DevoxxGenieIDEAPlugin
Free, open-source AI code assistant plugin for JetBrains IDEs with spec-driven development and Agent Mode
If your editor is JetBrains and you object to another AI subscription, start here. DevoxxGenie costs nothing and gives you spec-driven tasks, parallel sub-agents and local-model inference that Copilot's sidebar does not attempt. The catch is real: you supply provider keys, and MCP servers plus local runtimes take an afternoon to wire up. Want a zero-config assistant? This will feel fiddly.
Verified 3d ago · liveness 66/100 · cite: rightaichoice.com/tools/devoxxgenieideaplugin
- JetBrains IDE users on IntelliJ IDEA, PyCharm or WebStorm who want an AI assistant without a subscription
- Teams adopting spec-driven development with traceable tasks and acceptance criteria
- Developers who need local or self-hosted inference for privacy and data control
- Cost-conscious engineers mixing cheap models for sub-agents with a strong coordinator model
- Developers working primarily in VS Code, Eclipse or other non-JetBrains editors
- Teams that want a managed, zero-configuration assistant with no provider setup
- Anyone unwilling to supply their own API keys or run a local model server
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Skip DevoxxGenie if you work outside JetBrains IDEs, or if you want a managed assistant that runs without you supplying your own model keys or hosting a local model server.
The plugin itself is free, but every prompt runs on your own provider account, so OpenAI, Anthropic or Gemini usage bills land on you separately.
DevoxxGenie carries no licence fee at all — it is 100% open source and free, distributed via the JetBrains Marketplace. Your real spend is model usage on whichever provider you connect: a local Ollama or LM Studio setup costs nothing beyond hardware, while cloud models bill per token on your own account. Against paid subscriptions like GitHub Copilot or JetBrains AI Assistant, that makes DevoxxGenie cheapest for anyone already paying for model API access, and potentially more expensive for
In short
DevoxxGenieIDEAPlugin — Free, open-source AI code assistant plugin for JetBrains IDEs with spec-driven development and Agent Mode. Best for JetBrains IDE users on IntelliJ IDEA, PyCharm or WebStorm who want an AI assistant without a subscription, Teams adopting spec-driven development with traceable tasks and acceptance criteria, Developers who need local or self-hosted inference for privacy and data control. Free to use.
What's new in DevoxxGenieIDEAPlugin
Checked yesterdayAcross the latest 1 update: 1 feature update.
What people actually say about DevoxxGenieIDEAPlugin — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
9 mentions across 2 sources (YouTube, GitHub) · researched Jul 6, 2026.
Average across the 2 sources that answered — each source counts once, not each post.
- +Completely free and open-source with no usage caps.
- +Supports both local and cloud LLMs for privacy and flexibility.
- +Agent mode with 17 built-in tools for complex tasks.
- +NVIDIA integration offers over 100 free models.
- +MCP support with marketplace expands capabilities.
- −Frequent UI bugs like black screens and broken elements.
- −Setup for local models is not beginner-friendly.
- −Session persistence: provider selection resets on project switch.
- −Timeout errors with local models are common.
- −RAG feature often fails to populate required services table.
- • API costs for cloud providers (OpenAI, Anthropic, etc.) can add up
- • Local LLM hardware requirements (e.g., GPU RAM for large models)
Viability Score
How well maintained and how widely used is DevoxxGenieIDEAPlugin? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Spec-driven development with structured task specs and acceptance criteria
- Backlog.md integration with 17 built-in backlog tools
- Backlog Browser grouping tasks by To Do, In Progress and Done
- Agent Mode with read_file, write_file, edit_file, list_files, search_files and run_command
- Write operations gated by safety approvals
- Parallel sub-agents up to 10, each with its own model, provider and tool budget
- Agent Mode running fully on local models such as GLM-4.7-flash via Ollama
- MCP support with in-IDE marketplace for browsing and installing servers
- MCP debugging panel to inspect requests and responses in real time
- Security scanning via Gitleaks, OpenGrep and Trivy, filed as prioritised backlog tasks
- Inline code completion using Fill-in-the-Middle models via Ollama or LM Studio
- CLI runners for Claude Code, GitHub Copilot, OpenAI Codex, Gemini CLI and Kimi
- Personas to switch system prompt per mode (v1.13.0)
- Editable built-in tool descriptions in Settings without changing the system prompt (v1.13.0)
- Diff/merge view for reviewing and approving agent changes
About DevoxxGenieIDEAPlugin
DevoxxGenie is a fully Java-based LLM code assistant plugin that runs inside JetBrains IDEs — IntelliJ IDEA, PyCharm, WebStorm and the rest of the family. It connects to local runtimes like Ollama, LM Studio, Nativ and GPT4All alongside cloud providers such as OpenAI, Anthropic, Mistral, Groq, Kimi, GLM and Gemini. It's 100% open source and free under a Bring Your Own Keys model. The vendor reports 188,000+ active users, 101,639 plugin downloads and 685 GitHub stars as of October 2026. Spec-driven development is what separates it from a chat sidebar. Type "Create a task for..." and DevoxxGenie writes a structured spec with acceptance criteria, powered by Backlog.md and 17 built-in backlog tools. A Backlog Browser groups tasks by To Do, In Progress and Done; pick one and "Implement with Agent" injects the whole spec as structured context, with criteria checked off live as the agent works. Agent Mode covers the autonomous part: read_file, write_file, edit_file, list_files, search_files and run_command, with safety approvals gating writes. Parallel sub-agents run up to 10 read-only investigators at once, each on its own model and provider, so a cheap model digs while a stronger coordinator assembles the answer. It can run entirely on local models such as GLM-4.7-flash via Ollama, and an Exo-based Local AI Cluster pools multiple Apple Silicon machines to run models too large for one device. Security scanning folds Gitleaks, OpenGrep and Trivy in as agent tools, and findings land as prioritised backlog tasks. Expect an in-IDE MCP marketplace plus a debugging panel, CLI runners that route prompts through Claude Code, GitHub Copilot, OpenAI Codex, Gemini CLI and Kimi, personas for per-mode system prompts, inline FIM completion, a diff/merge review view and drag-and-drop images. Against GitHub Copilot or JetBrains AI Assistant, DevoxxGenie trades one-click setup for provider freedom and explicit control over what the agent touches.
