Junie - 2026 Pricing, Features, Reviews & Alternatives

Junie is JetBrains' AI coding agent for teams that need an autonomous agent grounded in real project context, not guesses. It runs inside JetBrains IDEs (IntelliJ IDEA, PyCharm, WebStorm, GoLand, PhpStorm, Rider, RubyMine, RustRover, CLion), as a standalone CLI for Linux, macOS, and Windows, and inside GitHub Actions and GitLab CI/CD pipelines.

Junie plans a task with a strong reasoning model, then implements the approved plan with a faster, cheaper model, so teams spend fewer tokens per task without losing output quality. Plans are saved as structured documents in .junie/plans, covering requirements, technical design, delivery stages, and test strategy, so you can review, edit, and approve before any code changes happen.

Model support: Junie works with almost any model you choose. Use JetBrains AI subscription credits, bring your own API key for Anthropic, OpenAI, Google, xAI, or OpenRouter, or connect a local runtime (LiteLLM, LM Studio, Ollama) to keep inference on your own hardware. New frontier models are supported on day zero of release.

Because Junie runs inside the JetBrains IDE engine instead of a separate approximation of it, it uses the IDE's semantic index for symbol-aware search and refactors, its configured test runners for test discovery and execution, and its real debugger for breakpoints and runtime inspection, including inside decompiled classes and library code. Through DataGrip and the JetBrains Database plugin, Junie also queries and validates against your live database while writing SQL.

Integrations: GitHub Action (triggered from issue and PR comments, opens pull requests, fixes CI failures), GitLab CI/CD (works with GitLab.com and self-managed instances, triggered from issue and merge request comments), Model Context Protocol (MCP) servers for connecting external tools, databases, and APIs, and custom slash commands and Agent Skills for repeatable workflows.

Security and compliance: JetBrains products, including Junie, are SOC 2 certified. The GitHub Action runs entirely on your own GitHub runners, so code stays on your infrastructure. GitLab CI/CD supports self-managed deployments for teams that can't send code to third-party infrastructure. Local model runtime support means prompts and code never have to leave your machine. Every potentially sensitive action, such as editing files outside the project, running terminal commands, or invoking MCP tools, requires explicit approval unless you add it to a configurable Action Allowlist.

Human oversight: Junie asks for approval before risky actions by default. Adjust its autonomy with Brave mode (off, auto, or on) depending on how much you trust it for a given repository. You can send follow-up instructions to a running task without restarting it, and review Junie's changes through an interactive walkthrough before merging.

Customization: Junie reads project-level guidelines (AGENTS.md) so it follows your team's coding standards, naming conventions, and review rules across every session. The IDE plugin and CLI run on the same underlying agent through ACP (the Agent Communication Protocol), so improvements and custom commands apply everywhere at once.

Junie also supports asynchronous work: start a task from your laptop, monitor progress from your phone, and review the finished pull request later. This suits long-running work such as framework upgrades or adding test coverage to a legacy service.