Codacy MCP Server Integration

What does “Codacy” MCP Server do?

The Codacy MCP (Model Context Protocol) Server acts as a bridge between AI assistants and the Codacy platform, enabling enhanced programmatic access to code quality, security, coverage, and repository management data. By exposing Codacy’s API and content as structured tools, resources, and context, this server allows AI-powered workflows to automate code analysis, manage repositories, analyze pull requests, and enforce code standards. Developers can use the Codacy MCP Server to query repositories, analyze files, manage organizational settings, and perform security checks, streamlining the software development lifecycle and improving code health by integrating Codacy’s capabilities directly into AI-driven or automated development environments.

List of Prompts

No prompt templates are mentioned in the repository or documentation.

List of Resources

No explicit list of MCP resources is provided in the repository or documentation.

List of Tools

The following tools are described as available via the Codacy MCP Server:

• Repository Setup and Management
  Tools for initializing, configuring, and managing repositories on Codacy.
• Organization and Repository Management
  Functions to manage organizations and repositories, such as adding/removing members or configuring settings.
• Code Quality and Analysis
  Analyze source code for quality metrics, code coverage, and maintainability.
• File Management and Analysis
  Tools to access, analyze, and manage files within repositories.
• Security Analysis
  Perform security scans and audits on codebases to identify vulnerabilities.
• Pull Request Analysis
  Tools to analyze, review, and provide feedback on pull requests.
• Tool and Pattern Management
  Manage analysis tools and patterns used for code reviews and quality checks.
• CLI Analysis
  Support for command-line driven code analysis.

Use Cases of this MCP Server

• Automated Code Quality Checks
  Integrate Codacy’s metrics into CI/CD pipelines to automatically enforce code quality and coverage standards on every commit.
• Security Auditing
  Use the server’s tools to regularly scan repositories for vulnerabilities, improving codebase security posture.
• Repository Management at Scale
  Manage multiple repositories and organizations programmatically, automating settings and member management.
• Context-Aware Pull Request Reviews
  Enable AI agents to fetch and analyze pull request data, providing actionable feedback or automating review comments.
• Dynamic Tool and Pattern Enforcement
  Programmatically adjust the analysis tools and code patterns enforced across projects to maintain consistent standards.

How to set it up

Windsurf

1. Ensure Node.js is installed on your machine.
2. Obtain a personal Codacy API Access Token.
3. Edit your Windsurf configuration file.
4. Add the Codacy MCP Server to the mcpServers object:

   "mcpServers": {
     "codacy": {
       "command": "npx",
       "args": ["@codacy/mcp-server@latest"]
     }
   }
   

5. Save the file and restart Windsurf.
6. Verify that the Codacy MCP Server is available in your MCP server list.

Securing API Keys (Example)

"mcpServers": {
  "codacy": {
    "command": "npx",
    "args": ["@codacy/mcp-server@latest"],
    "env": {
      "CODACY_API_TOKEN": "your_api_token_here"
    },
    "inputs": {}
  }
}

Claude

1. Ensure Node.js is installed.
2. Obtain your Codacy API token.
3. Locate and edit Claude’s MCP server configuration.
4. Add Codacy’s MCP server as follows:

   "mcpServers": {
     "codacy": {
       "command": "npx",
       "args": ["@codacy/mcp-server@latest"]
     }
   }
   

5. Save changes and restart Claude.
6. Check for Codacy MCP Server in available tools.

Securing API Keys

(Use the env property as shown in Windsurf example.)

Cursor

1. Install Node.js if not present.
2. Get your Codacy API token.
3. Open Cursor’s configuration.
4. Add Codacy MCP server:

   "mcpServers": {
     "codacy": {
       "command": "npx",
       "args": ["@codacy/mcp-server@latest"]
     }
   }
   

5. Save and restart Cursor to activate.

Securing API Keys

(See Windsurf example.)

Cline

1. Ensure Node.js is installed.
2. Secure your Codacy API key.
3. Edit your Cline configuration file.
4. Register the Codacy MCP server:

   "mcpServers": {
     "codacy": {
       "command": "npx",
       "args": ["@codacy/mcp-server@latest"]
     }
   }
   

5. Save and restart Cline.

Securing API Keys

(Use the env property as above.)

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "codacy": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “codacy” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the two tables, the Codacy MCP Server is well-documented for tools and setup, with good security practices, but lacks explicit prompt templates, resources, and sampling/roots documentation. I would rate this MCP a 6/10 for completeness and developer friendliness.

MCP Score