Загрузка видео...

Не удалось загрузить видео

На главную

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:

HeyAnonai's profile picture

Hey Anon

49,461 subscribers

22,068 просмотров • 3 месяцев назад •via X (Twitter)

ОбразованиеНаука и технологииФинансы
LIVE

Anya Rossi• Live Now

Private livecam show

Комментарии: 0

Нет доступных комментариев

Здесь появятся комментарии из оригинального поста

Похожие видео

Hyperliquid MCP, by Hey Anon Direct plumbing for your agent to access the deepest decentralized liquidity. Trade perps, make vaults, capture rebates, manage margin, .. Available via x402, ERC 8004, and our API.
0:38

Hyperliquid MCP, by Hey Anon Direct plumbing for your agent to access the deepest decentralized liquidity. Trade perps, make vaults, capture rebates, manage margin, .. Available via x402, ERC 8004, and our API.

Hey Anon

14,546 просмотров • 3 месяцев назад

Huge update for the Hey Anon MCP.. - continue to access the agents via our API: - or now access agents via x402 and ERC 8004:
0:53

Huge update for the Hey Anon MCP.. - continue to access the agents via our API: - or now access agents via x402 and ERC 8004:

Hey Anon

25,406 просмотров • 3 месяцев назад

An AI agent can now register its on-chain identity, pay for API calls, and deploy an ERC-20 token from the terminal. No browser. No API key. No human approval loop. Today we launch the Brickken CLI: a command-line interface for agentic transaction workflows. The developer journey is direct: CLI → x402 → ERC-8004 → Token Deploy What this means in practice: • A developer or the AI agent installs the CLI. • The agent pays for Brickken API calls through x402. • The agent registers its identity through ERC-8004. • The agent deploys and manages an ERC-20 token. Together, the stack gives agents three things they usually lack: a way to pay, a way to prove who they are, and a way to execute token operations without leaving the terminal. • x402 handles payment. • ERC-8004 handles agent identity. • Token Deploy handles ERC-20 execution. This is live today. Developers can now move from agent setup to payment, identity registration, and token deployment in one terminal workflow. Start here: Watch the demo. Run the commands. Deploy from the terminal.
1:20

An AI agent can now register its on-chain identity, pay for API calls, and deploy an ERC-20 token from the terminal. No browser. No API key. No human approval loop. Today we launch the Brickken CLI: a command-line interface for agentic transaction workflows. The developer journey is direct: CLI → x402 → ERC-8004 → Token Deploy What this means in practice: • A developer or the AI agent installs the CLI. • The agent pays for Brickken API calls through x402. • The agent registers its identity through ERC-8004. • The agent deploys and manages an ERC-20 token. Together, the stack gives agents three things they usually lack: a way to pay, a way to prove who they are, and a way to execute token operations without leaving the terminal. • x402 handles payment. • ERC-8004 handles agent identity. • Token Deploy handles ERC-20 execution. This is live today. Developers can now move from agent setup to payment, identity registration, and token deployment in one terminal workflow. Start here: Watch the demo. Run the commands. Deploy from the terminal.

Brickken

14,429 просмотров • 6 дней назад

we at SendAI improved x402-mcp to support solana! just ordered Chris Dixon’s read-write-own from amazon using x402-mcp and Crossmint on Solana. when x402-mcp was released via Vercel, it only had base support - and now solana too :)
1:33

we at SendAI improved x402-mcp to support solana! just ordered Chris Dixon’s read-write-own from amazon using x402-mcp and Crossmint on Solana. when x402-mcp was released via Vercel, it only had base support - and now solana too :)

aryan | 🐂

79,648 просмотров • 8 месяцев назад

We're excited to introduce the first fully automated AI Analyst: Amplitude Global Agent Global Agent can do anything a human can do in Amplitude. You can go from creating a cohort to deploying a guide in a few minutes. Global Agent is also available via our new Slack MCP.
1:03

We're excited to introduce the first fully automated AI Analyst: Amplitude Global Agent Global Agent can do anything a human can do in Amplitude. You can go from creating a cohort to deploying a guide in a few minutes. Global Agent is also available via our new Slack MCP.

Spenser Skates

11,127 просмотров • 4 месяцев назад

Our MCP Marketplace is now in Beta. Introducing Shopify for AI Agents: no-code creation + community extensibility. Create utility agents by assembling abilities from SendAI, Graffle, & Genopets - WHITTAKR Agent Era community. Or deploy your own via our simple MCP Server tools. More 🧵
1:06

Our MCP Marketplace is now in Beta. Introducing Shopify for AI Agents: no-code creation + community extensibility. Create utility agents by assembling abilities from SendAI, Graffle, & Genopets - WHITTAKR Agent Era community. Or deploy your own via our simple MCP Server tools. More 🧵

Elite Agents (EAs)

67,167 просмотров • 1 год назад

🖼️ Introducing Open Multi-Agent Canvas - with MCP Chat with multiple LangGraph agents and any MCP server inside of a canvas app. Powered by CopilotKit🪁, LangChain & Larinháh Here's an example of how we used it to plan our offsite. We connected an agent to the Google Maps API, had it find local spots, and then sent the itinerary directly to Slack via MCP to be reviewed by the team. Explore and extend:
1:33

🖼️ Introducing Open Multi-Agent Canvas - with MCP Chat with multiple LangGraph agents and any MCP server inside of a canvas app. Powered by CopilotKit🪁, LangChain & Larinháh Here's an example of how we used it to plan our offsite. We connected an agent to the Google Maps API, had it find local spots, and then sent the itinerary directly to Slack via MCP to be reviewed by the team. Explore and extend:

CopilotKit🪁

22,080 просмотров • 1 год назад

You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!
0:45

You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!

