Codacy MCP Server

The Codacy MCP Server bridges AI assistants with the full breadth of Codacy’s static analysis platform. By exposing a rich set of tools, it lets developers query repository metadata, pull quality and security metrics, and even trigger new analyses—all through a single, unified protocol. This removes the need to manually navigate Codacy’s web UI or write bespoke API wrappers, allowing AI agents to surface actionable insights directly within the developer’s workflow.

At its core, the server solves the problem of fragmented code quality data. Developers often juggle multiple dashboards—coverage reports, issue trackers, and security scans—each with its own API endpoints. The Codacy MCP Server consolidates these into a coherent interface: tools such as , , and provide granular, filter‑able views of code health. This unified access streamlines audits, technical debt reviews, and compliance checks by delivering all relevant metrics in one place.

Key capabilities include:

• Repository management – Register or list repositories and organizations, ensuring the AI can operate on any codebase tracked by Codacy.
• Code quality analysis – Retrieve, filter, and paginate through issues by severity, category, language, or author. This supports style guide enforcement, performance tuning, and complexity reduction.
• File‑level insights – Access per‑file metrics such as coverage, duplication clones, and detailed issue lists, enabling precise refactoring recommendations.
• Security scanning – Pull SAST, secrets, dependency, IaC, CI/CD, DAST, and pen‑testing findings from Codacy’s SRM dashboard, giving developers a single source for vulnerability management.
• Pull request integration – Analyze changes in the context of open PRs, facilitating code review automation.

In practice, a CI/CD pipeline could invoke the MCP server to fetch the latest security findings before merging. A pair‑programming session might use an AI assistant to surface style violations in the current file, while a senior developer reviews duplication clones highlighted by . During onboarding, new team members can query to understand the codebase’s health and prioritize learning objectives.

The server integrates seamlessly into AI workflows by exposing its tools as part of the MCP specification. An assistant can ask, “Show me all high‑severity security issues in this repository,” and receive a structured response without manual API calls. This tight coupling reduces friction, accelerates decision‑making, and ensures that code quality remains a first‑class citizen in the developer experience.