Everywhere

Signal

Everywhere · GitHub · 2026-04-22 Everywhere is a context-aware AI assistant for desktop environments, built on the Avalonia UI framework. It integrates multiple LLM providers and MCP tools to enable seamless, intelligent responses across local workflows.

Context

Desktop AI assistants have evolved from simple chat interfaces to context-aware orchestration layers. This entry captures a tool that emphasizes local UI integration (Avalonia) and multi-provider compatibility, moving beyond single-model dependency. It aligns with the broader shift toward local-first agent infrastructure where users require control over model selection and data flow.

Relevance

Everywhere contributes to the desktop-native agent infrastructure by providing a unified interface for heterogeneous LLM backends. It supports MCP integration, allowing external tools to extend agent capabilities without vendor lock-in. This fits the pattern of local-first desktop agent orchestration, prioritizing user control and local execution over cloud dependency.

Current State

The project is an open-source desktop application utilizing Avalonia for cross-platform UI. It supports multiple LLM providers including OpenAI, DeepSeek, and Ollama-compatible endpoints. MCP tool integration is implemented for expanding agent functionality, and it includes RAG capabilities for document grounding.

Open Questions

• How does the application manage persistent state and memory across sessions compared to vector-based systems?
• What are the specific security boundaries for MCP tool execution within the desktop runtime?
• How does the context window management handle multi-modal inputs locally versus cloud inference?

Connections

• cherry-studio: Similar desktop interface aggregation for multi-model LLM access and agent execution.
• goose: Native open-source AI agent framework with desktop runtime capabilities.
• local-first-desktop-agent-orchestration: Defines the desktop-native infrastructure layer where autonomous agents manage persistent state.