Cleaner pull requests, first time
Routine AI mistakes are fixed before code reaches review. Reviewers spend their time on logic and architecture — not cleanup.
Verify AI code before you commit
SonarQube Agentic Analysis verifies code written by AI agents against your team's quality and security standards while the AI is still writing. Bugs get fixed in seconds — not hours later in code review.
Claude Code
Devin & Windsurf
Google Gemini CLI
Cursor
GitHub Copilot
OpenAI Codex CLI
MCP-compatible clients
Linters miss the real issues
Basic code checkers only look at one file. They miss bugs that appear when different parts of your codebase interact.
CI feedback arrives too late
By the time CI flags a problem, the developer has moved on. Switching back to fix it costs time, focus, and momentum.
Reviewers spend time on AI cleanup
Senior engineers and security teams waste review cycles catching routine AI mistakes instead of focusing on architecture and logic.
Every AI tool has its own rules
Without a shared standard, teams using multiple AI coding tools get inconsistent code quality across the same codebase.
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.
Security and code quality together
Checks for vulnerabilities, reliability issues, maintainability problems, and exposed secrets — not just security, and not just style.
Works with the tools your team already uses
Connects through the SonarQube MCP Server to Cursor, GitHub Copilot, Claude Code, Windsurf, Gemini CLI, and any MCP-compatible workflow.
Consistent across your whole AI stack
One verification standard for every AI coding tool on the team. No more inconsistent code quality when developers use different assistants.
Guide
1. Set the context
Sonar Context Augmentation gives the AI agent your project's quality rules and code context before it writes a line.
Generate
2. AI writes code
Your AI coding tool — Cursor, Copilot, Claude Code, or any MCP-compatible tool — generates code as it normally would.
Verify
3. Sonar checks it
Agentic Analysis automatically checks the code against your SonarQube quality profiles using full project context — in seconds.
Solve
4. AI fixes and re-checks
The AI uses Sonar's specific, rule-based findings to fix its own mistakes and re-verify — before the developer ever sees the code.
Proven analysis engine
Built on the same Sonar analysis foundation teams already use to improve code quality and code security.
Project-aware verification
Bring SonarQube context, baseline, and standards into the agent loop instead of relying only on local heuristics.
Earlier issue removal
Catch and correct routine AI-generated issues before they become reviewer cleanup, not after.
Get started
Your AI writes the code.
Sonar makes sure it's ready to ship.
See how Agentic Analysis fits into your team's existing AI workflow — no new tools to learn, no new standards to define.
What is SonarQube Agentic Analysis?
SonarQube Agentic Analysis is a real-time code verification service from Sonar. It connects AI coding tools — such as Cursor, GitHub Copilot, and Claude Code — to SonarQube's analysis engine through the Model Context Protocol (MCP). While the AI is writing code, it automatically checks its own output against your team's SonarQube quality and security standards, finds issues, fixes them, and re-checks — all before the developer opens a pull request.
How is it different from a linter or IDE plugin?
Linters check one file at a time and miss bugs that require understanding how different parts of a codebase interact. SonarQube Agentic Analysis uses context from your last full SonarQube CI scan to understand your entire project — catching cross-file issues that single-file tools miss. It also applies your team's full quality, security, and reliability standards automatically, not just basic syntax checks.
Does it replace our existing CI pipeline?
No. Agentic Analysis works alongside your existing CI/CD pipeline — it doesn't replace it. It adds an earlier verification step inside the AI's coding workflow, so fewer problems reach CI in the first place. Your CI pipeline remains the final authority on code quality.
Is my code sent to an AI model for analysis?
No. Agentic Analysis uses Sonar's deterministic-first code analysis engine. Your code is checked using a systematic and deep code analysis, not processed by a generative AI. The results are consistent and explainable: every finding can be traced back. This is what makes Sonar's analysis trustworthy for compliance and enterprise governance.
Do we have to teach it our coding standards?
No. Agentic Analysis automatically uses the quality profiles your team already has set up in SonarQube. There are no new standards to define or maintain. It applies the same standard to AI-generated code that you already enforce for all your code.
Who is it for, and what do I need to get started?
Agentic Analysis is built for engineering teams that already use SonarQube and are actively using AI coding tools. It is available to SonarQube Cloud customers. To get started, you need an active SonarQube Cloud paid account, at least one recent SonarQube project scan, and an MCP-compatible AI coding tool. Most teams are up and running in under an hour.