Overview
Everywhere is a context-aware desktop AI assistant designed to seamlessly integrate multiple local and remote LLMs alongside MCP tools to deliver intelligent interactions and automation. It supports local model usage and remote backends, offers a plugin-based tooling ecosystem for retrieval, browser/UI automation, and task orchestration, while emphasizing privacy and extensibility.
Key features
- Multi-model support: integrate Ollama, OpenAI and other providers for flexible local/remote inference.
- MCP tool integration and plugin system for retrieval, UI automation, and external service calls.
- Desktop & UI automation: interact with OS interfaces to automate repetitive workflows and context-driven assistant behaviors.
Use cases
- Improve research productivity by enabling quick desktop search, summarization and note/report generation.
- Automate repetitive tasks via UI automation scripts and assistant-driven workflows.
- Run models locally in privacy-sensitive or offline scenarios to reduce data exposure.
Technical highlights
- Open-source implementation using C# and cross-platform UI frameworks (e.g., Avalonia) for desktop deployment.
- Agentic design with MCP/tool calling, decomposing tasks into retrievable sub-tasks and callable tools for extensibility and testing.
- CI/CD and plugin ecosystem to keep integrations and model backends up to date.