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⚡day 5 of launch week: from (zero) MCP server to ChatGPT app this is peak developer experience 🤌🏼 1. define your UI in a single react file. 2. test it instantly with hot reload in the built-in Inspector 3. deploy it in one click on mcp-use Cloud 4. ship...

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pederzh

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22,647 görüntüleme • 9 ay önce •via X (Twitter)

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Here's how to deploy your own MCP server in 30 seconds: 1. Remix the Replit template 2. Prompt Agent "create a server that does xyz" 3. Select "Publish" Voila - a streamable HTTP server deployed with API key auth Connect to your sever in your client of choice
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Here's how to deploy your own MCP server in 30 seconds: 1. Remix the Replit template 2. Prompt Agent "create a server that does xyz" 3. Select "Publish" Voila - a streamable HTTP server deployed with API key auth Connect to your sever in your client of choice

matt palmer

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You can now connect your React application to any MCP server! And it only takes a single command: $ npx copilotkit@latest init -m MCP This is massive for anyone building React applications! Using the CopilotKit🪁 MCP Client Component, you can get an MCP Client chat component in your application and instant access to any MCP server out there! It doesn't get easier than this. Check out the link below for instructions on how to proceed ↓
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You can now connect your React application to any MCP server! And it only takes a single command: $ npx copilotkit@latest init -m MCP This is massive for anyone building React applications! Using the CopilotKit🪁 MCP Client Component, you can get an MCP Client chat component in your application and instant access to any MCP server out there! It doesn't get easier than this. Check out the link below for instructions on how to proceed ↓

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Stop what you are doing and get your product on Claude and ChatGPT via MCP! Everyone does most of their work in AI apps now -> let users discover and use you right there. We built Manufact to be the cloud that takes your MCP from first commit to listed.
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Stop what you are doing and get your product on Claude and ChatGPT via MCP! Everyone does most of their work in AI apps now -> let users discover and use you right there. We built Manufact to be the cloud that takes your MCP from first commit to listed.

pederzh

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I'm still picking my jaw off the floor with this MCP update: Postman will now automatically build an MCP server for an API. Automatically! You select your API and the requests you want to include, and Potman will generate a Zip file with everything you need. In collaboration with Postman, I recorded a video showing how I generated an MCP server for the Google Maps API. It's glorious! Also, and before I forget: You can now test any MCP server with your Postman application. They built MCP right in, so now you can: • Connect to an MCP server • List out all of the available tools • Test any of the tools This is a 10x boost for the MCP ecosystem. If you've tried the default MCP debugger, you'll understand how huge a deal it is that you can do all of that from Postman now. Go here to give this a try:
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I'm still picking my jaw off the floor with this MCP update: Postman will now automatically build an MCP server for an API. Automatically! You select your API and the requests you want to include, and Potman will generate a Zip file with everything you need. In collaboration with Postman, I recorded a video showing how I generated an MCP server for the Google Maps API. It's glorious! Also, and before I forget: You can now test any MCP server with your Postman application. They built MCP right in, so now you can: • Connect to an MCP server • List out all of the available tools • Test any of the tools This is a 10x boost for the MCP ecosystem. If you've tried the default MCP debugger, you'll understand how huge a deal it is that you can do all of that from Postman now. Go here to give this a try:

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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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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 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:

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MCP in ~2 min In ~2 min I try to explain what it is, build a MCP server from scratch, connect it to @windsurf, Anthropic, Cursor desktop app, show it working. All code and longer vid below ...

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Chat with Claude Sonnet 3.7 to build your own MCP server. And publish it to GitHub with just a single click. All of this in less than 2 mins.

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Automate Customer Support entirely with Cursor + MCP!! Cursor Agent can now autonomously fetch emails, solve code issues with codebase indexing and reply to these emails. Here's how you can do it in just 2 mins, - Go to Composio's MCP directory - Click on the Gmail app and copy the sse url for Cursor - Add MCP server in cursor and complete auth - Let Cursor fetch emails, solve issues and reply to the query instantly All you need is

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Doom is now an MCP App 🎮 Waiting for the build in Visual Studio Code just got fun with your favorite arcade games! Runs on all MCP Apps hosts: Claude, goose, Postman, and more. My server pulls the games from the awesome Internet Archive. Check it out!
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Doom is now an MCP App 🎮 Waiting for the build in Visual Studio Code just got fun with your favorite arcade games! Runs on all MCP Apps hosts: Claude, goose, Postman, and more. My server pulls the games from the awesome Internet Archive. Check it out!

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Forgot to make dinner plans? No worries, you can now use the Browserbase MCP Server with Raycast to book a fancy place in no time. The everything MCP. Try it out now! Config below.

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Bhanu Teja P

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How to make a custom GPT action: Make your GPT ChatGPT talk to a server on @replit in 5mins 1. use this template 2. deploy in 5 clicks 3. copy paste url & schema (dont forget to lowercase) 4. test. Done. 5. Go wild, ask chatGPT to build itself

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The easiest way to build an MCP Server using Google DeepMind Gemini 2.5 Pro and get started! 1. Use Gitingest to get all the code and docs from the FastMCP repo 2. Download the code into a txt file 3. Go to AI Studio, upload the file, define what kind of MCP Server you want to build 4. Gemini 2.5 Pro builds it for you.

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Codex v0.93.0 introduces the ability to use ChatGPT apps directly in the terminal Enable via /experimental command To enable an app you MUST use $<app> which injects MCP tool functions for that session I like this approach, it means I could have 100 apps and dynamically use
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Codex v0.93.0 introduces the ability to use ChatGPT apps directly in the terminal Enable via /experimental command To enable an app you MUST use $<app> which injects MCP tool functions for that session I like this approach, it means I could have 100 apps and dynamically use

Numman Ali

177,266 görüntüleme • 6 ay önce

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Introducing Open MCP Client 🪁 Chat with any MCP server in your own app, just grab a URL from . The team and I vibe coded with Cursor this weekend and built: 1. The first web-based MCP client (link👇) 2. An open-source client you can add into any app How it's built It uses CopilotKit🪁 for the client and interactivity layer, and connects to a 40 line LangGraph ReAct agent that coordinates MCP calls. Hosted on Vercel. Kudos to Suhas Deshpande and Tyler Slaton for hacking and thanks to Harrison Chase for pointers!

Atai Barkai

299,711 görüntüleme • 1 yıl önce

MCP clearly has demand, But monetizing it has been tricky. I figured out the easiest way to build & monetize a Paid MCP server: 1. mcp-remote package 2. Stripe agent tool kit 3. Cloudflare mcp auth 4. Helicone to track LLM usage I've made a step by step video below + Ready-to-use MCP template with auth & payment Access it at — I drop weekly tips there.
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MCP clearly has demand, But monetizing it has been tricky. I figured out the easiest way to build & monetize a Paid MCP server: 1. mcp-remote package 2. Stripe agent tool kit 3. Cloudflare mcp auth 4. Helicone to track LLM usage I've made a step by step video below + Ready-to-use MCP template with auth & payment Access it at — I drop weekly tips there.

Jason Zhou

42,656 görüntüleme • 1 yıl önce

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:

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