Loading video...

Video Failed to Load

Go Home

Here is how you can build an MCP server with I built an MCP server that can send emails with Resend in < 1 min. Didn't need to write any code.

20,595 views • 1 year ago •via X (Twitter)

11 Comments

Resend's profile picture
Resend1 year ago

Anything we can do to make a better agent experience in your opinion?

Bhanu Teja P's profile picture
Bhanu Teja P1 year ago

Nothing specific comes to mind. As long as there is an API, that is all is needed. Also, looks like LLMs already know the Resend API without me having to give it manually. So that's another plus.

PDF GPT's profile picture
PDF GPT2 years ago

Everyone is getting ahead with AI. You should be too. Summarize documents, craft emails, and generate custom content instantly with this powerful tool. It's like having ChatGPT tailored for your job. Try it for free.

Mehul Mohan's profile picture
Mehul Mohan1 year ago

@resend very cool

Bhanu Teja P's profile picture
Bhanu Teja P1 year ago

@resend 😀

Virgil Brewster's profile picture
Virgil Brewster1 year ago

@resend This is wild.

Bhanu Teja P's profile picture
Bhanu Teja P1 year ago

@resend 😀

Programmers.App's profile picture
Programmers.App1 year ago

@resend Pure gold Mate!🚀 Are you planning to add a feature to pick different platforms like does? I just imagine copy pasting the output into #n8n or a code editor like #boltdotnew or #cursor. Great work!

Bhanu Teja P's profile picture
Bhanu Teja P1 year ago

@resend I am not sure I understand. Do you mean different platforms to host the MCP server?

Arjun D's profile picture
Arjun D1 year ago

@resend Excited to see platforms like making AI accessible! As I work on my UI/UX projects, I'm curious to see how this tool can help create engaging user experiences without extensive coding.

Bhanu Teja P's profile picture
Bhanu Teja P1 year ago

What do you mean? Have you tried it?

Related Videos

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 views • 1 year ago