Loading video...

Video Failed to Load

There was a problem loading this video. This could be due to a temporary network issue or the video might be unavailable.

Golf (Golf (YC X25)) is an open-source platform for shipping production-ready MCP servers. Build a server with Golf's OSS framework with auth, telemetry, and debugging included. Deploy with one click, and observe through their hosted platform. Start shipping at Congrats on the launch, Wojciech Błaszak and Antoni Gmitruk!

Y Combinator

1,639,000 subscribers

31,061 views • 1 year ago •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

6 Comments

Mudassir Mustafa ⌥1 year ago

@Golf__mcp Who are the people behind these animations? Really would like to know. amazing work

Rainmaker2 years ago

Here I share an XGBoost model that delivers a 25% CAGR with minimal drawdown on Visa stock. In this free Substack post I share code and commentary for a powerful Machine Learning strategy that delivers powerful returns.

ᴀɴᴅʀᴇᴡ1 year ago

@Golf__mcp tell me more

Alec Polsley1 year ago

@Golf__mcp Now we’re talking 🥲

Wojciech Błaszak1 year ago

@Golf__mcp

Josh1 year ago

@Golf__mcp That's so cool. Hope to find more mcp and agents soon here

Related Videos

.Nitrode (YC W25) is an AI-assisted gaming platform - where you can build, launch, and play your favorite games with ease. Congrats on the launch, Ben Kim, Richard Gu, Brian La, and Sejoon Chang!

.Nitrode (YC W25) is an AI-assisted gaming platform - where you can build, launch, and play your favorite games with ease. Congrats on the launch, Ben Kim, Richard Gu, Brian La, and Sejoon Chang!

Y Combinator

28,135 views • 1 year ago

.Jinba (YC W26) is n8n for enterprise AI automation. Build AI workflows through chat, deploy them to your whole company with one click. Serving 40,000+ users across Fortune 500 Global companies. Congrats on the launch, Takuya Norisugi @jinba(YC 26W) AI and Shoya Matsumori!

.Jinba (YC W26) is n8n for enterprise AI automation. Build AI workflows through chat, deploy them to your whole company with one click. Serving 40,000+ users across Fortune 500 Global companies. Congrats on the launch, Takuya Norisugi @jinba(YC 26W) AI and Shoya Matsumori!

Y Combinator

76,658 views • 5 months ago

🦜Expected Parrot (YC F25) is an open-source framework for simulating your customers with AI agents. Test pricing, refine messaging, and explore product feedback and decisions in minutes, not weeks. Congrats on the launch, John Horton and Robin!

🦜Expected Parrot (YC F25) is an open-source framework for simulating your customers with AI agents. Test pricing, refine messaging, and explore product feedback and decisions in minutes, not weeks. Congrats on the launch, John Horton and Robin!

Y Combinator

71,387 views • 9 months ago

Kestrel (Kestrel AI (YC F25)) is the agentic platform that unifies Kubernetes ops & security, replacing manual triage and on-call firefighting with autonomous investigations and one-click fixes. Congrats on the launch, Raman Varma & Evan Chopra!

Kestrel (Kestrel AI (YC F25)) is the agentic platform that unifies Kubernetes ops & security, replacing manual triage and on-call firefighting with autonomous investigations and one-click fixes. Congrats on the launch, Raman Varma & Evan Chopra!

Y Combinator

19,319 views • 9 months ago

YC S24's Polymet (YC S24) helps non-designers create production-ready designs and frontend code with AI. Explain what you want to build, or provide an image, and Polymet designs and implements it. Congrats on the launch, and Furkan Köseoğlu!

YC S24's Polymet (YC S24) helps non-designers create production-ready designs and frontend code with AI. Explain what you want to build, or provide an image, and Polymet designs and implements it. Congrats on the launch, and Furkan Köseoğlu!

Y Combinator

125,453 views • 2 years ago

.Tensorfuse (YC W24) is a testing and evaluation platform for LLM apps. They make it easy for developers to experiment with various prompts, models, and retrieval methods to find the most effective one. Congrats on the launch agam & samagra14!

.Tensorfuse (YC W24) is a testing and evaluation platform for LLM apps. They make it easy for developers to experiment with various prompts, models, and retrieval methods to find the most effective one. Congrats on the launch agam & samagra14!

Y Combinator

14,195 views • 2 years ago

Airweave (Airweave (YC X25)) is an open-source tool that lets agents search any app. It connects to apps, databases, or document stores and turns their contents into searchable knowledge bases for agents. Congrats on the launch, Lennert Jansen & Rauf!

