Devin Desktop
Devin Desktop (formerly Windsurf) is an AI-powered development environment that combines a full-featured IDE with advanced coding agents in a unified workspace. Formerly known as Windsurf, the platform enables developers to manage local and cloud-based AI agents, delegate tasks, review code, and ship software without leaving their editor. Developers can use multiple coding agents simultaneously to research, write, test, debug, and improve code while maintaining full visibility into every change. Devin Desktop includes features such as agent orchestration, shared workspaces, intelligent code completion, contextual code search, and integrated review tools. The platform supports a wide range of models, extensions, language servers, and MCP integrations, allowing teams to work with their preferred tools and workflows. Devin Desktop helps engineering teams accelerate software development, improve productivity, and manage AI-assisted coding at scale.
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Qdrant
Qdrant is a high-performance, composable vector search engine built in Rust for production-grade semantic, hybrid, and agentic workloads.
Combine dense vectors, sparse vectors, metadata filters, multi-vector representations, and custom scoring as primitives at query time. Written in Rust for memory efficiency, SIMD optimization, and predictable performance without garbage collection pauses. No wrappers, no bolt-ons, no legacy compromises — just a custom HNSW implementation and storage engine built specifically for vector workloads.
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Agent Communication Protocol (ACP)
The Agent Communication Protocol (ACP) is an open interoperability standard designed to enable seamless communication between AI agents, applications, and human users. It provides a standardized RESTful API that supports synchronous and asynchronous interactions, streaming communication, long-running tasks, and both stateful and stateless operations. ACP is framework-agnostic, allowing agents built with technologies such as BeeAI, LangChain, CrewAI, or custom solutions to work together without requiring changes to their internal architecture. The protocol supports all content modalities through MimeTypes, making it flexible enough to handle text, images, audio, video, and custom data formats. ACP also includes capabilities for online and offline agent discovery, helping organizations find and connect compatible agents across different environments.
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Model Context Protocol (MCP)
Model Context Protocol (MCP) is an open protocol designed to standardize how applications provide context to large language models (LLMs). It acts as a universal connector, similar to a USB-C port, allowing LLMs to seamlessly integrate with various data sources and tools. MCP supports a client-server architecture, enabling programs (clients) to interact with lightweight servers that expose specific capabilities. With growing pre-built integrations and flexibility to switch between LLM vendors, MCP helps users build complex workflows and AI agents while ensuring secure data management within their infrastructure.
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