正在加载视频...

视频加载失败

Introducing MCP client-side tooling🪁 Add an MCP client into your React application with a single command $ npx copilotkit@latest init -m MCP Chat with MCP severs inside your app and allow them to be tools for your in-app copilot. Documentation, demo & tutorial 🔗👇

38,050 次观看 • 1 年前 •via X (Twitter)

9 条评论

CopilotKit🪁 的头像
CopilotKit🪁1 年前

MCPs can be used with the CPK Standard Agent -- or inside specialized agents built with the top frameworks through CoAgents. Documentation 📄 Tutorial 👨‍🏫 CoAgents MCP: Demo 💻

MightyBot 的头像
MightyBot1 年前

🧠 Unified Search. Smarter Meetings. Effortless CRM. MightyBot is your AI agent platform for seamless workflows—record meetings, automate CRM updates, and find answers across apps in seconds. 🌟 Focus on what matters. We'll handle the grind.

Anmol 的头像
Anmol1 年前

This is a seriously impressive release in mcp space. Congrats to the entire team! 👏

Bonnie 的头像
Bonnie1 年前

This is awesome. Looking forward to giving it a try.

Arindam Majumder 𝕏 的头像
Arindam Majumder 𝕏1 年前

Great Work Team 👏👏

Avi Chawla 的头像
Avi Chawla1 年前

Great demo, can't wait to try these 🙌

Adam Silverman (Hiring!) 🖇️ 的头像
Adam Silverman (Hiring!) 🖇️1 年前

awesome

Saïd Aitmbarek 的头像
Saïd Aitmbarek1 年前

damn looks really cool, trying it tomorrow :) meanwhile, feel free to push it to @microlaunchhq whenever it helps mate

luizfcouto 的头像
luizfcouto1 年前

@grok , give me some examples of what I can do with a MCP client on a react app

相关视频

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

141,941 次观看 • 1 年前