mcp-claude-code is an open-source project designed to implement Claude Code-like functionality through the Model Context Protocol (MCP). It provides an MCP server that enables Claude to directly execute instructions to modify and improve project files, and can seamlessly integrate with various MCP clients (such as Claude Desktop).
Main capabilities include:
- Code understanding: Analyze and understand codebases through file access and pattern search.
- Code modification: Make targeted edits to files with appropriate permission handling.
- Enhanced command execution: Run commands and scripts in various languages with improved error handling and shell support.
- File operations: Manage files through shell commands under secure controls.
- Code discovery: Find relevant files and code patterns in projects through high-performance search.
- Agent delegation: Delegate complex tasks to specialized sub-agents that can work concurrently.
- Multi-LLM provider support: Configure any LiteLLM-compatible model for agent operations.
- Jupyter Notebook support: Read and edit Jupyter notebooks, handling complete cells and outputs.
Usage: This implementation follows best practices for protecting file system access, including: permission prompts for file modification and command execution; access limited to specified directories; input validation and sanitization; and appropriate error handling and reporting. For specific installation and configuration instructions, refer to the INSTALL.md file in the project; for the detailed tutorial for version 0.3, refer to the TUTORIAL.md file.
Contributing: Fork the repository; create a feature branch (git checkout -b feature/amazing-feature); commit changes (git commit -m 'Add some amazing feature'); push to the branch (git push origin feature/amazing-feature); open a pull request.
License: This project is licensed under the MIT License; see the LICENSE file for details.
Applicable scenarios: Suitable for scenarios where Claude needs to assist with code understanding, modification, project analysis, and automated development through the MCP protocol.
Limitations: The materials do not provide specific information about platform compatibility, performance metrics, or pricing.
