Continue
The open-source AI coding assistant for VS Code and JetBrains
About Continue
Continue is an open-source AI coding assistant that integrates directly into VS Code and JetBrains IDEs, offering chat, inline editing, autocomplete, and autonomous agent capabilities. It supports any LLM — including OpenAI, Anthropic, Gemini, and local models via Ollama — giving teams full control over their AI stack without vendor lock-in. Teams can also use Continue's CI-integrated PR review checks to enforce custom code standards across every pull request.
Pros & Cons
Pros
- Completely free and open-source (Apache 2.0) with no feature paywalls on core IDE functionality
- Works with virtually any LLM including local models, preventing vendor lock-in and enabling full data privacy
- Supports both VS Code and all JetBrains IDEs, covering most developers' preferred environments
- Team configuration stored in-repo via .continue/rules/ ensures consistent AI behavior across the team
- MCP integration brings real-time context from GitHub, Sentry, Snyk, and Linear directly into AI responses
- CI-integrated PR checks let teams enforce custom code standards automatically on every pull request
Cons
- Requires more manual setup and configuration than polished paid alternatives like GitHub Copilot or Cursor
- Code edit quality depends heavily on the chosen model — the tool is only as good as the underlying LLM
- Some features (stability, advanced agent behavior) are still maturing and may have bugs
- The Hub cloud features add cost on top of your LLM API spend, which can become complex to manage
Key Features
AI Chat in IDE
Context-aware chat assistant embedded in your editor. Select code, ask questions, get explanations, and apply changes without leaving VS Code or JetBrains.
Inline Edit
Trigger inline edits with a keyboard shortcut, describe a change in natural language, and have the AI rewrite the selected code block in place.
Autocomplete
Real-time AI-powered inline code suggestions as you type, functioning like enhanced IntelliSense backed by any supported LLM including local models.
Agent Mode
Autonomous agent that can plan multi-step tasks, search the codebase, edit files, run terminal commands, and iterate — reducing manual context gathering.
Bring Your Own LLM
Connect any AI model provider: OpenAI, Anthropic, Google Gemini, Mistral, Cohere, or local models via Ollama. No forced vendor dependency.
Model Context Protocol (MCP)
Integrates with MCP-compatible tools such as GitHub, Sentry, Snyk, and Linear to pull live context from your development workflow into AI responses.
PR Quality Checks (CI)
Define custom code standards as markdown files. Continue runs AI checks on every pull request and reports pass/fail as GitHub status checks.
Team Configuration Sharing
Store shared AI rules, prompts, and standards in .continue/rules/ inside your repository so all team members use consistent configuration.
Local & Private Model Support
Run entirely on local models (Ollama, llama.cpp) to keep code and prompts 100% private and never send data to third-party cloud providers.
Open Source & Extensible
Apache 2.0 licensed. Fully customizable through configuration files, custom context providers, slash commands, and community-built extensions.
Pricing
- VS Code and JetBrains extension
- Chat, Edit, Autocomplete, and Agent modes
- Bring your own LLM
- Full open-source codebase (Apache 2.0)
- MCP tool integrations
- Team configuration via .continue/rules/
- Access to frontier AI models via Continue Hub
- Create and run AI agents
- Integrations (Slack, Sentry, Snyk)
- Automated PR checks (GitHub status checks)
- All Starter features
- $10 in model credits per seat per month
- Team agent management and sharing
- Agent access permission controls
- SSO login
- All Team features
- Custom SSO (SAML or OIDC)
- Bring your own API keys
- Invoicing and SLA agreements
- Priority support
Best For
Privacy-First AI Coding
Teams handling sensitive or proprietary code can connect Continue to local Ollama models, keeping all code and prompts entirely on-premises.
Multi-LLM Experimentation
Developers who want to compare different AI models (Claude vs GPT-4 vs Gemini) for coding tasks without switching tools or paying multiple subscriptions.
Automated PR Code Review
Engineering teams enforce custom code standards by defining checks as markdown files. Every PR gets AI-powered pass/fail analysis as a GitHub status check.
Team AI Standardization
Orgs wanting all developers to use the same AI rules and context sources can commit a .continue/ directory and have everyone inherit those settings.
Autonomous Multi-File Refactoring
Senior developers use Agent mode to delegate large, multi-step refactoring tasks while retaining review control.
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