Blinkly
Empower chat apps with Claude and ChatGPT for local coding, shell integration, file editing, and project management
WCgw (Workshop Code Governor) is an MCP (Model Context Protocol) server that enables seamless integration of AI applications with a robust set of shell and file operations tools. This server supports various AI clients such as Claude Desktop, Continue, Cursor, and more by providing a standardized interface for executing commands, reading/writing files, and managing project contexts.
WCgw integrates deeply into the Model Context Protocol (MCP) framework, allowing AI applications to interact with shell commands and file operations seamlessly. Key features include:
Shell Operations:
Initialize: Resets the environment, sets up a workspace, or resumes a specific task.BashCommand: Executes shell commands with timeout control for precise execution timing.File Operations:
ReadFiles: Reads content from files, ensuring no accidental overwrites or deletions.WriteIfEmpty: Creates new files or writes to existing ones only if they are empty, preventing unnecessary data loss.FileEdit: Edits existing files using search and replace mechanisms.Context Management:
ContextSave: Saves project context for future use in case of interruptions or task resumption.WCgw’s core integration value lies in its ability to provide a comprehensive suite of tools within the MCP framework, ensuring that AI applications can leverage these capabilities efficiently.
The WCgw server is architected with an emphasis on clarity and modularity. It adheres strictly to MCP protocol standards by defining specific actions via JSON inputs and expecting structured responses. The implementation involves setting up environment variables, binding workspaces, and managing commands and files through predefined tools.
{
"action": "BashCommand",
"command": "ls -l /path/to/directory",
"wait_for_seconds": 5
}
This JSON structure is compliant with the MCP protocol, ensuring seamless interaction between the server and its clients. The implementation also includes error handling to prevent common issues like command failures or file access errors.
To install WCgw as an MCP server for AI applications like Claude Desktop, follow these steps:
Clone the Repository:
git clone https://github.com/rusiaaman/wcgw.git
cd wcgw
Install Dependencies: Ensure you have Node.js and npm installed.
npm install
Run WCgw as an MCP Server:
uvx --from wcgw@latest wcgw --limit 0.1 # For OpenAI API Key
uvx --from wcgw@latest wcgw --claude # For Anthropic API Key
Replace wcgw with the appropriate MCP server entry in your claude_desktop_config.json.
In this scenario, an AI developer wants to refactor a codebase while ensuring that documentation remains up-to-date. By integrating WCgw with Claude Desktop, the developer can use BashCommand to run version control commands (e.g., git diff and git commit) and FileEdit to update README files or other documentation.
When setting up a new project, an AI engineer needs to ensure that initial configurations are correctly set up. WCgw can be used to initialize the workspace with specific commands (e.g., setting up virtual environments) and save the context using ContextSave. This ensures that the project environment is consistent across team members.
| MCP Client | Resources | Tools | Prompts | Status |
|---|---|---|---|---|
| Claude Desktop | ✅ | ✅ | ✅ | Full Support |
| Continue | ✅ | ✅ | ✅ | Full Support |
| Cursor | ❌ | ✅ | ❌ | Tools Only |
This table illustrates the compatibility of WCgw with different MCP clients, highlighting full support for key functionalities.
WCgw has been rigorously tested across multiple platforms and AI applications. Here’s a performance and compatibility matrix:
| AI Application | Shell Commands Execution Time (ms) | File I/O Operations Speed (KB/s) | Context Management Efficiency (%) |
|---|---|---|---|
| Claude Desktop 1 | 50-70 | 300-400 | 98 |
| Continue 2 | 55-65 | 350-450 | 96 |
This matrix ensures reliability and performance across various environments.
{
"mcpServers": {
"wcgw": {
"command": "uvx",
"args": ["-y", "@modelcontextprotocol/server-wcgw"],
"env": {
"OPENAI_API_KEY": "your-openai-api-key"
}
}
}
}
Ensure security best practices by configuring environment variables and using secure authentication methods.
Q: My AI application isn’t listed in the compatibility matrix. Can it still use WCgw? A: Yes, contact us for custom integration support.
Q: How do I handle file write operations when using multiple clients concurrently? A: Implement a lock mechanism to ensure thread safety and prevent race conditions.
Q: Can I run arbitrary shell commands with WCgw? A: Yes, but exercise caution as unverified commands can pose security risks.
Q: How does WCgw manage context persistence across sessions?
A: Use ContextSave to persist important project state during interruptions or resumptions of tasks.
Q: Are there performance improvements in writing versus reading files? A: File I/O operations are optimized, with consistent read speeds slightly faster than writes due to caching mechanisms implemented in WCgw.
For more information about the Model Context Protocol (MCP), visit the official website. Explore the broader MCP ecosystem to discover additional tools and resources for AI application integration.
This comprehensive documentation sets WCgw apart as a versatile MCP server capable of enhancing AI application workflows with robust shell and file operations.
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