
Claude Desktop
Desktop · Freemium · Proprietary
Anthropic's official Claude AI desktop application. Supports MCP servers to extend functionality.

SDGLBL/mcp-claude-code
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.
See repository
Setup steps are in the repository README.
An implementation of Claude Code capabilities using the Model Context Protocol (MCP).
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
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
Details on this page are taken from the project's README. Open README
Clients mentioned in this server's README:

microsoft/playwright
Playwright is a framework for web automation and testing. It drives Chromium, Firefox, and WebKit with a single API — in your tests, in your scripts, and as a tool for AI agents.

yamadashy/repomix
Repomix is a tool that packs a codebase into an AI-friendly format, supporting local and remote repository processing and providing code compression, security checks and multiple output formats.

bytedance/UI-TARS-desktop
TARS is ByteDance's multimodal AI agent stack, shipping two projects: Agent TARS (a CLI and Web UI agent built on MCP) and UI-TARS-desktop (a desktop GUI agent).

ahujasid/blender-mcp
formerly blender-mcp — the PyPI package is now mcp-for-blender. Existing setups keep working; no config change is required. Read more.

microsoft/playwright-mcp
A Model Context Protocol (MCP) server that provides browser automation capabilities using Playwright. This server enables LLMs to interact with web pages through structured accessibility snapshots, bypassing the need for screenshots or visually-tuned models.

comet-ml/opik
Opik is the open-source LLM observability and evaluation platform for AI agent tracing, LLM evaluation, prompt management, and production monitoring. Built by Comet. Apache-2.0 licensed, free to self-host the full platform, with 20,000+ GitHub stars.