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MCP implementation of Claude Code capabilities

Project description

MCP Claude Code

An implementation of Claude Code capabilities using the Model Context Protocol (MCP).

Overview

This project provides an MCP server that implements Claude Code-like functionality, allowing Claude to directly execute instructions for modifying and improving project files. By leveraging the Model Context Protocol, this implementation enables seamless integration with various MCP clients including Claude Desktop.

example

Features

  • Code Understanding: Analyze and understand codebases through file access and pattern searching
  • Code Modification: Make targeted edits to files with proper permission handling
  • Enhanced Command Execution: Run commands and scripts in various languages with improved error handling and shell support
  • File Operations: Manage files with proper security controls through shell commands
  • Code Discovery: Find relevant files and code patterns across your project with high-performance searching
  • Agent Delegation: Delegate complex tasks to specialized sub-agents that can work concurrently
  • Multiple LLM Provider Support: Configure any LiteLLM-compatible model for agent operations
  • Jupyter Notebook Support: Read and edit Jupyter notebooks with full cell and output handling

Tools Implemented

Tool Description
read_files Read one or multiple files with encoding detection
write Create or overwrite files
edit_file Make line-based edits to text files
directory_tree Get a recursive tree view of directories
get_file_info Get metadata about a file or directory
grep Fast pattern search in files with ripgrep integration for best performance (docs)
content_replace Replace patterns in file contents
grep_ast Search code with AST context showing matches within functions, classes, and other structures
run_command Execute shell commands (also used for directory creation, file moving, and directory listing)
run_script Execute scripts with specified interpreters
script_tool Execute scripts in specific programming languages
read_notebook Extract and read source code from all cells in a Jupyter notebook with outputs
edit_notebook Edit, insert, or delete cells in a Jupyter notebook
think Structured space for complex reasoning and analysis without making changes
dispatch_agent Launch one or more agents that can perform tasks using read-only tools concurrently

Getting Started

For detailed installation and configuration instructions, please refer to INSTALL.md.

For optimal performance, we recommend installing ripgrep to accelerate file content searches. See Grep migration docs for details.

Of course, you can also read USEFUL_PROMPTS for some inspiration on how to use mcp-claude-code.

Security

This implementation follows best practices for securing access to your filesystem:

  • Permission prompts for file modifications and command execution
  • Restricted access to specified directories only
  • Input validation and sanitization
  • Proper error handling and reporting

Development

To contribute to this project:

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

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