Vladyslav Donchenko’s Post

Translation: AI Agents are now easier to create, smarter, and more effective. 2025 is going to be a very interesting year...

Anthropic has open-sourced the Model Context Protocol (MCP) standard to connect AI systems to the data they need—from content repositories to business tools—eliminating silos and enabling smarter, more relevant responses. The MCP standard is an approach for: 🔗 Universal Access: Replace fragmented integrations with a unified protocol. 🔐 Secure & Scalable: Build two-way connections between AI and data while maintaining security. 🚀 Developer-Friendly: Open-source SDKs and pre-built connectors for tools like Google Drive, GitHub, Slack, and more. The standard enables the rapid creation of agentic systems that focus on creativity while the machines handle the mechanics of content retrieval. Anthropic is inviting developers, enterprises, and innovators to explore MCP and help shape the future of context-aware AI. Standards are important and AI is moving quickly. Check out Anthropic's MCP here: https://lnkd.in/e4JRWX7g

Open source isn't just how we build technology— it's how we make innovation accessible to all. We're proud to partner with Anthropic on the Model Context Protocol (MCP), an open standard bridging the gap between AI systems and enterprise data. MCP helps address a critical challenge in the AI space: bridging the gap between advanced models and the data sources they rely on. By enabling AI systems to securely and reliably access information, MCP opens up new possibilities for making AI tools more effective and grounded in real-world applications. Our CTO Dhanji Prasanna on this partnership: "At Block, open source is more than a development model—it's the foundation of our work and a commitment to creating technology that drives meaningful change and serves as a public good for all. Open technologies like the Model Context Protocol are the bridges that connect AI to real-world applications, ensuring innovation is accessible, transparent, and rooted in collaboration." Learn more: https://lnkd.in/grPMihv7

Anthropic's Model Context Protocol (MCP) has the potential to revolutionize how AI connects with data and applications as we build AI agents and applications across different verticals and usecases. Here's why it matters: - Simplifying Connections Connecting AI systems to data sources or tools has always been resource-intensive and error-prone. MCP introduces a standardized approach, eliminating the need for custom integrations and streamlining the process. - Enabling Autonomous and Agentic AI MCP lays the foundation for creating autonomous AI agents that can perform meaningful tasks, maintain context across systems, and act on behalf of users. - Versatile by Design Unlike frameworks limited to specific industries, MCP works universally across AI models, tools, and data sources, making it adaptable to any domain. - Boosting Productivity Direct access to data enables faster and more efficient AI operations, enhancing performance across use cases and making applications more responsive and reliable. One of MCP's most exciting features is its ability to solve the “NxM problem.” Instead of requiring countless custom integrations between multiple AI models (N) and data sources or tools (M), MCP’s standardized framework makes connectivity seamless and scalable. This is a major leap forward—it simplifies integration, boosts performance, and accelerates the development of secure and trustworthy agentic AI systems. At Skyflow, we’re excited to explore how our privacy and security solution for AI along with MCP can empower our customers to build secure AI agents and applications. #Skyflow #AgenticAI #Anthropic #Innovation

What if AI could access and use data as easily as flipping a switch? As someone passionate about connecting data with decision-making, I’m excited by Anthropic’s 𝗠𝗼𝗱𝗲𝗹 𝗖𝗼𝗻𝘁𝗲𝘅𝘁 𝗣𝗿𝗼𝘁𝗼𝗰𝗼𝗹 (𝗠𝗖𝗣)—a game-changer for how AI systems interact with data. MCP establishes an open standard, enabling AI to seamlessly connect with diverse sources like content repositories, business tools, and development environments. This hits home for me because one of the greatest challenges I’ve faced in leveraging AI for better environments is integration bottlenecks—custom solutions for every new data source. MCP changes that equation by simplifying connections and boosting reliability. Why this matters: 🔥 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗕𝗼𝗼𝘀𝘁: MCP’s open standard eliminates the need for custom integrations, cutting deployment times by up to 30%. 🔥 𝗕𝗿𝗼𝗮𝗱 𝗔𝗱𝗼𝗽𝘁𝗶𝗼𝗻: Leaders like Block and Apollo are already on board, while platforms like Zed and Replit are building for the future. 🔥 𝗥𝗲𝗮𝗹-𝗧𝗶𝗺𝗲 𝗔𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲: Reliable data access means fewer delays and better decision-making when seconds count. This isn’t just about tech—it’s about making decisions with clean, defensible data that drive real outcomes. How could it apply to your organization? #AI #DataIntegration #ModelContextProtocol #RealTimePerformance #DataDefensibility source: https://lnkd.in/gFs4jB2R

The new MCP framework is facilitating data workflows and outputs. #MCP #AI #framework #Development #database

Everyday is a new reason to get excited! https://lnkd.in/ew98tUMb MCP or Model Context Protocol is the API of our day… imagine the possibilities! It is a new standard for connecting AI to the systems where data lives, including content repositories, creative and business tools, and development environments, anything. This is massive because it frees AI from the silos that have held it back, letting us connect any data source seamlessly. It means real time personalization, smarter idea generation, and deeper collaboration across every tool we use. Now AI doesn’t just help process data, it understands it, giving us the power to create work that is smarter, faster, and more human. It’s the foundation for a new level of creativity… through connectivity and understanding why those connections are important. Anthropic

Great article by tahpot on his first impressions using Anthropic's Model Context Protocol(MCP):https://lnkd.in/ef6zrs6a Biggest takeaway: 1) MCP is a protocol which standardizes the LLM integration with every data source. You still need to create integration with every data source. 2) It only supports local integrations as of now, so limited usage 3) It needs you to create a server and connecting with your Claude Desktop, so it is a developer tool and it has barrier for normal users to use it. Overall, sounds like a helpful tool, which provides an interface to monitor all your integrations and standardized way to build integrations, but in current state, can't be used much If they create an intuitive way to let people interact any data source with @Claude, that will be awesome feature for non-technical AI chatbot users, so this holds massive potential for Anthropic. Currently they are targeting standardizing data source integration on LLMs for developer, which is already very promising open-source tool to improve GenAI adoption. Read more on MCP: https://lnkd.in/e23mw68Q

Another step forward for enhancing Agentic Workflows. By streamlining the protocol to access data across multiple data sources, AI agents are going to be able to better communicate with external data and hence leading to better sync among themselves.

Linking multiple data sources together,, on demand, just to build a rich context our of your own insights and experiences gives your owned AI the fasttrack to real facts in RAG setups and also for fine-tuning and collaborative training. This MCP release looks like a huge booster for intelligent collaboration, baked by data and AI.