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Who brought developers into this conversation? The disrespect is wild. An average designer with the right Codex, Claude, or Cursor setup, .md file, plus a CLI and MCP server, can literally make some of you irrelevant. Let that sink in.

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TimX | Million-Dollar UX Design 🚀

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111,189 görüntüleme • 3 ay önce •via X (Twitter)

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Spatial now ships with a built-in MCP server, so you can use whole boards as context for Claude or Codex. As an example, you can let Claude analyze your visuals, reverse engineer a style prompt, and then save that prompt back as a new note.
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this has been the most requested feature for years now. FlutterFlow MCP is here. you can now bring your agents directly into FlutterFlow and switch between them: Claude Code, Gemini CLI, Codex, or any MCP-compatible client. can’t wait to see what y’all build.
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Introducing Asterisk MCP - An MCP server that fixes security vulnerabilities while you vibe code. Supports Cursor, Windsurf, Cline, Claude, and any IDE that supports the model context protocol. It can perform codebase-wide scans, analyze snippets in your conversation history, and verify changes/fixes for security issues. mcp dot asterisk dot so
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Introducing Asterisk MCP - An MCP server that fixes security vulnerabilities while you vibe code. Supports Cursor, Windsurf, Cline, Claude, and any IDE that supports the model context protocol. It can perform codebase-wide scans, analyze snippets in your conversation history, and verify changes/fixes for security issues. mcp dot asterisk dot so

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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!

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