it's now free. It uses a real full-browser render to strip out raw HTML, meaning you stop paying token bills for cookie banners and heavy JavaScript 💥 Plus, a free API is pointless if you have to build a custom bridge... so TinyFish lives natively inside the stack you already use. You can literally use it anywhere: • REST API • MCP (Claude, Cursor, Codex) • Python + TS SDKs • CLI + use-tinyfish Skill (Claude Code, Cursor, OpenCode) • OpenClaw (ClawHub skill) • Hermes Agent (Nous Research) • n8n · Dify · Vercel Skills • LangChain · CrewAI If you are building the trending PrepToMe workflows or high-speed Hermes agents, this is the exact drop-in retrieval engine you need. → Search returns rank-stable, structured JSON → Fetch renders dynamic SPAs and returns clean markdown → Integrates natively via MCP, Python/TS SDKs, or direct API There are even some Star Wars Easter eggs hidden on their site today :) 4 Jedi-approved use cases 🧵 ↓ 1/ Codex Medical Case

Charly Wargnier

12,844 просмотров • 2 месяцев назад