claude-code-mcp is an MCP server that connects with the locally installed Claude Code command. It enables operations teams to automate code explanations and reviews. The server provides tools like explain_code and revise_code, integrating with existing workflows to streamline code analysis and maintenance.
git clone https://github.com/KunihiroS/claude-code-mcp.gitThe claude-code-mcp skill is designed to facilitate seamless connections between the MCP Server and local Claude Code commands. This automation skill enables users to streamline their workflows by allowing direct interaction with local commands, enhancing the overall efficiency of AI-driven tasks. By implementing this skill, developers can automate repetitive command executions, thus saving time and reducing the potential for manual errors. One of the primary benefits of using the claude-code-mcp skill is its ability to simplify complex workflows. While the exact time savings are not quantified, the intermediate implementation time of approximately 30 minutes suggests that users can quickly integrate this skill into their existing systems. This skill is particularly valuable for developers and product managers who are looking to enhance their AI automation strategies and improve their operational efficiency. The target audience for this skill includes developers, product managers, and AI practitioners who are engaged in workflow automation. By utilizing the claude-code-mcp skill, these professionals can create more robust AI agent skills that interact fluidly with local commands, thereby optimizing their processes. For instance, a developer could use this skill to automate the deployment of applications, allowing for faster release cycles and improved productivity. With an intermediate complexity level, the implementation of the claude-code-mcp skill requires a basic understanding of command-line interfaces and local server configurations. This skill fits seamlessly into an AI-first workflow by enabling automation that is critical for modern software development and operational tasks. As organizations increasingly adopt AI-driven solutions, incorporating skills like claude-code-mcp will be essential for maintaining a competitive edge.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/KunihiroS/claude-code-mcpCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
I'm using the explain_code tool to analyze this code snippet from our [PROJECT_NAME] repository. The code is in [PROGRAMMING_LANGUAGE] and is part of the [MODULE_NAME] module. Please provide a detailed explanation of what this code does, any potential issues, and suggestions for improvement. Here's the code: [CODE_SNIPPET].
Based on the provided code snippet from the 'user_authentication' module in the 'SecureLogin' project, here's my analysis: The code implements a password hashing function using the bcrypt algorithm in Python. It takes a plaintext password as input, generates a salt, and returns a hashed password. This is a good security practice as it ensures passwords are not stored in plaintext. Potential issues: 1. The salt generation could be more secure by using a cryptographically secure random number generator. 2. The function lacks input validation, which could lead to errors if non-string inputs are provided. 3. There's no error handling for cases where the hashing process fails. Suggestions for improvement: 1. Use secrets.SystemRandom() for salt generation to enhance security. 2. Add input validation to ensure the input is a string. 3. Implement try-except blocks to handle potential errors during hashing. 4. Consider adding a parameter to specify the work factor (cost) for the bcrypt algorithm to balance between security and performance.
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