Codacy Review 2026: AI Code Review, Pricing & Limits

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Last verified: October 13, 2026. This is an editorial research review — how we review. Prices and plans change often; confirm on the vendor’s site.

Codacy is an automated code quality and security platform. It scans repositories and pull requests with a large set of static analysis tools, tracks coverage, duplication and complexity, and blocks merges that break your standards. In 2026 it repositions itself around AI-assisted development, describing itself as “Code Quality & Security for AI-Assisted Engineering.” It adds an AI Reviewer for pull requests, AI Guardrails that check AI-generated code inside the IDE, and organization-wide AI policy tools.

Codacy is for engineering teams that want consistent quality and security gates across many repositories, especially teams whose code is increasingly written by AI assistants. It is less a coding assistant than a checkpoint: it sits between your developers, or their agents, and the main branch.

This is an editorial research review based on Codacy’s website, pricing page, documentation and release notes. We did not run our own benchmarks or timed tests.

Quick verdict

Codacy combines mature, rule-based static analysis with a newer layer of AI review and AI governance, in one platform with a free IDE tier and a moderately priced Team plan. It suits teams that want deterministic quality gates and security scanning first and AI suggestions second. The main catches are that the AI Reviewer works only with GitHub, SSO and several AI governance features require the custom-priced Business plan, and the cloud product does not support on-premise Git servers.

Pro: A free Developer tier that brings AI Guardrails, security scanning and quality scanning into VS Code, Cursor, Windsurf and JetBrains IDEs.
Pro: Covers more than 40 languages, with tools such as ESLint, PMD, Pylint, Trivy and Opengrep, plus infrastructure-as-code scanning.
Pro: Quality gates, coverage and security findings sit next to AI review, so AI suggestions are grounded in deterministic analysis.
Pro: Free for public, open-source repositories.
Con: The AI Reviewer is available only for GitHub. GitLab and Bitbucket get the more limited AI-enhanced comments.
Con: The Team plan caps out at 30 developers and 100 private repositories, and SSO and audit logs require Business.
Con: No support for on-premise Git deployments in the cloud product.
Con: Seats are counted per Git contributor to private repositories, which can make costs harder to predict.

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What is Codacy?

Codacy is a cloud platform that connects to GitHub, GitLab and Bitbucket. It analyzes every commit and pull request and reports issues, security findings, duplication, complexity and coverage at the repository and organization level. Teams define coding standards and gate policies once and apply them across repositories, and failing checks can block a merge.

The current product is organized into AI Inventory, AI Guardrails, AI Risk Hub, AI Reviewer, Code Quality, Security and Coverage. Codacy’s AI features use enterprise instances of OpenAI and Google Gemini: Gemini powers the AI Reviewer, and OpenAI powers AI-enhanced comments and false-positive triage. Codacy says customer code will not be used by Codacy, OpenAI or any third-party AI provider to train models. The platform ships regular cloud updates; the September 2026 release added stack detection, coverage status improvements and more container image controls.

Key features

AI Reviewer for pull requests

The AI Reviewer combines Codacy’s rule-based analysis with AI reasoning. Codacy says it flags security issues with suggested fixes, finds critical functions without unit tests, highlights functions that have become too complex, spots duplicated code, and checks whether the PR description matches what the code actually does. It adds a summary to the pull request, can use linked Jira tickets as context, and reads repository-specific instructions from .codacy/instructions/review.md. It is opt-in, available on GitHub only, and included in the Team and Business plans.

AI Guardrails in the IDE

Guardrails is part of Codacy’s free IDE extension for VS Code, Cursor, Windsurf and JetBrains IDEs. It bundles a local analyzer and installs a Codacy MCP server, so AI agents in the editor (for example Copilot or Junie in agent mode) can check generated code against your rules and fix issues before they are committed. You can also query Codacy findings from the AI chat panel.

Static analysis, quality gates and coverage

Codacy runs established open-source analyzers and reports issues, duplication and complexity per file and per pull request. Coverage reports feed the same dashboards, and gates can require minimum coverage or block new critical issues. In February 2026 Codacy migrated its Semgrep-based rules to Opengrep, and it continues to add tools such as Oxlint.

