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Coding Standards

corbat-tech/coding-standards-mcp
4STDIOregistry active
Summary

This is a linter-as-context for AI code generation. It injects coding standards into your LLM's prompts before it writes code, enforcing patterns like DDD layers, SOLID principles, dependency injection, custom exceptions, and max line counts per method. Works via stdio with Cursor, VS Code, Claude Desktop, and other MCP clients. The value prop is reducing the AI slop that technically runs but fails code review. Instead of fixing generated code after the fact, you get repository interfaces, proper error types, and test scaffolding from the first output. Configure once in your MCP settings, optionally override rules in `.corbat.json`, and it auto-detects your stack to apply relevant guardrails.

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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.

npm version CI Coverage License: MIT MCP


Cursor VS Code Windsurf JetBrains Zed Claude

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.


The Problem

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

Without CorbatWith Corbat
Methods with 50+ linesMax 20 lines per method
No dependency injectionProper DI with interfaces
throw new Error('failed')Custom exceptions with context
Missing or minimal testsTests included, TDD approach
God classes, mixed concernsSOLID principles, clean layers
Works locallyReviewable implementation with explicit checks

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


Quick Start

1. Add to your MCP config:

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

2. Config file location:

ToolLocation
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Windsurf~/.codeium/windsurf/mcp_config.json
JetBrainsSettings → AI Assistant → MCP
Claude Desktop~/.config/Claude/claude_desktop_config.json
Claude Codeclaude 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 →


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.


What Corbat Provides

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

Code Quality

RuleWhy It Matters
Max 20 lines per methodReadable, testable, single-purpose functions
Max 200 lines per classSingle Responsibility Principle
Meaningful namesNo data, info, temp, x
No magic numbersConstants with descriptive names

Architecture

RuleWhy It Matters
Interfaces for dependenciesTestable code, easy mocking
Layer separationDomain logic isolated from infrastructure
Hexagonal/Clean patternsFramework-agnostic business rules

Error Handling

RuleWhy It Matters
Custom exceptionsUserNotFoundError vs Error('not found')
Error contextInclude IDs, values, state in errors
No empty catchesEvery error handled or propagated

Security-Oriented Checks

RuleWhy It Matters
Input validationReject bad data at boundaries
No hardcoded secretsEnvironment variables only
Parameterized queriesPrevent SQL injection
Output encodingPrevent XSS

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:

ScenarioWith CorbatWithout CorbatWhat This Means
Kotlin Coroutines236 lines1,923 linesSame functionality, 8x less to maintain
Java Hexagonal623 lines2,740 linesClean architecture without the bloat
Go Clean Arch459 lines2,012 linesIdiomatic Go, not Java-in-Go
TypeScript NestJS395 lines1,554 linesRight 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:

MetricResultWhat It Means
Code Reduction67%Less to maintain, review, and debug
Security checks100%No issues detected by benchmark pattern checks
Maintainability93% winEasier to understand and modify
Architecture Efficiency87% winBetter 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

LanguageScenariosPatterns
☕ Java5Spring Boot, DDD Aggregates, Hexagonal, Kafka Events, Saga
📘 TypeScript4Express REST, NestJS Clean, React Components, Next.js Full-Stack
🐍 Python2FastAPI CRUD, Repository Pattern
🐹 Go2HTTP Handlers, Clean Architecture
🦀 Rust1Axum with Repository Trait
🟣 Kotlin1Coroutines + Strategy Pattern

📖 Full benchmark methodology · Value analysis


Built-in Profiles

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

ProfileStackWhat You Get
java-spring-backendJava 21 + Spring Boot 3Hexagonal + DDD, TDD with 80%+ coverage
kotlin-springKotlin + Spring Boot 3Coroutines, Kotest + MockK
nodejsNode.js + TypeScriptClean Architecture, Vitest
nextjsNext.js 14+App Router patterns, Server Components
reactReact 18+Hooks, Testing Library, accessible components
vueVue 3.5+Composition API, Vitest
angularAngular 19+Standalone components, Jest
pythonPython + FastAPIAsync patterns, pytest
goGo 1.22+Idiomatic Go, table-driven tests
rustRust + AxumOwnership patterns, proptest
csharp-dotnetC# 12 + ASP.NET Core 8Clean + CQRS, xUnit
flutterDart 3 + FlutterBLoC/Riverpod, widget tests

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


When to Use Corbat

Use CaseWhy Corbat Helps
Starting a new projectCorrect architecture from day one
Multi-agent deliveryPlanner, implementation, review, and security agents share the same policy context
Teams with mixed experienceStandards become explicit and repeatable
Strict code review standardsAgents can validate against the review bar before handoff
Regulated industriesConsistent security and documentation
Legacy modernizationNew 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

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.


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.


Documentation

ResourceDescription
Setup GuideInstallation notes for common MCP-compatible tools
TemplatesReady-to-use .corbat.json configurations
CompatibilityFull list of supported AI tools
Benchmark AnalysisDetailed results from 15 scenarios
Multi-Agent ArchitectureHow Corbat fits planner/reviewer/security/release agent workflows
Security ModelLocal execution model, threat model, and reporting
API ReferenceTools, prompts, and configuration options

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.


Developed by corbat-tech

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Package@corbat-tech/coding-standards-mcp
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UpdatedJan 21, 2026
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