Loading video...

Video Failed to Load

Go Home

Introducing Vapi's MCP client! Your agent can now call tools from any MCP server (like Zapier or Composio), live in conversations. Access hundreds of tools without any custom integrations. Examples and docs👇

43,181 views • 1 year ago •via X (Twitter)

20 Comments

Vapi's profile picture
Vapi1 year ago

"Can you check on my recent order, reschedule the delivery to Friday and update the support team?" Vapi agent: - Fetches order data from Shopify - Updates Google Calendar - Sends a Slack message

Vapi's profile picture
Vapi1 year ago

"Can you search hacker news for any posts referencing agent protocols in the last week, and send them to the social slack channel?" Vapi agent: - Searches Hacker News - Posts to Slack

Vapi's profile picture
Vapi1 year ago

"I want to check if invoice #1293 was payed" Vapi agent: - Finds invoice (Airtable, Stripe etc.) - Shares payment status

Vapi's profile picture
Vapi1 year ago

Blog post:

Vapi's profile picture
Vapi1 year ago

Docs:

Aitherias's profile picture
Aitherias1 year ago

mcp to find mcp. - ask agent to find and configure - Make mcp.json with: { "mcpServers": { "mcp-search": { "command": "npx", "args": [ "-y", "mcp-search" ] } } }

Daniel Lizio-Katzen's profile picture
Daniel Lizio-Katzen1 year ago

Cool demo - how do you get it to validate your email though?

christian's profile picture
christian1 year ago

This is huge! Congrats guys

Design Chief Priest's profile picture
Design Chief Priest1 year ago

Niceee 🔥

Emanuel Perez's profile picture
Emanuel Perez1 year ago

MCP roaring 20s

Vapi's profile picture
Vapi1 year ago

Yes! They haven't released an official MCP server yet, but if you can build one yourself/use an unofficial one.

WitArist's profile picture
WitArist1 year ago

@ycombinator @ycombinator, this sounds like a game-changing feature! 🚀

Kedar Kubal's profile picture
Kedar Kubal1 year ago

@ycombinator @Vapi_AI This is next-level! I can already imagine my Vapi agent juggling Shopify orders, syncing my Google Calendar, and keeping the team in the loop on Slack—all while I sip my coffee. The MCP client is a fantastic for seamless workflows.

Aaliya's profile picture
Aaliya1 year ago

Sounds amazing tool

Marc_dev's profile picture
Marc_dev1 year ago

nice!

Antaripa Saha's profile picture
Antaripa Saha1 year ago

this is cool!!

FairyFrens ⦼'s profile picture
FairyFrens ⦼1 year ago

@ycombinator this is an exciting advancement in agent communication.

Dave Hayes's profile picture
Dave Hayes1 year ago

This looks GREAT! Solid work

Saïd Aitmbarek's profile picture
Saïd Aitmbarek1 year ago

looks awesome, adding it to our official MCPs for @microlaunchhq v2

PDF GPT's profile picture
PDF GPT1 year 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.

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

141,952 views • 1 year ago