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CORBAT MCP

Policy and quality engine for AI coding agents

Shared standards, context, and verification gates for agent-assisted software delivery.

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Designed for MCP-compatible coding tools and multi-agent workflows. See compatibility notes.

⚡ Try it in 30 seconds — just add the config below and start coding.

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The Problem

AI-generated code often works locally but misses team-specific review expectations:

Without Corbat	With Corbat
Methods with 50+ lines	Max 20 lines per method
No dependency injection	Proper DI with interfaces
throw new Error('failed')	Custom exceptions with context
Missing or minimal tests	Tests included, TDD approach
God classes, mixed concerns	SOLID principles, clean layers
Works locally	Reviewable implementation with explicit checks

Corbat helps by giving agents your team's standards before implementation and by providing validation tools before review or handoff.

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Quick Start

1. Add to your MCP config:

{
  "mcpServers": {
    "corbat": {
      "command": "npx",
      "args": ["-y", "@corbat-tech/coding-standards-mcp"]
    }
  }
}

2. Config file location:

Tool	Location
Cursor	.cursor/mcp.json
VS Code	.vscode/mcp.json
Windsurf	~/.codeium/windsurf/mcp_config.json
JetBrains	Settings → AI Assistant → MCP
Claude Desktop	~/.config/Claude/claude_desktop_config.json
Claude Code	claude mcp add corbat -- npx -y @corbat-tech/coding-standards-mcp

Complete setup guide for common MCP-compatible tools

3. Done. Corbat can auto-detect your stack and return matching standards.

Zero overhead. Corbat runs locally and adds ~50ms to detect your stack. After that, it's just context for the AI.

Fully customizable. Don't like a rule? Override it in .corbat.json. Jump to customization →

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See It In Action

You: "Create a user registration service"

Without Corbat, you get:

class UserService {
  private users: Map<string, User> = new Map();

  register(name: string, email: string, password: string) {
    if (!name || !email || !password) throw new Error('Invalid input');
    const user = { id: crypto.randomUUID(), name, email, password };
    this.users.set(user.id, user);
    return user;
  }
}
// ✗ Hardcoded storage  ✗ Password in plain text  ✗ Generic error  ✗ No tests

With Corbat, you get:

// Domain
interface UserRepository {
  save(user: User): Promise<void>;
  findByEmail(email: string): Promise<User | null>;
}

class EmailAlreadyExistsError extends Error {
  constructor(email: string) {
    super(`Email already registered: ${email}`);
  }
}

// Application
class RegisterUserUseCase {
  constructor(
    private readonly repository: UserRepository,
    private readonly hasher: PasswordHasher
  ) {}

  async execute(input: RegisterUserInput): Promise<User> {
    const existing = await this.repository.findByEmail(input.email);
    if (existing) throw new EmailAlreadyExistsError(input.email);

    const user = User.create({
      ...input,
      password: await this.hasher.hash(input.password)
    });
    await this.repository.save(user);
    return user;
  }
}
// ✓ Repository interface  ✓ Password hashing  ✓ Custom error  ✓ Testable

// Test included
describe('RegisterUserUseCase', () => {
  const repository = { save: vi.fn(), findByEmail: vi.fn() };
  const hasher = { hash: vi.fn() };
  const useCase = new RegisterUserUseCase(repository, hasher);

  beforeEach(() => vi.clearAllMocks());

  it('should hash password before saving', async () => {
    repository.findByEmail.mockResolvedValue(null);
    hasher.hash.mockResolvedValue('hashed_password');

    await useCase.execute({ name: 'John', email: 'john@test.com', password: 'secret' });

    expect(hasher.hash).toHaveBeenCalledWith('secret');
    expect(repository.save).toHaveBeenCalledWith(
      expect.objectContaining({ password: 'hashed_password' })
    );
  });

  it('should reject duplicate emails', async () => {
    repository.findByEmail.mockResolvedValue({ id: '1', email: 'john@test.com' });

    await expect(
      useCase.execute({ name: 'John', email: 'john@test.com', password: 'secret' })
    ).rejects.toThrow(EmailAlreadyExistsError);
  });
});

This is the kind of structure Corbat asks agents to consider before handoff.

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What Corbat Provides

Corbat provides these guardrails before generation and validation checks during iteration:

Code Quality

Rule	Why It Matters
Max 20 lines per method	Readable, testable, single-purpose functions
Max 200 lines per class	Single Responsibility Principle
Meaningful names	No data, info, temp, x
No magic numbers	Constants with descriptive names

Architecture

Rule	Why It Matters
Interfaces for dependencies	Testable code, easy mocking
Layer separation	Domain logic isolated from infrastructure
Hexagonal/Clean patterns	Framework-agnostic business rules

Error Handling

Rule	Why It Matters
Custom exceptions	UserNotFoundError vs Error('not found')
Error context	Include IDs, values, state in errors
No empty catches	Every error handled or propagated

Security-Oriented Checks

Rule	Why It Matters
Input validation	Reject bad data at boundaries
No hardcoded secrets	Environment variables only
Parameterized queries	Prevent SQL injection
Output encoding	Prevent XSS

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Benchmark Results v3.0

We evaluated Corbat across 15 scenarios in 6 languages. The primary benchmark report is mixed and should be read honestly: Corbat won 1/15 scenarios by the original aggregate score, while an alternative value analysis found stronger results for code compactness and maintainability.

What The Data Supports

The strongest observed signal is that Corbat-guided outputs are often smaller and more focused:

Scenario	With Corbat	Without Corbat	What This Means
Kotlin Coroutines	236 lines	1,923 lines	Same functionality, 8x less to maintain
Java Hexagonal	623 lines	2,740 lines	Clean architecture without the bloat
Go Clean Arch	459 lines	2,012 lines	Idiomatic Go, not Java-in-Go
TypeScript NestJS	395 lines	1,554 lines	Right patterns, right size

This is not enough to claim universal quality improvement. It is evidence that standards context can reduce over-generation in some workflows.