Behind the Verdict
We'd reach for DevoxxGenie when the editor is JetBrains and the budget line for AI tooling is zero. It is the rare assistant where the open-source licence is not a stripped teaser — the full feature set ships in the free plugin, and the only cost is whatever your providers charge. The spec-driven workflow is the part worth learning. Turning "Create a task for..." into a structured spec with acceptance criteria, then handing that spec to the agent, gives you a paper trail Copilot's chat does not produce. On a multi-day refactor that traceability matters more than raw model quality, because you can see which criteria passed and which the agent quietly skipped. Parallel sub-agents are the other differentiator. Assigning a cheap model to each read-only investigator and a stronger one to the coordinator is exactly the cost trick power users want, and it is not something the managed assistants expose. Smaller shops may never touch this; teams running big codebases will. Where it bites: setup. You bring keys, you install local runtimes if you want privacy, and MCP servers need configuring before the marketplace's filesystem and database tools do anything useful. Budget an afternoon, not five minutes. The plugin also assumes you are comfortable reasoning about which model does what — per-agent overrides are a feature, but they are also a decision you now own. The closest alternative is JetBrains AI Assistant, which wins on zero setup and loses on provider choice and price. GitHub Copilot is fine if your team lives in VS Code and IntelliJ. If you are a JetBrains-only shop that already pays for an LLM API, DevoxxGenie is the cheaper path with more control — provided you accept that you are the integrator.
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Real-world workflow fit
Concrete scenarios for the personas DevoxxGenieIDEAPlugin actually fits — and what changes day-one when you adopt it.
Installs DevoxxGenie from the JetBrains Marketplace, points it at Ollama with a Fill-in-the-Middle model for inline completion and GLM-4.7-flash for Agent Mode, then types "Create a task for..." to draft a spec with acceptance criteria.
Outcome: Gets code completion and agentic editing inside IntelliJ IDEA with no API keys and no per-token cloud spend.
Writes tasks into the Backlog Browser, groups them by To Do, In Progress and Done, then clicks "Implement with Agent" so the full spec is injected as structured context. Sub-agent slots are pinned to cheaper models for codebase reconnaissance.
Outcome: Acceptance criteria get ticked off as the agent works, leaving a traceable record of what was requested versus delivered.
Runs the built-in Gitleaks, OpenGrep and Trivy agent tools against the repository and lets findings flow into the backlog rather than a standalone report.
Outcome: Secrets, SAST issues and vulnerable dependencies appear as prioritised tasks alongside the rest of the work.
Use Cases
- Review and refactor code using local or cloud AI models directly in IntelliJ IDEA.
- Turn "Create a task for..." prompts into structured specs with acceptance criteria, then implement them with the agent.
- Explore large codebases autonomously using Agent Mode with up to 10 parallel read-only sub-agents.
- Run Gitleaks, OpenGrep and Trivy scans as agent tools so findings become prioritised backlog tasks.
- Get inline code completions while typing using Fill-in-the-Middle models via Ollama or LM Studio.
- Drive Claude Code, GitHub Copilot, OpenAI Codex, Gemini CLI or Kimi prompts from the DevoxxGenie chat window.
- Browse, install and debug MCP servers from inside IntelliJ IDEA without leaving the IDE.
- Drop images into the chat for visual context when working with multimodal LLMs.
Models Under the Hood
as of 2026-10-16
Limitations
- DevoxxGenie is a free, 100% open-source plugin for JetBrains IDEs (IntelliJ IDEA, PyCharm, WebStorm and more), following a BYOK (Bring Your Own Keys) model for LLM API keys.
