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Continue

AI agents inside your IDE, managed from the cloud

Continue embeds AI agents directly into IDEs like VS Code and Android Studio, and lets you manage cloud agents through a central Mission Control interface. You can connect multiple model providers, run agents locally or remotely, and wire them up with tools, secrets, and codebase indexing. It’s aimed at developers and teams who want configurable, agentic workflows rather than a simple chat bot in the editor.

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About

What It Is

Continue is an AI assistant and agent framework built around your development environment. It runs as an IDE extension (with documented support for VS Code, Android Studio, and code-server) and connects those editors to large language models and tools that can act on your codebase and environment. On top of the editor plugins, it offers a Mission Control web interface for managing cloud-based agents.

The product is aimed squarely at developers and engineering teams who want deep IDE integration plus centralized control over AI agents. From the docs, you configure models and behavior via local YAML/JSON config files and/or through Mission Control, including details like certificates, proxies, and provider-specific options. It supports popular model providers such as OpenAI and OpenRouter, as well as local and remote models through Ollama, and can run in remote/dev container setups like code-server and WSL.

What to Know

According to the documentation, Continue supports an "agent mode" with tools, and a Mission Control "Agents" page that gives you a single view of all your cloud agents—where they run, how they’re triggered, and how to reuse them. This points to a genuinely agentic setup, not just inline chat: agents can be wired to external tools, depend on secrets and environment variables, and operate across projects. At the same time, this flexibility comes with configuration overhead: you may need to manage certificates, proxy behavior, local vs. remote Ollama connectivity, and per-model tool capabilities before everything works smoothly.

There are some clear technical caveats in the docs. Codebase indexing on Linux requires modern CPU features (AVX2 and FMA), and will be disabled otherwise. Models must explicitly support tools for agent mode to function, and a fair amount of troubleshooting guidance is devoted to networking issues (corporate proxies, SSL certificates, WSL, Docker) and provider-specific errors (OpenAI, OpenRouter, Ollama). Privacy and data-handling practices aren’t detailed in the FAQ beyond how secrets and environment variables are stored (locally via .env files or managed through Mission Control), so you’ll need to consult their main site or security docs if that’s critical.

Continue is a good fit if you’re a developer or team comfortable editing config files and debugging IDE/network quirks to get a powerful, customizable agent setup. It’s not well suited to non-technical users looking for a simple web chatbot, or to environments that can’t satisfy the documented hardware and networking requirements. Pricing information isn’t provided in the FAQ, so you’ll need to check their main site or repository for current licensing and plans.

Key Features
Runs as an IDE extension for VS Code with support for the right-hand sidebar and keyboard shortcuts (e.g., cmd/ctrl+L) to open the Continue panel
Works in additional development environments including Android Studio and code-server, with guidance for running in secure/remote setups
Connects to multiple model providers via configuration, including OpenAI and OpenRouter (with provider-specific error handling documented)
Integrates with local and remote LLMs through Ollama, including troubleshooting for WSL, Docker, and network connectivity scenarios
Supports an agent mode where models can use tools, enabling more autonomous agent behavior than basic chat completion
Use Cases
A backend engineer using VS Code wants AI agents that can operate on their repository, with cloud agents centrally managed and reusable across different projects via Mission Control.
A developer working behind a corporate proxy configures custom certificates and leverages VS Code’s proxy support so Continue can securely reach OpenAI or OpenRouter models.
A team running local LLMs with Ollama on a shared server wires those models into Continue, handling WSL and Docker networking so IDE agents can call the local models instead of cloud providers.
Agenticness Score
8/ 20
Level 2: Capable

Handles multi-step tasks with guidance

Overall, Continue enables capable, tool-using coding agents embedded in IDEs, with a strong focus on configurability, networking/security integration, and operational observability via Mission Control. It supports multiple models, tools, secrets, and codebase indexing, letting agents act beyond simple chat. However, based on the provided information, its autonomy appears mainly constrained to responding to user-driven triggers within the IDE, and there is no clear evidence of advanced multi-step planning, persistent personal memory, or formal approval/permission frameworks. This places it as a Level 2 agentic system: a capable, tool-using agent with moderate autonomy and solid operational robustness, but not fully autonomous or self-directed.

Score Breakdown

Action Capability
2/4
Autonomy
2/4
Adaptation
2/4
State & Memory
1/4
Safety
1/4

Categories

Pricing
  • Pricing not publicly available
Details
Website: continue.dev
Added: January 22, 2026
Last Verified: January 22, 2026
Agenticness: 8/20 (Level 2)
Cite This Listing
Name: Continue
URL: https://agentic-directory.onrender.com/t/continue
Last Updated: January 29, 2026

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