Security scanning

Plans include SAST, software composition analysis, secret detection and infrastructure-as-code scanning. Team adds malicious package detection. Business adds daily re-scans against new CVEs, license scanning, DAST, container image scanning and AI-based false-positive triage.

AI Risk Hub and AI Inventory

On the Business plan, AI Risk Hub lets you define and enforce AI coding policies covering risks such as unvetted models, concealed prompt-injection attempts and outdated dependencies. AI Inventory tracks the AI models, MCP servers and coding-tool configurations (for example Cursor rules or CLAUDE.md files) found in your codebase, and updates on every commit. These features are aimed at engineering leaders who need to govern how AI tools are used, not just review their output.

Integrations, API and CLIs

Codacy integrates with Jira and Slack, offers webhooks and a public API, and ships both an Analysis CLI for local and CI runs and a Cloud CLI for managing the platform. Organizations can group repositories into segments for reporting.

Who should use Codacy

Codacy suits engineering teams of up to about 30 developers on GitHub, GitLab Cloud or Bitbucket Cloud who want automated quality and security gates on every pull request, with AI review as an extra layer. It also suits larger organizations that want to govern AI coding tools centrally and can negotiate a Business plan, and open-source maintainers who want free scanning.

Who should skip it

Skip Codacy if your code lives on an on-premise Git server, if you mainly want a conversational AI reviewer on GitLab or Bitbucket, or if you are a small team that only needs AI pull request comments and no static analysis or coverage tracking.

Strengths and limitations

Strengths

Deterministic first, AI second. Rule-based analysis, coverage and gates give predictable results, and AI review adds context on top rather than replacing them.
Broad language and tool coverage. One configuration covers dozens of languages and IaC formats, which suits polyglot organizations.
Useful free tier. Individual developers get IDE scanning and AI Guardrails at no cost, and open-source projects scan for free.
Organization-level standards. Coding standards, gate policies and segments make it practical to enforce the same rules across many repositories.
Clear AI data statements. AI features are opt-in, secrets are redacted before false-positive triage, and Codacy states that code is not used for model training.

Limitations

GitHub-only AI Reviewer. GitLab and Bitbucket teams get AI-enhanced comments, not the full reviewer with PR summaries and custom instructions.
Plan cliffs. Team stops at 30 developers and 100 private repositories, and SSO, audit logs, AI governance and false-positive triage are Business-only with custom pricing.
Static analysis noise. Rule-based tools can produce findings that are not worth fixing. AI triage helps, but only on Business, and you have to ask Codacy to enable it.
Hosting constraints. Cloud Codacy does not support on-premise Git servers, and the public pricing page does not list self-hosting.
Some rough edges. JetBrains Guardrails on Windows requires WSL and supports only local analysis, and the pricing page gives inconsistent language counts, so check support for your stack.

Pricing (as of October 2026)

Plan	Price	What you get
Developer	$0	The IDE extension for VS Code, IntelliJ and Cursor with AI Guardrails, scan-as-you-type, SAST, SCA, secret and quality scans, and handoff to an agent for fixes. No pull request integration.
Open source	$0	Scanning for public repositories, free forever according to Codacy.
Team	From $18/developer/month billed yearly, or $21 monthly	GitHub, GitLab and Bitbucket integration, cloud scans, AI Reviewer and merge gates, shared coding standards, coverage and merge policies, malicious package detection, and Jira and Slack. Up to 30 developers and 100 private repositories.
Business	Custom quote	Unlimited private projects, a priority scan queue, daily CVE re-scans, AI Inventory and AI Risk Hub, license scanning, DAST, container scanning, false-positive detection, custom rules, SSO/SAML, audit logs and a dedicated success manager. Penetration testing is billed separately.

A 14-day trial with no credit card is available, and a seat is required for every Git contributor who commits to a private repository added to Codacy. The pricing page lists only cloud Git providers and says Codacy does not support projects on on-premise Git deployments. Codacy’s documentation still covers a licensed Codacy Self-hosted installation on Kubernetes, so ask sales if you need it. Confirm current prices and limits on Codacy’s pricing page. See Codacy pricing

Prices verified on October 13, 2026 against the official Codacy pricing page. Plans change often — confirm on the vendor’s page before you buy.

