Cline vs Everywhere: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Cline and Everywhere — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Cline
Cline Bot Inc
Open-source coding agent runtime that runs in your IDE, your terminal or embedded via SDK, works with any model, and asks approval on every step.
Key features
- One runtime, three surfaces: The same agent runs as a VS Code extension, a terminal CLI, or embedded in your own product through the SDK
- Model agnostic: Works with Claude, GPT, Gemini, local Ollama or LM Studio models and any OpenAI-compatible endpoint, using your own key or weights
- Plan then Act: Align on a strategy in Plan mode before execution, then approve each step in Act mode or flip on auto-approve
- Multi-file edits with undo: Coordinated changes across a project with linter-aware fixes, diffs, checkpoints and one-click undo on every step
- Live terminal execution: Runs bash commands and reacts to output as it appears, handling dev servers, test runs and deploys
- Rules and Skills: Ship .clinerules with the repo so the agent follows your coding standards, architecture and deployment conventions
- Multi-agent teams: Coordinator agents delegate to specialists with their own tools and context, and can run on cron for recurring automation
- MCP and integrations: Register MCP servers and custom tools, chat from Slack, Discord, Telegram or Linear, and run headlessly in GitHub Actions or GitLab
Best for
- A developer onboarding to an unfamiliar codebase and asking the agent how files, dependencies and behaviour fit together
- Refactoring across a large repository while keeping imports, types and behaviour consistent
- Running recurring maintenance — dependency bumps, lint sweeps, scheduled checks — from cron or a CI pipeline
- A team that must keep code on self-hosted or local models for compliance reasons, pointing the agent at its own endpoint
- Embedding an agent loop inside an internal developer platform via the SDK instead of building one from scratch
- Encoding team conventions in .clinerules so every engineer's agent produces consistent, review-ready changes
- Triggering a coding task from Slack or Linear and having the agent open the resulting change
Everywhere
Sylinko (DearVa)
Context-aware desktop AI assistant that senses your screen, understands application context, and acts in-place across platforms.
Key features
- Context-Aware Invocation: Captures text and UI context directly from the screen so the assistant can answer or act without manual screenshots, copying, or app switching.
- Multimodel Provider Support: Connects to numerous LLM/MCP providers (OpenAI, Anthropic/Claude, Google Gemini, Ollama, DeepSeek, Moonshot, OpenRouter, SiliconCloud) allowing flexible model selection and fallbacks.
- Inline Overlay UI: Modern frosted-glass overlay summoned via keyboard shortcuts that renders Markdown, supports voice input, and displays contextual responses adjacent to the relevant UI element.
- Actionable Responses: Beyond explanations, the assistant can draft emails, translate text, summarize web pages, analyze error messages, and propose step-by-step fixes based on captured context.
- Cross-Platform Desktop Integration: Built with .NET and Avalonia to run on Windows, macOS, and Linux with deep desktop integration for consistent experience.
- Extensibility and Open Source: Distributed under Apache-2.0 with community discussions and contribution paths on GitHub; supports plugins and integration with external tools.
- Privacy and Self-Hosting Friendly: Local client that can be configured to use user-supplied API keys and model endpoints, enabling control over which services process data.
- Context-aware screen sensing that captures and understands visible content without manual screenshots
- Direct desktop integration with context-aware invocation beside content
- Supports multiple model providers and runtimes (OpenAI, Anthropic/Claude, Google Gemini, Ollama, OpenRouter, Moonshot/Kimi, DeepSeek, SiliconCloud, etc.)
- Retrieval-augmented workflows (RAG) and integration with external search / web summarization
- UI-automation capabilities to take actions in applications based on assistant instructions
- Modern UI (frosted-glass style), Markdown rendering and rich text output
- Voice input and keyboard shortcut invocation
- Cross-platform support via Avalonia for Windows, macOS, and Linux
- Extensible via chat/plugins and connectors to model service providers
- Open-source codebase (Apache-2.0) with public documentation and GitHub repository
Best for
- Error Troubleshooting: Summon Everywhere next to an application error message to get a diagnosis and step-by-step remediation without copying the text or leaving the app.
- Quick Research Summaries: Call the assistant while reading a long article or documentation page to produce concise multi-point summaries in-place.
- Instant Translation: Select foreign-language text on-screen and request immediate translation without switching to a separate translator app.
- Email and Writing Polishing: Highlight draft text in an email or editor and ask Everywhere to rephrase, professionalize, or shorten the content inline.
- Contextual Code Help: Invoke the assistant on snippets of code or logs shown on-screen to get explanations, bug-hunting tips, or suggested fixes informed by surrounding context.
- Desktop Task Automation: Use the assistant to perform contextual actions (e.g., copy structured data, open related resources, or run configured workflows) based on UI elements.
- Diagnosing and resolving on-screen error messages by invoking assistant next to the error
- Summarizing long web articles with three-point summaries without leaving the page
- Instant translation of selected foreign text in-place
- Drafting and polishing emails or other text directly from a desktop editor
- Using multiple LLM providers or local runtimes for redundancy, privacy, or cost control
- Automating UI tasks by having the assistant take actions in applications