Learn how MCP is transforming AI workflows, offering scalable solutions for developers and enthusiasts alike. It accelerates AI system deployment ...

The Java ecosystem brings you unmatched speed and stability. Here’s our review of seven top-shelf Java microframeworks built ...

Abstract: In a traditional, well-known client-server architecture, the client sends a request to the server, and the server prepares the response by executing business logic that utilizes information ...

Abstract: Federated Learning (FL) is typically deployed in a client-server architecture, which makes the Edge-Cloud architecture an ideal backbone for FL. A significant challenge in this setup arises ...

The Model Context Protocol (MCP) has rapidly become a foundational standard for connecting large language models (LLMs) and other AI applications with the systems and data they need to be genuinely ...

Model Context Protocol, Agent2Agent protocol, and Agent Communication Protocol take slightly different approaches to AI agent communications. Let’s unpack them. Unlike traditional AI models that ...

For a quick introduction to installing and using the plugin, see the Quick Start Guide.

As the field of artificial intelligence (AI) continues to evolve at a rapid pace, fresh research has found how techniques that render the Model Context Protocol (MCP) susceptible to prompt injection ...

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Microsoft’s versatile MarkItDown tool, an open-source Python utility for converting various file types into LLM-friendly Markdown, now includes a server component adhering to the Model Context ...

Developers can now use Pydantic's mcp-run-python server, distributed via JSR, to allow AI agents to execute Python code with automatic dependency handling in isolation. It addresses a frequent ...