High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 158 languages, sub-ms queries, 99% fewer tokens. Single static binary, zero dependencies.
MCP server for Claude Code-style tools
This project provides an MCP server that adds Claude Code-like file and command tools to an MCP client. It includes read, write, edit, search, notebook, todo, batch, and agent-delegation tools for working on projects directly.
Builders who use Claude Desktop or another MCP client and want it to work on files, notebooks, and shell tasks.
You can let your agent inspect a project, make edits, run commands, and delegate subtasks without leaving the MCP client.
What it does
File reading and editing
Provides `read`, `write`, `edit`, `multi_edit`, `content_replace`, and `directory_tree` tools for working with project files.
Code search
Adds `grep` and `grep_ast` for fast pattern search and structure-aware code discovery.
Shell command execution
Uses `run_command` to execute commands and support file and directory operations through the shell.
Notebook support
Includes `notebook_read` and `notebook_edit` for reading and changing Jupyter notebooks with cell and output handling.
Agent delegation
Offers `dispatch_agent` and `batch` so one request can launch sub-agents or multiple tool calls.
Task tracking and reasoning
Includes `think`, `todo_write`, and `todo_read` for structured reasoning and task lists.
Security controls
Implements permission prompts, directory restrictions, and input validation for file and command actions.
README
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.

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 | Read file contents with line numbers, offset, and limit capabilities |
write | Create or overwrite files |
edit | Make line-based edits to text files |
multi_edit | Make multiple precise text replacements in a single file operation with atomic transactions |
directory_tree | Get a recursive tree view of directories |
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) |
notebook_read | Extract and read source code from all cells in a Jupyter notebook with outputs |
notebook_edit | 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 |
batch | Execute multiple tool invocations in parallel or serially in a single request |
todo_write | Create and manage a structured task list |
todo_read | Read a structured task list |
Getting Started
For detailed installation and configuration instructions, please refer to INSTALL.md.
For detailed tutorial of 0.3 version, please refer to TUTORIAL.md
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:
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature) - Commit your 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.
Files in the repo
- .github
- doc
- mcp_claude_code
- tests
- .gitignore
- .python-version
- CHANGELOG.md
- LICENSE
- Makefile
- pyproject.toml
- README.md
- uv.lock
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