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🤖 Introducing our Model Context Protocol (MCP) Server The MCP protocol standardizes how apps provide context to LLMs. No more training LLMs — just connect them directly to our blockchain APIs for live token prices, transfers, NFT data, and more 💪 Build smarter AI agents today! Let’s gooooooo 🔗...

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In case you missed it, earlier this week we launched "MCP: Build Rich-Context AI Apps with Anthropic." Enroll now and: ✅ Explore how MCP standardizes access to tools and data for AI applications, its underlying architecture, and how it simplifies the integration of new tools and connections to external systems (e.g., GitHub repos, Google Docs, local files). ✅ Build and deploy an MCP server that provides tools, resources, and prompts, and add it to the configuration of AI applications, such as Claude Desktop, to extend them. ✅ Build an MCP-compatible application that hosts multiple MCP clients, each maintaining 1-to-1 connection to an MCP server. Join in for free:
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In case you missed it, earlier this week we launched "MCP: Build Rich-Context AI Apps with Anthropic." Enroll now and: ✅ Explore how MCP standardizes access to tools and data for AI applications, its underlying architecture, and how it simplifies the integration of new tools and connections to external systems (e.g., GitHub repos, Google Docs, local files). ✅ Build and deploy an MCP server that provides tools, resources, and prompts, and add it to the configuration of AI applications, such as Claude Desktop, to extend them. ✅ Build an MCP-compatible application that hosts multiple MCP clients, each maintaining 1-to-1 connection to an MCP server. Join in for free:

DeepLearning.AI

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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!
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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

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wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.
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wtf is MCP? Paul Klein IV, CEO of explains "Model Context Protocol" (MCP) in plain terms: "There's this new way that people are exposing tools to AI & the 'Model Context Protocol' is one of those ways that you can standardize & give your AI a set of tools to call. BrowserBase has a way to expose the browser to your agent via MCP or MCP server. More & more developers are trying to find ways to integrate more functionalities to their AI agents & BrowserBase's browsers are one of those primitive functionalities, & the MCP is just one way to integrate it into your software." Paul Klein IV From 🅱️'s GitHub: Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. This server provides cloud browser automation capabilities using Browserbase and Stagehand. This server enables LLMs to interact with web pages, take screenshots, and execute JavaScript in a cloud browser environment.

Molly O’Shea

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PSA: Groq Inc now supports remote MCP server integration (BETA). ⚡️ LLMs are only as good as the context you give them and MCP enables you to connect them directly to live APIs, databases, and tools. Now your models can pull fresh data, perform actions, AND respond in seconds.
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PSA: Groq Inc now supports remote MCP server integration (BETA). ⚡️ LLMs are only as good as the context you give them and MCP enables you to connect them directly to live APIs, databases, and tools. Now your models can pull fresh data, perform actions, AND respond in seconds.

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We were super stoked to see Anthropic launch the Model Context Protocol (MCP) this week. 🫡 Today, we’re rolling out the first version of our Cloudflare MCP server with initial support for R2, D1, KV, and Workers.
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We were super stoked to see Anthropic launch the Model Context Protocol (MCP) this week. 🫡 Today, we’re rolling out the first version of our Cloudflare MCP server with initial support for R2, D1, KV, and Workers.

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HeyGen’s new MCP server is live. A protocol to help AI agents talk to external tools and data while generating smarter, more contextual videos. Start building 👇
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HeyGen’s new MCP server is live. A protocol to help AI agents talk to external tools and data while generating smarter, more contextual videos. Start building 👇

HeyGen

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New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:
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New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

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Discover the power of Firebase's MCP Server! 💪 This experimental tool streamlines communication and helps enable secure AI actions on behalf of users. Chapters: 0:00 - Introduction 1:02 - Set up an MCP Server 1:41 - Current Project Demo 2:48 - Data Connect Demo 3:35 - Setting an SMS Region Policy 4:14 - More tools

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An iOS QA agent is coming to a Cursor near you 🍎🤖👷 Announcing ios-simulator-mcp, a Model Context Protocol server for interacting with the iOS Simulator
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An iOS QA agent is coming to a Cursor near you 🍎🤖👷 Announcing ios-simulator-mcp, a Model Context Protocol server for interacting with the iOS Simulator

Joshua Yoes

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This week, ML Scientist @dimid_ml shares an exciting update on the Theoriq Protocol. ⚡️ As MCP gains momentum in connecting AI models with external tools and data, our team has moved fast to integrate an MCP server directly into Theoriq’s SDK. This upgrade makes it easy for agents to register, manage, and update other agents on the protocol, laying the foundation for a more flexible and adaptable agentic ecosystem. More below.
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This week, ML Scientist @dimid_ml shares an exciting update on the Theoriq Protocol. ⚡️ As MCP gains momentum in connecting AI models with external tools and data, our team has moved fast to integrate an MCP server directly into Theoriq’s SDK. This upgrade makes it easy for agents to register, manage, and update other agents on the protocol, laying the foundation for a more flexible and adaptable agentic ecosystem. More below.

