MCP Code Checker
MCP server providing code quality checks (pylint and pytest) with smart LLM-friendly prompts for analysis and fixes. Enables Claude and other AI assistants to analyze your code and suggest improvements.
What is MCP Code Checker?
What is MCP Code Checker? MCP Code Checker is a Model Context Protocol (MCP) server that provides code quality checking operations, enabling AI assistants to perform quality checks on code within a specified project directory. How to use MCP Code Checker? To use MCP Code Checker, clone the repository, set up a virtual environment, install dependencies, and run the server with the command: python -m src.main --project-dir /path/to/project. You can also configure it to work with AI assistants like Claude. Key features of MCP Code Checker? Run pylint checks to identify code quality issues. Execute pytest to identify failing tests. Generate smart prompts for LLMs to explain issues and suggest fixes. Combine multiple checks for comprehensive code quality analysis. Use cases of MCP Code Checker? Identifying and fixing code quality issues in Python projects. Running automated tests to ensure code reliability. Enhancing debugging workflows by integrating AI assistance. FAQ from MCP Code Checker? Can MCP Code Checker be used with any Python project? Yes! It can be used with any Python project by specifying the project directory. Is there a graphical interface for MCP Code Checker? No, it operates via command line and integrates with AI assistants for enhanced functionality. What is the license for MCP Code Checker? It is licensed under the MIT License.
As an MCP (Model Context Protocol) server, MCP Code Checker enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.
How to use MCP Code Checker
To use MCP Code Checker, clone the repository, set up a virtual environment, install dependencies, and run the server with the command: python -m src.main --project-dir /path/to/project. You can also configure it to work with AI assistants like Claude. Key features of MCP Code Checker? Run pylint checks to identify code quality issues. Execute pytest to identify failing tests. Generate smart prompts for LLMs to explain issues and suggest fixes. Combine multiple checks for comprehensive code quality analysis. Use cases of MCP Code Checker? Identifying and fixing code quality issues in Python projects. Running automated tests to ensure code reliability. Enhancing debugging workflows by integrating AI assistance. FAQ from MCP Code Checker? Can MCP Code Checker be used with any Python project? Yes! It can be used with any Python project by specifying the project directory. Is there a graphical interface for MCP Code Checker? No, it operates via command line and integrates with AI assistants for enhanced functionality. What is the license for MCP Code Checker? It is licensed under the MIT License.
Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.
Use Cases for this MCP Server
- No use cases specified.
MCP servers like MCP Code Checker can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.
About Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like MCP Code Checker provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.
Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.