Codacy Review 2026: Features, Pricing & Alternatives

Codacy is a unified code quality and security platform that automatically analyzes code for security vulnerabilities, code smells, complexity issues, and style violations.

Founded in 2012, Codacy supports over 40 programming languages and integrates directly into developer workflows through IDE plugins and pull request checks.

The Codacy Analysis CLI is open source (AGPL-3.0) with 113+ stars on GitHub. Codacy maintains 156+ repositories on GitHub, including language-specific integrations for ESLint, Pylint, Trivy, and more.

What is Codacy?

Codacy provides automated code review that catches security issues and quality problems before they reach production.

The platform combines multiple analysis engines to deliver comprehensive coverage, from security vulnerabilities and hardcoded secrets to code duplication and maintainability concerns.

What sets Codacy apart is its AI code guardrails feature, specifically designed to protect against vulnerabilities introduced by AI-generated code.

As developers increasingly use tools like GitHub Copilot and ChatGPT for code generation, Codacy ensures that AI-assisted code meets the same security and quality standards as human-written code.

The platform emphasizes developer experience with real-time feedback in IDEs, actionable findings with remediation guidance, and auto-fix capabilities that resolve common issues automatically.

Key Features

Security Analysis (SAST)

Detect security vulnerabilities across your codebase:

OWASP Top 10 vulnerability detection
CWE coverage for comprehensive security scanning
SQL injection, XSS, and command injection detection
Authentication and authorization flaws
Cryptographic weaknesses
Path traversal and file inclusion vulnerabilities
Severity-based prioritization

AI Code Guardrails

Protect against AI-generated code risks:

Specialized detection rules for AI code patterns
Identification of common AI-generated vulnerabilities
Quality checks for Copilot and ChatGPT code
Automated scanning of AI-assisted pull requests
Risk scoring for AI-generated code blocks

Secrets Detection

Find hardcoded credentials before they leak:

API keys and tokens
Database credentials
Private keys and certificates
Cloud provider credentials
Custom secret patterns
Historical scanning of repository history

Code Quality Analysis

Maintain healthy, maintainable codebases:

Code complexity metrics (cyclomatic, cognitive)
Duplication detection
Style and formatting violations
Documentation coverage
Dead code identification
Technical debt tracking

Software Composition Analysis

Identify open-source risks:

Dependency vulnerability scanning
License compliance checking
Outdated package detection
Transitive dependency analysis
SBOM generation

Installation

GitHub Integration

Connect Codacy directly to your GitHub repositories:

Sign up at codacy.com using your GitHub account
Select repositories to analyze
Codacy automatically scans on each push

IDE Extensions

Install Codacy in your development environment:

# VS Code
code --install-extension codacy.codacy

# JetBrains IDEs (IntelliJ, PyCharm, WebStorm)
# Install via IDE Settings > Plugins > Marketplace > Search "Codacy"

CLI Tool

Run Codacy analysis locally or in CI:

# Install Codacy CLI
curl -L https://github.com/codacy/codacy-analysis-cli/releases/latest/download/codacy-analysis-cli.sh \
  -o codacy-analysis-cli.sh
chmod +x codacy-analysis-cli.sh

# Run local analysis
./codacy-analysis-cli.sh analyze \
  --directory /path/to/project \
  --tool eslint \
  --tool security

# With project token for upload
./codacy-analysis-cli.sh analyze \
  --project-token $CODACY_PROJECT_TOKEN \
  --upload

Configuration File

Create a .codacy.yml in your repository root:

---
engines:
  eslint:
    enabled: true
    config: .eslintrc.json
  pylint:
    enabled: true
    config: pylintrc
  semgrep:
    enabled: true
  secrets:
    enabled: true

exclude_paths:
  - "node_modules/**"
  - "vendor/**"
  - "**/*.min.js"
  - "tests/**"

languages:
  javascript:
    extensions:
      - ".js"
      - ".jsx"
      - ".ts"
      - ".tsx"

Integration

GitHub Actions

name: Codacy Analysis

on:
  push:
    branches: [main]
  pull_request:
    branches: [main]

jobs:
  codacy-analysis:
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
        with:
          fetch-depth: 0  # Full history for accurate analysis

      - name: Run Codacy Analysis CLI
        uses: codacy/codacy-analysis-cli-action@master
        with:
          project-token: ${{ secrets.CODACY_PROJECT_TOKEN }}
          upload: true
          max-allowed-issues: 0

      - name: Run Codacy Coverage Reporter
        uses: codacy/codacy-coverage-reporter-action@v1
        with:
          project-token: ${{ secrets.CODACY_PROJECT_TOKEN }}
          coverage-reports: coverage/lcov.info

GitLab CI

stages:
  - quality

codacy:
  stage: quality
  image: codacy/codacy-analysis-cli:latest
  variables:
    CODACY_PROJECT_TOKEN: $CODACY_PROJECT_TOKEN
  script:
    - codacy-analysis-cli analyze
        --project-token $CODACY_PROJECT_TOKEN
        --upload
        --verbose
  rules:
    - if: $CI_PIPELINE_SOURCE == "merge_request_event"
    - if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH

codacy-coverage:
  stage: quality
  image: codacy/codacy-coverage-reporter:latest
  script:
    - codacy-coverage-reporter report
        --project-token $CODACY_PROJECT_TOKEN
        --coverage-reports coverage/lcov.info
  rules:
    - if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCH
  needs:
    - test  # Depends on your test job that generates coverage

Jenkins Pipeline

pipeline {
    agent any

    environment {
        CODACY_PROJECT_TOKEN = credentials('codacy-project-token')
    }

    stages {
        stage('Codacy Analysis') {
            steps {
                sh '''
                    curl -L https://github.com/codacy/codacy-analysis-cli/releases/latest/download/codacy-analysis-cli.sh \
                      -o codacy-analysis-cli.sh
                    chmod +x codacy-analysis-cli.sh
                    ./codacy-analysis-cli.sh analyze \
                      --project-token $CODACY_PROJECT_TOKEN \
                      --upload \
                      --fail-if-incomplete
                '''
            }
        }

        stage('Coverage Report') {
            steps {
                sh '''
                    bash <(curl -Ls https://coverage.codacy.com/get.sh) report \
                      --project-token $CODACY_PROJECT_TOKEN \
                      --coverage-reports coverage/lcov.info
                '''
            }
        }
    }
}

Pull Request Integration

Codacy comments directly on pull requests with:

Security vulnerability findings
Code quality issues
Coverage impact
Overall quality gate status
Links to detailed explanations

Configure quality gates in Codacy settings:

# Quality gate example configuration
quality_gate:
  issues:
    max_new_issues: 0
    severity_threshold: medium
  coverage:
    min_coverage: 80
    max_coverage_drop: 5
  duplication:
    max_duplication: 3

When to Use Codacy

Codacy is particularly well-suited for teams that:

Use AI coding assistants and need guardrails for generated code
Want unified quality and security in a single platform
Need multi-language support across diverse tech stacks
Value developer experience with IDE integration and PR comments
Have open-source projects that can use the free tier
Want auto-fix capabilities to speed up remediation

Consider alternatives if you need:

Deep security analysis only without code quality (consider dedicated SAST tools)
Compliance-focused reporting for regulated industries (consider Checkmarx or Veracode)
Enterprise-scale deployment with complex policy management
Specific language depth that specialized tools might offer

Codacy works well as part of a defense-in-depth strategy, complementing dedicated security tools with its broad quality coverage and developer-friendly workflow integration.