Theoriq

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Developers: MCP is about to become extremely relevant as AI needs to connect with real-world data. The problem? Most don't know how to build MCP plugins yet. Here's how to build them with Cline in 3 simple steps using our .clinerules protocol. Thread 🧵
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Developers: MCP is about to become extremely relevant as AI needs to connect with real-world data. The problem? Most don't know how to build MCP plugins yet. Here's how to build them with Cline in 3 simple steps using our .clinerules protocol. Thread 🧵

Cline

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👋 Meet the Model Context Protocol (MCP): the open standard allowing apps to feed vital context to LLMs. Why is this protocol so important? Because context is what turns those generic AI replies into relevant, useful assistance tailored to your work. In this video, ☁️ Chris Reddington explains how MCP delivers this crucial info and why it makes such a difference for AI pair programmers like GitHub Copilot. 💡
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👋 Meet the Model Context Protocol (MCP): the open standard allowing apps to feed vital context to LLMs. Why is this protocol so important? Because context is what turns those generic AI replies into relevant, useful assistance tailored to your work. In this video, ☁️ Chris Reddington explains how MCP delivers this crucial info and why it makes such a difference for AI pair programmers like GitHub Copilot. 💡

GitHub

35,316 Aufrufe • vor 1 Jahr

Ever run into Cursor giving you out of date info when building on Solana? Add the Solana MCP server to provide additional context to Cursor, accelerating your development Learn more 👇
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Ever run into Cursor giving you out of date info when building on Solana? Add the Solana MCP server to provide additional context to Cursor, accelerating your development Learn more 👇

Jacob Creech

18,529 Aufrufe • vor 1 Jahr

In this video, we break down the Model Context Protocol — a massively underrated concept in AI that's quietly redefining what large language models can do. While most people are distracted by the hype, MCP is solving a core problem: LLMs that can perform actions. We dive into: 1. The limitations of current AI systems 2. What makes MCP different 3. How MCP can reduce engineering overhead 4. Real-world scenarios where MCP shines 00:00 What is MCP? 01:48 Usecase - SEO 03:50 Usecase - RAG 04:50 Usecase - Apps 06:30 Conclusion 07:00 The future? #MCP #AI #LLM
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In this video, we break down the Model Context Protocol — a massively underrated concept in AI that's quietly redefining what large language models can do. While most people are distracted by the hype, MCP is solving a core problem: LLMs that can perform actions. We dive into: 1. The limitations of current AI systems 2. What makes MCP different 3. How MCP can reduce engineering overhead 4. Real-world scenarios where MCP shines 00:00 What is MCP? 01:48 Usecase - SEO 03:50 Usecase - RAG 04:50 Usecase - Apps 06:30 Conclusion 07:00 The future? #MCP #AI #LLM

Gaurav Sen

41,097 Aufrufe • vor 1 Jahr

You can now integrate Sardine Issuing Risk APIs using Model Context Protocol (MCP) and LLMs like Claude or tools like Cursor. If you issue cards, you can implement fraud rules directly from your IDE or LLM. Here's how it works 👇
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You can now integrate Sardine Issuing Risk APIs using Model Context Protocol (MCP) and LLMs like Claude or tools like Cursor. If you issue cards, you can implement fraud rules directly from your IDE or LLM. Here's how it works 👇

Soups Ranjan

19,803 Aufrufe • vor 1 Jahr

Just announced: Additional capabilities in MCP Toolbox for Databases designed to empower AI-assisted development! Toolbox is an open-source MCP server that allows developers to easily connect gen AI agents to enterprise data. Learn more →
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Just announced: Additional capabilities in MCP Toolbox for Databases designed to empower AI-assisted development! Toolbox is an open-source MCP server that allows developers to easily connect gen AI agents to enterprise data. Learn more →

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Introducing the official Supabase MCP Server! Supabase MCP Server allows you to read and write to your database, create new projects, apply migrations, and more, right from your favorite AI tools! You can start using them in Cursor or Windsurf today!
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Introducing the official Supabase MCP Server! Supabase MCP Server allows you to read and write to your database, create new projects, apply migrations, and more, right from your favorite AI tools! You can start using them in Cursor or Windsurf today!

Supabase

193,087 Aufrufe • vor 1 Jahr

ICYMI: You can now connect Model Context Protocol (MCP) tools into Amazon Q Developer CLI using an expansive list of AWS pre-built integrations or any MCP servers that support stdio. 🖇️🔌💻 Once connected, Q Developer will provide even more context-aware responses, understand data structures and execute complex queries, without needing to write additional integration code. Get started on our expansive free tier today. 👉
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ICYMI: You can now connect Model Context Protocol (MCP) tools into Amazon Q Developer CLI using an expansive list of AWS pre-built integrations or any MCP servers that support stdio. 🖇️🔌💻 Once connected, Q Developer will provide even more context-aware responses, understand data structures and execute complex queries, without needing to write additional integration code. Get started on our expansive free tier today. 👉

Amazon Web Services

17,048 Aufrufe • vor 1 Jahr

You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!
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You can connect your Supabase database via MCP server to Cursor! The Cursor agent can get the schema and any data from your database through the official Postgres MCP server! This helps Cursor understand your database better when it needs to modify it to add a new feature!

Tyler Shukert

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