Use cases

Codacy is a quality and security checkpoint, not a code generator, so its use cases center on enforcing standards around code that people and AI agents write. These scenarios are based on Codacy’s documentation and the research behind our review, not on hands-on testing.

Quality gates for a growing GitHub team

A team of 15 developers on GitHub wants every pull request checked for new issues, duplication, complexity and coverage drops before merge. Codacy’s Team plan connects to the repositories, applies shared coding standards and merge gates, and adds the AI Reviewer’s summary and suggestions to each PR. The caveat is that Team stops at 30 developers and 100 private repositories.

Checking AI-generated code before it is committed

Developers using Copilot or another agent in VS Code, Cursor, Windsurf or a JetBrains IDE want insecure patterns caught as code is generated. Codacy’s free IDE extension adds AI Guardrails, with a bundled local analyzer and an MCP server the agent can call to scan and fix its own output. In our assessment, this is a low-cost first step for individuals, though JetBrains on Windows requires WSL and supports only local analysis.

Governing AI tool use across an organization

An engineering leader needs to know which AI models, MCP servers and coding-tool configurations are in use across hundreds of repositories, and to enforce policies on them. On the Business plan, AI Inventory tracks these on every commit and AI Risk Hub enforces centralized AI coding policies. Both require a custom-priced Business contract.

Free scanning for an open-source project

A maintainer of a public library wants automated static analysis and security checks on contributions without paying for seats. Codacy says scanning is free forever for open-source projects on public repositories. Check whether your project’s languages and tools are covered before you rely on it.

Alternatives

SonarQube: a long-established code quality and security platform with self-managed and cloud options.
DeepSource: rule-based static checks combined with AI review on pull requests, with suggested fixes. It is the closest like-for-like comparison.
CodeRabbit: an AI-first pull request reviewer for GitHub, GitLab, Bitbucket and Azure DevOps.
Qodo: a code review and governance platform with on-prem deployment options.

Final verdict

Codacy is a solid choice for teams that want deterministic quality and security gates and are adding AI review and AI governance on top. The free IDE tier and $18-per-developer Team plan make it accessible, but the GitHub-only AI Reviewer, Business-only SSO and lack of on-premise Git support are real constraints. If those fit your setup, the 14-day trial is an easy way to see how it handles your repositories.

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FAQ

Is Codacy free?

Partly. The Developer plan is free and includes the IDE extension with AI Guardrails and local security and quality scans, and Codacy says scanning is free forever for open-source projects. Pull request integration, the AI Reviewer and merge gates for private repositories require a paid plan, which comes with a 14-day trial and no credit card required. Check Codacy’s pricing page for current details.

Does Codacy work with GitLab and Bitbucket?

Yes. The cloud product supports GitHub, GitLab and Bitbucket. However, the AI Reviewer is GitHub-only, so GitLab and Bitbucket users get AI-enhanced comments on issues instead. Codacy’s pricing page says on-premise Git deployments are not supported.

Is my code used to train AI models?

Codacy states that customer code will not be used by Codacy, OpenAI or any third-party AI provider for training. Its AI features are opt-in and use enterprise instances of OpenAI and Google Gemini. For the AI Reviewer and false-positive triage, Codacy says data is not stored on its side.

Which IDEs does Codacy support?

Codacy’s IDE extension, which includes AI Guardrails, works with Visual Studio Code, Cursor, Windsurf and JetBrains IDEs such as IntelliJ IDEA and PyCharm. In VS Code-based editors it installs a Codacy MCP server so AI agents can scan their own output. On Windows, JetBrains support requires WSL.

Can Codacy be self-hosted?

The public pricing page lists only cloud plans. Codacy’s documentation still describes a licensed Codacy Self-hosted installation on Kubernetes, with release notes for v16.0.0 in January 2026. If you need self-hosting, confirm availability and terms with Codacy’s sales team.

Codacy vs SonarQube: which is better?

Both are established static analysis and quality-gate platforms. SonarQube offers self-managed and cloud options, while Codacy is cloud-first and adds IDE AI Guardrails, a GitHub AI Reviewer and AI governance features. In our assessment, Codacy suits cloud-hosted teams focused on governing AI-written code, and SonarQube suits organizations that need to run analysis on their own infrastructure.

Codacy Review (2026): Code Quality Gates Meet AI Review and Guardrails