Value Metrics

The value report reweights the same dataset toward efficiency and maintainability:

Metric	Result	What It Means
Code Reduction	67%	Less to maintain, review, and debug
Security checks	100%	No issues detected by benchmark pattern checks
Maintainability	93% win	Easier to understand and modify
Architecture Efficiency	87% win	Better patterns per line of code
Cognitive Load	-59%	Faster onboarding for new developers

📊 Detailed value analysis

Security: No Benchmark Pattern Findings

Every scenario was analyzed using pattern checks inspired by OWASP Top 10 categories. This is not a replacement for SAST, DAST, dependency scanning, manual review, or threat modeling.

• No SQL/NoSQL injection patterns detected
• No XSS patterns detected
• No hardcoded credentials detected
• Input validation patterns present at boundaries
• Error messages did not expose stack traces in the benchmark samples

Languages & Patterns Tested

Language	Scenarios	Patterns
☕ Java	5	Spring Boot, DDD Aggregates, Hexagonal, Kafka Events, Saga
📘 TypeScript	4	Express REST, NestJS Clean, React Components, Next.js Full-Stack
🐍 Python	2	FastAPI CRUD, Repository Pattern
🐹 Go	2	HTTP Handlers, Clean Architecture
🦀 Rust	1	Axum with Repository Trait
🟣 Kotlin	1	Coroutines + Strategy Pattern

📖 Full benchmark methodology · Value analysis

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Built-in Profiles

Corbat auto-detects your stack and applies the right standards:

Profile	Stack	What You Get
java-spring-backend	Java 21 + Spring Boot 3	Hexagonal + DDD, TDD with 80%+ coverage
kotlin-spring	Kotlin + Spring Boot 3	Coroutines, Kotest + MockK
nodejs	Node.js + TypeScript	Clean Architecture, Vitest
nextjs	Next.js 14+	App Router patterns, Server Components
react	React 18+	Hooks, Testing Library, accessible components
vue	Vue 3.5+	Composition API, Vitest
angular	Angular 19+	Standalone components, Jest
python	Python + FastAPI	Async patterns, pytest
go	Go 1.22+	Idiomatic Go, table-driven tests
rust	Rust + Axum	Ownership patterns, proptest
csharp-dotnet	C# 12 + ASP.NET Core 8	Clean + CQRS, xUnit
flutter	Dart 3 + Flutter	BLoC/Riverpod, widget tests

Auto-detection: Corbat reads pom.xml, package.json, go.mod, Cargo.toml, etc.

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When to Use Corbat

Use Case	Why Corbat Helps
Starting a new project	Correct architecture from day one
Multi-agent delivery	Planner, implementation, review, and security agents share the same policy context
Teams with mixed experience	Standards become explicit and repeatable
Strict code review standards	Agents can validate against the review bar before handoff
Regulated industries	Consistent security and documentation
Legacy modernization	New code follows modern patterns

When Corbat Might Not Be Needed

• Quick prototypes where quality doesn't matter
• One-off scripts you'll throw away
• Learning projects where you want to make mistakes

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Customize

Option 1: Interactive Setup

npx corbat-init

Detects your stack and generates a .corbat.json with sensible defaults.

Option 2: Manual Configuration

Create .corbat.json in your project root:

{
  "profile": "java-spring-backend",
  "architecture": {
    "pattern": "hexagonal",
    "layers": ["domain", "application", "infrastructure", "api"]
  },
  "quality": {
    "maxMethodLines": 20,
    "maxClassLines": 200,
    "minCoverage": 80
  },
  "rules": {
    "always": [
      "Use records for DTOs",
      "Prefer Optional over null"
    ],
    "never": [
      "Use field injection",
      "Catch generic Exception"
    ]
  }
}

Option 3: Use a Template

Browse 14 ready-to-use templates for Java, Python, Node.js, React, Go, Rust, and more.

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How It Works

┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│ Your Prompt │────▶│ Corbat MCP  │────▶│ AI + Rules  │
└─────────────┘     └──────┬──────┘     └─────────────┘
                          │
           ┌──────────────┼──────────────┐
           ▼              ▼              ▼
    ┌────────────┐ ┌────────────┐ ┌────────────┐
    │ 1. Detect  │ │ 2. Load    │ │ 3. Inject  │
    │   Stack    │ │  Profile   │ │ Guardrails │
    └────────────┘ └────────────┘ └────────────┘
     pom.xml        hexagonal      max 20 lines
     package.json   + DDD          + interfaces
     go.mod         + SOLID        + custom errors

Corbat does not modify AI output. It supplies context, standards, profiles, and validation feedback so agents can align with your review expectations.

Important: Actual code quality depends on the model, host tool, prompt, repository context, tests, and human review. Treat Corbat as a policy and verification layer, not as a guarantee of production readiness.

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Documentation

Resource	Description
Setup Guide	Installation notes for common MCP-compatible tools
Templates	Ready-to-use .corbat.json configurations
Compatibility	Full list of supported AI tools
Benchmark Analysis	Detailed results from 15 scenarios
Multi-Agent Architecture	How Corbat fits planner/reviewer/security/release agent workflows
Security Model	Local execution model, threat model, and reporting
API Reference	Tools, prompts, and configuration options

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Make agent output easier to review.

Add to your MCP config and you're done:

{ "mcpServers": { "corbat": { "command": "npx", "args": ["-y", "@corbat-tech/coding-standards-mcp"] }}}

Use Corbat as shared standards context plus a local quality gate.

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Developed by corbat-tech

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