Airweave (Airweave (YC X25)) is an open-source tool that lets agents search any app. It connects to apps, databases, or document stores and turns their contents into searchable knowledge bases for agents. Congrats on the launch, Lennert Jansen & Rauf!

Y Combinator

77,780 views • 1 year ago

21st (21stdev) is the production layer for frontier AI agents. 1.4M developers already use their platform to build AI apps, 15K+ GitHub stars - now they're making it dead simple to deploy Claude Code, Codex, and other agents to production. Congrats on the launch, sergey bunas & serafim!

21st (21stdev) is the production layer for frontier AI agents. 1.4M developers already use their platform to build AI apps, 15K+ GitHub stars - now they're making it dead simple to deploy Claude Code, Codex, and other agents to production. Congrats on the launch, sergey bunas & serafim!

Y Combinator

33,400 views • 5 months ago

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.

Here is a step-by-step introduction to building a workflow with a custom AI agent that uses MCP. I explain every component in the video: 1. Building the MCP server 2. Building the agent and an MCP client 3. Building a workflow that uses the agent The goal is simple: Generate a dialogue between two people and make one yell and the other answer with sarcasm. Kestra is sponsoring this video. They are an open-source orchestration platform (repo link below), and I used them to build the workflow that connects every component.

Santiago

51,527 views • 1 year ago

Introducing Claude Managed Agents: everything you need to build and deploy agents at scale. It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days. Now in public beta on the Claude Platform.

Introducing Claude Managed Agents: everything you need to build and deploy agents at scale. It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days. Now in public beta on the Claude Platform.

Claude

21,765,344 views • 4 months ago

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!

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

142,137 views • 1 year ago

Fernstone is an AI-powered insurance brokerage for businesses. Their platform handles the back and forth with carriers, autonomously files paperwork, and instantly responds to customer requests. Congrats on the launch, Luke Button, James Chen, and Bryant Le!

Fernstone is an AI-powered insurance brokerage for businesses. Their platform handles the back and forth with carriers, autonomously files paperwork, and instantly responds to customer requests. Congrats on the launch, Luke Button, James Chen, and Bryant Le!

Y Combinator

13,737 views • 10 months ago

Once one of the world's most polluted shipping ports, Canary Wharf may not seem like the obvious place for swimming—but Antoni is ready to dive in! 🏊 #BestOfTheWorld with Antoni Porowski is now streaming on Disney+ and Hulu.

Once one of the world's most polluted shipping ports, Canary Wharf may not seem like the obvious place for swimming—but Antoni is ready to dive in! 🏊 #BestOfTheWorld with Antoni Porowski is now streaming on Disney+ and Hulu.

Nat Geo Travel

20,659 views • 2 months ago

.@oximyhq shows enterprises everything their employees do with AI. Which tools, how much they cost, and where sensitive data is going. One platform for discovery, spend intelligence, and data protection. Congrats on the launch Naman Ambavi!

.@oximyhq shows enterprises everything their employees do with AI. Which tools, how much they cost, and where sensitive data is going. One platform for discovery, spend intelligence, and data protection. Congrats on the launch Naman Ambavi!

Y Combinator

42,225 views • 6 months ago

The $100,000 Higgsfield App Contest is on. Build an app on Claude and deploy it in one click via Higgsfield MCP. 13 winners split the pool, with $25,000 for first place. Submit by July 22. Winners announced July 29. The time to launch your app is NOW.

The $100,000 Higgsfield App Contest is on. Build an app on Claude and deploy it in one click via Higgsfield MCP. 13 winners split the pool, with $25,000 for first place. Submit by July 22. Winners announced July 29. The time to launch your app is NOW.

Higgsfield AI 🧩

91,693 views • 1 month ago

Hypercubic (Hypercubic) is building an agentic AI platform to maintain and modernize COBOL, supporting enterprises with their mission-critical legacy systems from the 1960s. Congrats on the launch Sai & Aayush Naik!

Hypercubic (Hypercubic) is building an agentic AI platform to maintain and modernize COBOL, supporting enterprises with their mission-critical legacy systems from the 1960s. Congrats on the launch Sai & Aayush Naik!

Y Combinator

48,942 views • 7 months ago

Your entire n8n instance is now MCP-ready. Access your workflows through native connectors in Lovable and Mistral AI, with Claude and more platforms on the way! Give it a try with n8n version 1.121.2 and your go-to MCP-enabled platform. 🔗 Watch the full video here:

Your entire n8n instance is now MCP-ready. Access your workflows through native connectors in Lovable and Mistral AI, with Claude and more platforms on the way! Give it a try with n8n version 1.121.2 and your go-to MCP-enabled platform. 🔗 Watch the full video here:

n8n.io

24,395 views • 8 months ago