Verify Code＃
LLMs can produce non-factual or irrelevant output (hallucinations). In software development, that translates into risky code changes and extra engineering overhead:
- Difficulty programmatically trusting AI-generated code.
- Increased complexity in error handling and QA.
- Potential for cascading failures in chained AI operations.
- Manual review cycles that slow development and deployment.
Verify Code is part of kluster.ai trust layer, and its goal is to validate AI-generated code in real time so you can deploy AI at scale where accuracy and security matter most.
With Verify Code, you can ship confidently: potential issues are surfaced (and can be auto-corrected) before they reach production. The service works seamlessly with AI coding assistants in your IDE (Cursor, VS Code, Claude Code and others), analyzing diffs as code is generated.
How Verify Code works＃
Verify Code analyzes AI-generated code (typically in diff format) and returns a structured assessment with actionable fixes. It combines the following MCP tools:
kluster_code_review_auto: For code security and quality verification.kluster_dependency_validator: For dependency validation.
The service responds with the following fields:
isCodeCorrect: Indicates whether the code has issues.issues: Array of detected problems with type, severity, and priority.explanation: Summary of all issues found.agent_todo_list: Prioritized list of fixes to apply.
Key features＃
- Real-time code review: Monitors AI-generated code as it’s written.
- Comprehensive issue detection: Analyzes 7 issue types — Semantic, Intent, Logical, Security, Knowledge, Performance, and Quality.
- Customizable severity levels: Configure detection sensitivity from Low to Critical.
- Dual analysis tools: Real-time Code Review and Dependency Analysis for complete coverage.
- Automatic correction: AI incorporates feedback to fix issues immediately.
Configuration options＃
Tailor Verify Code to your workflow:
- Severity settings: Set minimum severity to report (Low → Critical).
- Bug check types: Select which issue types to check: Semantic, Security, Quality, Intent, Knowledge, Logical, Performance.
- Enabled tools: Choose which MCP tools are active (bug check tool, packages check tool).
These settings can be configured directly in your IDE integration.
Target applications and use cases＃
- AI coding assistants and IDE integrations.
- Automated code review pipelines.
- CI/CD security scanning for AI-generated code.
- Development workflow automation.
- Code quality assurance systems.
When to use Verify Code＃
- AI code validation: Verify AI-generated code before production use.
- Security scanning: Detect potential vulnerabilities early.
- Quality assurance: Enforce best practices automatically.
- Dependency checking: Validate that new packages are secure and up-to-date.
Integrations＃
Verify Code is available as a native extension for IDEs such as Cursor, VS Code and Claude Code, and through MCP-compatible IDEs such as Windsurf, Kilo Code and others.
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Guide Cursor, VS Code and Claude Code
Enable real-time analysis during development by setting up Verify Code with Cursor, VS Code and Claude Code.
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Guide Other MCP-compatible IDEs
Integrate Verify Code with other MCP-compatible IDEs, including Windsurf and Kilo Code.
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Guide Tools reference
Use Verify Code tools directly in your IDE via MCP.
Additional resources＃
- Get started: Run Verify Code in minutes.
- See real examples: Walk through a complete Firebase migration case study.