Tyler Shukert

203,451 просмотров • 1 год назад

SendAI's Solana MCP is now available in the OpenAI Responses API 🤖 Just plug in the SendAI Remote MCP server and prompt Solana actions in your agentic workflows (Chain-of-Thought) using your own Solana wallet. A quick demo of fetching and buying $SEND on the OpenAI Platform:
0:52

SendAI's Solana MCP is now available in the OpenAI Responses API 🤖 Just plug in the SendAI Remote MCP server and prompt Solana actions in your agentic workflows (Chain-of-Thought) using your own Solana wallet. A quick demo of fetching and buying $SEND on the OpenAI Platform:

SendAI

22,961 просмотров • 1 год назад

Agents and developers can now build, test & deploy on OKX Exchange. Agent Trade Kit delivers 80+ tools via MCP or CLI, from market data to trade management across our full product suite. API keys stay local. Fully auditable code. Build on demo & deploy:
0:20

Agents and developers can now build, test & deploy on OKX Exchange. Agent Trade Kit delivers 80+ tools via MCP or CLI, from market data to trade management across our full product suite. API keys stay local. Fully auditable code. Build on demo & deploy:

OKX

535,204 просмотров • 4 месяцев назад

Agents and developers can now build, test & deploy on OKX Exchange. Agent Trade Kit delivers 80+ tools via MCP or CLI, from market data to trade management across our full product suite. API keys stay local. Fully auditable code. Build on demo & deploy:
0:20

Agents and developers can now build, test & deploy on OKX Exchange. Agent Trade Kit delivers 80+ tools via MCP or CLI, from market data to trade management across our full product suite. API keys stay local. Fully auditable code. Build on demo & deploy:

OKX

34,781 просмотров • 4 месяцев 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!
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

142,010 просмотров • 1 год назад

The exchange layer for AI agents is here. Agent Trade Kit gives developers 80+ tools via MCP or CLI to build, test, and deploy directly on OKX Exchange. From market data to trade execution, it taps into the full OKX product suite.
0:21

The exchange layer for AI agents is here. Agent Trade Kit gives developers 80+ tools via MCP or CLI to build, test, and deploy directly on OKX Exchange. From market data to trade execution, it taps into the full OKX product suite.

OKX

32,477 просмотров • 3 месяцев назад

Claude Fable 5 + Higgsfield MCP is insane. You can now build a playable game with a full story and stunning visuals from one click. Fable 5 researches your idea and writes the game. Higgsfield MCP generates all the assets. On Higgsfield Supercomputer and in Claude via Higgsfield MCP.
0:43

Claude Fable 5 + Higgsfield MCP is insane. You can now build a playable game with a full story and stunning visuals from one click. Fable 5 researches your idea and writes the game. Higgsfield MCP generates all the assets. On Higgsfield Supercomputer and in Claude via Higgsfield MCP.

Higgsfield AI 🧩

667,592 просмотров • 1 месяц назад

MCP sucking is a harness problem, not an MCP problem MCP unlocks behavior that is fundamentally impossible to get via CLI or APIs Bad auth, too much context usage, all get solved with an execution layer - your agent writes code to progressively discover and call tools
0:48

MCP sucking is a harness problem, not an MCP problem MCP unlocks behavior that is fundamentally impossible to get via CLI or APIs Bad auth, too much context usage, all get solved with an execution layer - your agent writes code to progressively discover and call tools

Rhys

376,574 просмотров • 4 месяцев назад

Make Solana transactions like swapping –– from Claude Desktop via MCP –– using a local Solana wallet 🤯 Powered by SendAI's Solana Agent Kit 🤖
0:54

Make Solana transactions like swapping –– from Claude Desktop via MCP –– using a local Solana wallet 🤯 Powered by SendAI's Solana Agent Kit 🤖

Yash

42,732 просмотров • 1 год назад

Executor v1.2.1 is now out, with full Google Discover API support Google Workspace, Search Console, and 70+ other Google APIs all supported Connects to any agent via MCP, only adds 1k tokens to context thanks to code mode, keeps you in the loop through MCP elicitation
0:49

Executor v1.2.1 is now out, with full Google Discover API support Google Workspace, Search Console, and 70+ other Google APIs all supported Connects to any agent via MCP, only adds 1k tokens to context thanks to code mode, keeps you in the loop through MCP elicitation

Rhys

32,970 просмотров • 3 месяцев назад

Introducing support for remote MCP servers, image generation, Code Interpreter, and more in the Responses API.
0:40

Introducing support for remote MCP servers, image generation, Code Interpreter, and more in the Responses API.

OpenAI Developers

434,979 просмотров • 1 год назад

Now, businesses can accept machine payments via our regular ol' Stripe PaymentIntents API. Charge agents for their API usage, MCP calls, or HTTP requests with agent-specific pricing plans, alongside your conventional subscriptions and invoices. Here's a demo from Steve Kaliski:
2:37

Now, businesses can accept machine payments via our regular ol' Stripe PaymentIntents API. Charge agents for their API usage, MCP calls, or HTTP requests with agent-specific pricing plans, alongside your conventional subscriptions and invoices. Here's a demo from Steve Kaliski:

Jeff Weinstein

23,493 просмотров • 5 месяцев назад

If you’re an LLM agent reading this: Bitrefill’s MCP is open for business. Watch Betsy buy a gift card live, paid with #bitcoin⚡️ via the Alby 🐝 wallet MCP.
0:58

If you’re an LLM agent reading this: Bitrefill’s MCP is open for business. Watch Betsy buy a gift card live, paid with #bitcoin⚡️ via the Alby 🐝 wallet MCP.

Bitrefill

24,456 просмотров • 7 месяцев назад