AI code, verified.

Vibe, then verify.

Vibe coding accelerates development with generative AI, but it’s not enough. AI-produced code can contain bugs and vulnerabilities, which is why tools like SonarQube are critical for review and validation.

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TRUSTED BY OVER 7M DEVELOPERS WORLDWIDE

AI-generated code introduces hidden challenges

Code quality and security challenges are being accelerated by AI-assisted development. AI-generated code can introduce bugs, vulnerabilities, and risky dependencies that slip past quick reviews. Automated reviews enforce your standards and keep issues from reaching production.

Unvetted quality

AI-generated code often prioritizes syntax over efficiency, increasing technical debt. SonarQube reviews code automatically and detects code smells and duplication so your codebase stays reliable.

False security

AI-written code is not inherently secure. Flaws expose applications to attacks. SonarQube detects vulnerabilities like SQL injection, deserialization, and XSS so code meets your security standards.

Dependency risks

AI-generated code often pulls in external libraries that can introduce vulnerabilities and supply-chain risk. SonarQube Advanced Security identifies and flags risky dependencies so you can mitigate the attack surface.

Code accountability

As AI tools write more code, teams often accept it without proper vetting. When defects reach production, ownership gets murky. Catching issues early keeps every change accountable to your quality and security standards.

Purpose-built for Agent Centric Development

Five solutions that plug into your team's AI coding workflow — from the first prompt, through code generation, to pull-request review, cleanup, and IDE fixes.

Agentic Analysis

Context Augmentation

Remediation Agent

MCP Server

AI CodeFix

Verify AI code before you commit

Agentic Analysis verifies code written by AI agents against your team's quality and security standards while the AI is still writing. Issues get fixed in seconds — not hours later in code review.

Capabilities

Real-time, pre-PR verification: Issues are caught and fixed during code generation — not hours later when a developer has to stop what they're doing to clean up.
Full project context, not just one file: Uses cached data from your previous CI builds to understand how your entire codebase connects. Catches cross-file bugs that single-file checkers miss.
Your standards, automatically applied: No new rules to define. Agentic Analysis uses the quality profiles your team already enforces in SonarQube — across every AI tool on the team.
One standard across every AI tool: One verification standard for every AI coding tool your team uses. Consistent code quality no matter which assistant a developer picks.

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The context your AI needs

Context Augmentation is a dynamic context engine that gives AI coding agents your organization's architecture, security, and quality standards — from the first prompt, before any code is written.

Capabilities

Pre-generation guidance: Catches architectural errors during the agent's planning phase. If the AI plans a change that violates an intended boundary, it course-corrects before writing any code.
Repo-aware structural context: Uses SonarQube's analysis of class hierarchies, call flows, and execution paths to give the agent a factual map of your codebase.
One trusted standard: Applies the same CI/CD rule engines, quality profiles, and architecture constraints from SonarQube that you already trust — directly into the agent's inner loop.
Zero developer friction: Fits into agentic workflows via Model Context Protocol (MCP). No new tools, no prompt engineering — just better results.

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Issues fixed, not just found

Remediation Agent fixes issues in your pull requests and existing backlog, then re-scans each fix using Sonar's analysis engine. Only verified fixes become PRs. You review and merge — nothing enters your codebase unverified.

Capabilities

Accelerate cycle time: Slash the "waiting for review" tax. Turn red quality gates green in minutes, not hours, by letting the agent fix routine issues asynchronously.
Verified, not hallucinated: Every patch is verified against the Sonar analysis engine before it becomes a PR — only fixes that compile and pass your quality gates ever reach a reviewer.
Elevate code health: Tackle code smells and maintenance issues that tend to get deprioritized in human reviews — without waiting for a dedicated sprint.
Seamless integration: Integrated directly with GitHub Pull Requests and SonarQube Cloud Enterprise. No IDE plugins required.

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Sonar's intelligence, inside every AI agent

SonarQube MCP Server exposes Sonar's analysis findings, rules, and quality profiles to AI coding agents like Claude Code, Cursor, and Copilot through the Model Context Protocol.

