正在加载视频...

视频加载失败

Supabase MCP server now supports creating and deploying Edge Functions! Refresh your MCP server and make sure you have the `deploy_edge_function` tool, and you are good to go! Just ask your AI tool to create an edge function or a backend, and it will create it for you!

28,997 次观看 • 1 年前 •via X (Twitter)

11 条评论

Blake 的头像
Blake1 年前

Can someone explain Supabase MCP on a 5th grade reading level ?

PDF GPT 的头像
PDF GPT1 年前

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.

0xRecruiter 的头像
0xRecruiter1 年前

Finally fam! The last few weeks have been a pain with how cursor has been handling the supabase MCP function, since I have so much data and tables I get the “conversation too long” error whenever the MCP tries to read the database table names

Tristan Rhodes 的头像
Tristan Rhodes1 年前

This is very useful! Keep up the great work.

Fili 的头像
Fili1 年前

awesome. I remember creating and testing edge functions in cursor for hours. It was pain in the ass

Dream of Sakura P 的头像
Dream of Sakura P1 年前

Amazing

Renato Abreu 🍃 的头像
Renato Abreu 🍃1 年前

This is integrated with @lovable_dev , can I use it there?

Chingis Alekenov 的头像
Chingis Alekenov1 年前

Cool, thank you

Dream of Sakura P 的头像
Dream of Sakura P1 年前

Will it work in windsurf ai ? Or is it only for Cursor ?

Evren Dombak 的头像
Evren Dombak1 年前

@supabase finally 🙌

Kalyan Dechiraju 的头像
Kalyan Dechiraju1 年前

Do we have options to create the db schema or edge functions locally first and then deploy? Or does MCP always deploys to cloud instance?

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