continue

Learn how Continue's profiling and workspace configuration works. This guide explains how profiles and workspaces are managed to enhance your IDE experience.

Quickly set up Continue with self-hosted models like Ollama. Follow our guide to configure the ollama provider for seamless local LLM integration.

Discover the NextEditProvider in Continue. This AI powered feature predicts and suggests your next code edit, enhancing your workflow alongside tab-autocomplete for faster development.

Learn how Continue manages token counting and context window limits. It prunes content efficiently to stay within model constraints while preserving key information.

Fix LLM connection issues in Continue with this complete guide. Learn how to troubleshoot errors and configure local runtimes like Ollama and Lemonade effectively.

Understand Continue's authentication and OAuth flow. Learn how MCP integrates with VS Code, JetBrains, and more for secure remote access. Get the details here.

Explore Continue's prompt file system architecture. Customize LLM behavior with version-controlled YAML files. Modify prompts without touching source code.

Learn how Continue enforces rules and policies for code modification. Discover its three-layer architecture for secure and controlled code changes in your repository.

Easily migrate from older Continue config JSON to the new YAML format. Continue automatically converts your legacy settings to streamline your workflow. Discover the simple, automated migration process today.

Learn how to use the Continue SDK a powerful TypeScript interface for IDE, LLM, and context management in your AI assistant projects.

Learn how Continue's edit aggregation clusters keystrokes into diffs for multi-file changes. Understand how edits are isolated and unified for LLM context to improve code editing.

Explore how Continue implements the Model Context Protocol with a deep dive into its layered CLI architecture, Zod validation, transport abstraction, and MCPService for UI tool and prompt exposure.