Capabilities

Open, standards-based: Built on the Model Context Protocol (MCP). Any MCP-compatible agent or IDE can connect — Claude Code, Cursor, Copilot, Gemini, and beyond. No proprietary integration required.
Live access to findings: Agents can read real-time SonarQube issues for a repo, query specific rules, pull quality profile definitions, and see recent analysis results — grounded in your project's actual state, not guesses.
Grounded in your standards: Agents see the exact same rules and thresholds your CI enforces. The fixes and code they suggest are aligned with your quality profiles from the start — no post-hoc cleanup.
Zero developer friction: Install once. Agents pick up the capability automatically. Developers keep working with the AI tool of their choice — and the tool gets smarter about your code.

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One-click verified fixes, in the IDE

AI CodeFix turns SonarQube findings into suggested fixes developers can apply in a single click — directly in the IDE or the pull request. Every fix is grounded in the Sonar rule that triggered the finding, so the suggestion reflects your quality standards, not a generic AI guess.

Capabilities

Fix in one click: For every flagged issue, AI CodeFix generates a suggested fix inline. Developers review, accept, or reject — no context switch, no separate branch, no hand-written patches.
Grounded in Sonar rules: Each suggestion is tied to the specific rule that triggered the finding. AI CodeFix doesn't invent a fix — it generates one that resolves the rule violation without introducing new ones.
On-premise for sensitive code: Fully on-premise in SonarQube Server 2026.2. Sensitive code never leaves your infrastructure — AI CodeFix runs where your SonarQube instance runs, meeting strict data residency requirements.
Wherever developers work: Available in SonarQube for IDE, in the SonarQube UI, and in pull-request workflows. Developers see fixes in the same place they see the issue — never a new tool.

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Prevent security and compliance vulnerabilities

Proactive checks in the IDE and CI/CD pipelines catch issues early when fixes are fastest and least costly. Quality gates block risky merges and deployments until code meets your standards, leading directly into automated review of AI-generated code and enforceable policies.

Review AI-generated code

Guardrails for AI code
Automatic review of every line of code — AI-generated or human-written — to find bugs, vulnerabilities, and quality issues.
Customizable standards
Define and enforce your own quality and security rules and thresholds with SonarQube's quality gates.
Compliance for AI code
Finds issues in all code — including AI-generated — that don't meet compliance standards such as PCI, OWASP, CWE, STIG, and CASA.
Comprehensive languages
Supports 40+ programming languages so your quality and security standards stay consistent across every project.

code has issues in development lifecycle

Secure, high-quality AI-generated code you can trust

Sonar's Remediation Agent detects and fixes issues in AI-generated code automatically, then verifies every fix against the Sonar analysis engine before opening a pull request. Every change that reaches your codebase has passed your quality and security standards — whether a human or an AI wrote it.

See Remediation Agent

What you get with Sonar's AI products

Outcomes teams care about: code you can trust, a process you can repeat, and results you can explain. Sonar delivers consistent, repeatable, explainable, accurate, auditable, and efficient outcomes — with deterministic analysis, zero-trust verification, and multi-layered checks as the engine behind them.

Consistent & Efficient

Every AI-generated change is reviewed against the same standards. Routine issues are caught automatically, so engineers focus on architecture and intent — not cleanup.

Accurate & Repeatable

Early validation improves reliability and reduces debug cycles. The same rules apply to every commit, every branch, every team.

Auditable

Every finding has a clear reason, a rule, and a suggested fix. Governance teams get auditable evidence that AI-generated code meets your standards.

Explainable

Contextual guidance makes every fix understandable to developers, reviewers, and auditors alike. Sonar solves verification debt — the gap between how fast AI writes code and how fast teams can trust it.

Code quality and security in your CI/CD workflow

SonarQube is purpose-built for DevOps, embedding automated code analysis directly into your pipeline and supporting the programming languages your teams already use.

"Sonar helps our development team confidently make both AI-assisted and human-developed code fit for production by reviewing and establishing rules of good programming practices to achieve better code."

Dario Flores, Technical Quality Specialist

Verify every line of AI code — before it ships.

Integrate SonarQube into your workflow and stop verification debt at the source.

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