MCP Claude Code
Claude Code-like functionality via the Model Context Protocol.
Key Features
Use Cases
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.
Star History
Repository Owner
User
Repository Details
Programming Languages
Tags
Topics
Join Our Newsletter
Stay updated with the latest AI tools, news, and offers by subscribing to our weekly newsletter.
Related MCPs
Discover similar Model Context Protocol servers
Lucidity MCP
Intelligent prompt-based code quality analysis for AI coding assistants.
Lucidity MCP is a Model Context Protocol (MCP) server that empowers AI coding assistants to deliver high-quality code through intelligent, prompt-driven analysis. It offers comprehensive detection of code issues across multiple quality dimensions, providing structured and actionable feedback. With language-agnostic capabilities, extensible framework, and flexible transport options, Lucidity MCP seamlessly integrates into developer workflows and AI systems.
- ⭐ 72
- MCP
- hyperb1iss/lucidity-mcp
Exa MCP Server
Fast, efficient web and code context for AI coding assistants.
Exa MCP Server provides a Model Context Protocol (MCP) server interface that connects AI assistants to Exa AI’s powerful search capabilities, including code, documentation, and web search. It enables coding agents to retrieve precise, token-efficient context from billions of sources such as GitHub, StackOverflow, and documentation sites, reducing hallucinations in coding agents. The platform supports integration with popular tools like Cursor, Claude, and VS Code through standardized MCP configuration, offering configurable access to various research and code-related tools via HTTP.
- ⭐ 3,224
- MCP
- exa-labs/exa-mcp-server
Unichat MCP Server
Universal MCP server providing context-aware AI chat and code tools across major model vendors.
Unichat MCP Server enables sending standardized requests to leading AI model vendors, including OpenAI, MistralAI, Anthropic, xAI, Google AI, DeepSeek, Alibaba, and Inception, utilizing the Model Context Protocol. It features unified endpoints for chat interactions and provides specialized tools for code review, documentation generation, code explanation, and programmatic code reworking. The server is designed for seamless integration with platforms like Claude Desktop and installation via Smithery. Vendor API keys are required for secure access to supported providers.
- ⭐ 37
- MCP
- amidabuddha/unichat-mcp-server
Plane MCP Server
Enables LLMs to manage Plane.so projects and issues via the Model Context Protocol.
Plane MCP Server provides a standardized interface to connect large language models with Plane.so project management APIs. It enables LLMs to interact directly with project and issue data, supporting tasks such as listing projects, retrieving detailed information, creating and updating issues, while prioritizing user control and security. Installation is streamlined through tools like Smithery, and configuration supports multiple clients including Claude for Desktop.
- ⭐ 32
- MCP
- kelvin6365/plane-mcp-server
Azure DevOps MCP Server
Standardized AI access to Azure DevOps via Model Context Protocol.
Implements the Model Context Protocol (MCP) to enable AI assistants to securely and efficiently interact with Azure DevOps resources. Provides a standardized bridge for managing projects, work items, repositories, pull requests, and pipelines through natural language interfaces. Supports modular authentication and a feature-based architecture for scalability and integration. Facilitates seamless integration with AI tools such as Claude Desktop and Cursor AI.
- ⭐ 306
- MCP
- Tiberriver256/mcp-server-azure-devops
Taskade MCP
Tools and server for Model Context Protocol workflows and agent integration
Taskade MCP provides an official server and tools to implement and interact with the Model Context Protocol (MCP), enabling seamless connectivity between Taskade’s API and MCP-compatible clients such as Claude or Cursor. It includes utilities for generating MCP tools from any OpenAPI schema and supports the deployment of autonomous agents, workflow automation, and real-time collaboration. The platform promotes extensibility by supporting integration via API, OpenAPI, and MCP, making it easier to build and connect agentic systems.
- ⭐ 90
- MCP
- taskade/mcp
Didn't find tool you were looking for?