- It supports both local LLMs (Ollama, LM Studio, Nativ, GPT4All) and cloud providers (OpenAI, Anthropic, Mistral, Groq, Kimi, GLM, Gemini).
- As of October 2026 the vendor reports 186,000+ active users, 101,454 plugin downloads and 685 GitHub stars, distributed via the JetBrains Marketplace.
- The plugin does not provide its own hosted model inference, so you must supply and manage API keys, which may incur costs from your LLM provider.
as of 2026-10-02
Verification history
We have re-verified DevoxxGenieIDEAPlugin 9 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 9 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published DevoxxGenieIDEAPlugin tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free (Open Source)
$0
Ideal for
JetBrains IDE users — solo developers, small teams and security-conscious shops — who are willing to supply their own model keys or run a local LLM server.
What this tier adds
Starting tier: the whole plugin at $0, including spec-driven development, Agent Mode, 10 parallel sub-agents, MCP support and CLI runners.
Where the pricing makes sense
The company stage and team size where DevoxxGenieIDEAPlugin's pricing actually pencils out — and where peers do it cheaper.
DevoxxGenie carries no licence fee at all — it is 100% open source and free, distributed via the JetBrains Marketplace. Your real spend is model usage on whichever provider you connect: a local Ollama or LM Studio setup costs nothing beyond hardware, while cloud models bill per token on your own account. Against paid subscriptions like GitHub Copilot or JetBrains AI Assistant, that makes DevoxxGenie cheapest for anyone already paying for model API access, and potentially more expensive for
Setup time & first value
How long it actually takes to get something useful out of DevoxxGenieIDEAPlugin — broken out by persona, not the marketing-page minute.
Local-model users: roughly 15-30 minutes to install the plugin and point it at a running Ollama or LM Studio instance. Cloud BYOK users: budget about an hour to add API keys and pick providers. Teams wiring up MCP servers, personas, sub-agent model overrides and CLI runners should set aside an afternoon before the workflow feels native.
Switching to or from DevoxxGenieIDEAPlugin
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From GitHub Copilot: install DevoxxGenie from the JetBrains Marketplace, add your own provider key, and optionally keep Copilot reachable through the GitHub Copilot CLI runner.
- →From JetBrains AI Assistant: add DevoxxGenie alongside it, then move prompting and agent work into DevoxxGenie's chat and Backlog Browser.
- →From raw Ollama or LM Studio usage: point DevoxxGenie at the same local endpoint to gain inline completion, Agent Mode tools and backlog task management on top.
- →From Claude Code or Codex CLI: keep the CLI and drive it from DevoxxGenie's CLI runners so prompts and spec tasks execute from the IDE.
- ↗To GitHub Copilot: if you want a managed subscription with no key handling, Copilot pairs with JetBrains IDEs directly.
- ↗To JetBrains AI Assistant: a first-party option for teams that prefer JetBrains-run model hosting and no BYOK setup.
- ↗To a VS Code-based assistant: if your team standardises on VS Code, DevoxxGenie's JetBrains-only plugin cannot follow you.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “DevoxxGenieIDEAPlugin”, and we withheld 6: 6 could not be judged, because “DevoxxGenieIDEAPlugin” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about DevoxxGenieIDEAPlugin.
Official links
Tools that pair well with DevoxxGenieIDEAPlugin
Common stack mates teams adopt alongside DevoxxGenieIDEAPlugin, with the specific reason each pairing earns its keep.
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Featured Head-to-Head Comparisons
Devoxxgenieideaplugin vs Bito
Choose DevoxxGenie if you're an IntelliJ user wanting a free, open-source AI assistant with local LLM support and spec-driven development. Opt for Bito if your team uses AI coding agents (Cursor, Claude Code, Codex) across multiple repos and needs system-wide context, impact analysis, and enterprise features like SOC 2 and on-prem deployment. Bito offers deeper architectural awareness but at a cost and limited agent integration; DevoxxGenie is free but IDE-locked and less suited for cross-repo orchestration.
Devoxxgenieideaplugin vs Poolside Ai
If you're an enterprise in a regulated industry needing custom, secure AI agents with full auditability, Poolside is the right choice despite its high cost. If you're an individual developer or small team using IntelliJ IDEA and want a free, flexible AI assistant with local and cloud options, DevoxxGenie is a no-brainer. For most developers, DevoxxGenie's zero-cost and broad provider support make it the practical pick.
Devoxxgenieideaplugin vs Cognition Ai
If you're an enterprise engineering team aiming for autonomous, end-to-end software engineering with measurable productivity guarantees and cross-platform native builds, Cognition AI's Devin is the clear choice—backed by a $10M guarantee and Fortune 500 deployments. For IntelliJ IDEA users on a budget who need a flexible, privacy-respecting assistant with extensive LLM provider options (including free NVIDIA models), DevoxxGenie is an exceptional, constantly improving open-source plugin.
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