STeLA MCP

A Python implementation of a Model Context Protocol server that provides secure access to local system operations via a standardized API interface.

STeLA (Simple Terminal Language Assistant) MCP is a lightweight server that provides secure access to local machine commands and file operations via a standardized API interface. It acts as a bridge between applications and your local system, implementing the Model Context Protocol (MCP) architecture.

Overview

STeLA MCP implements the Model Context Protocol (MCP) architecture to provide a secure, standardized way for applications to execute commands and perform file operations on a local machine. It serves as an intermediary layer that accepts requests through a well-defined API, executes operations in a controlled environment, and returns formatted results.

Features

• Command Execution: Run shell commands on the local system with proper error handling
• File Operations: Read, write, and manage files on the local system
• Directory Visualization: Generate recursive tree views of file systems
• Working Directory Support: Execute commands in specific directories
• Robust Error Handling: Detailed error messages and validation
• Comprehensive Output: Capture and return both stdout and stderr
• Simple Integration: Standard I/O interface for easy integration with various clients
• Multi-Directory Support: Configure multiple allowed directories for file operations
• Security-First Design: Strict path validation and command execution controls
• File Search: Search for files matching a pattern
• File Edit: Make selective edits to a file
• Type Safety: Strong type checking with Pydantic models for all tool inputs
• Path Validation: Enhanced symlink and parent directory validation

Installation

Installing via Smithery

To install STeLA for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @Sachin-Bhat/stela-mcp --client claude

Prerequisites

• Python 3.10 - 3.12
• pip or uv package manager
• Pydantic v2.x

Installation Steps

1. Clone the repository:

git clone <repository-url>
cd stela-mcp

1. Create and activate a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

1. Install dependencies:

pip install -e .

Creating a Binary Distribution

To create a self-contained binary:

1. Install PyInstaller:

pip install pyinstaller

1. Create the binary:

pyinstaller --onefile src/stella_mcp//server.py --name stela-mcp

The binary will be created in the dist directory.

Configuration

STeLA MCP can be configured using environment variables:

Directory Access Control

• ALLOWED_DIRS (Required): Comma-separated list of directories where file operations are allowed
• Example: /home/user/project,/home/user/docs
• Default: Current working directory if not specified

• Note: All paths must be absolute

• ALLOWED_DIR (Optional): Primary directory for command execution context

• Example: /home/user/project
• Default: First directory from ALLOWED_DIRS or current working directory
• Note: This is separate from ALLOWED_DIRS and controls command execution context

Command Execution Security

• ALLOWED_COMMANDS (Optional): Comma-separated list of allowed shell commands
• Example: ls,cat,pwd,echo
• Default: ls,cat,pwd,echo

• Special value: all to allow any command (not recommended)

• ALLOWED_FLAGS (Optional): Comma-separated list of allowed command flags

• Example: -l,-a,-h,--help
• Default: -l,-a,-h,--help

• Special value: all to allow any flag (not recommended)

• MAX_COMMAND_LENGTH (Optional): Maximum length of command strings

• Example: 1024
• Default: 1024

• Note: Prevents command injection via overly long strings

• COMMAND_TIMEOUT (Optional): Maximum execution time for commands in seconds

• Example: 60
• Default: 60
• Note: Prevents hanging commands

Example Configuration

# Directory access
export ALLOWED_DIRS="/home/user/project,/home/user/docs"
export ALLOWED_DIR="/home/user/project"

# Command execution
export ALLOWED_COMMANDS="ls,cat,pwd,echo"
export ALLOWED_FLAGS="-l,-a,-h,--help"
export MAX_COMMAND_LENGTH=1024
export COMMAND_TIMEOUT=60

Project Structure

stela-mcp/
├── src/
│   ├── stela_mcp/
│   │   ├── __init__.py
│   │   ├── shell.py        # Shell command execution
│   │   ├── filesystem.py   # File system operations
│   │   └── security.py     # Security configuration
│   └── server.py           # Main server implementation
├── pyproject.toml          # Project configuration
└── README.md

Usage

Starting the Server

Run the server using:

uv run python -m src.stella_mcp.server

The server will start and listen for connections through standard I/O.

Using with Claude Desktop

To use STeLA MCP with Claude Desktop:

1. Option 1: Using Python directly
2. Start the server using: bash uv run python -m src.stela_mcp.server

3. In Claude Desktop:

   • Go to Settings
   • Under "Tools", click "Add Tool"
   • Select "MCP Server"
   • Enter the following configuration:
   • Name: STeLA MCP
   • Path: The absolute path to your Python executable (e.g., /home/username/.venv/bin/python)
   • Arguments: -m src.stela_mcp.server
   • Working Directory: The path to your STeLA MCP project directory

4. Option 2: Using the binary

5. Copy the binary from dist/stela-mcp to a location in your PATH

6. In Claude Desktop:

   • Go to Settings
   • Under "Tools", click "Add Tool"
   • Select "MCP Server"
   • Enter the following configuration:
   • Name: STeLA MCP
   • Path: The absolute path to the binary (e.g., /usr/local/bin/stela-mcp)
   • Arguments: (leave empty)
   • Working Directory: (leave empty)

7. Once configured, you can use STeLA MCP tools in your conversations with Claude. For example:

8. "Show me the contents of my home directory"
9. "Create a new file called 'test.txt' with some content"

10. "Run the command 'ls -la' in my current directory"

11. Claude will automatically use the appropriate tools based on your requests and display the results in the conversation.

Available Tools

Command Tools

execute_command

Executes shell commands on the local system.

Parameters: * command (string, required): The shell command to execute * working_dir (string, optional): Directory where the command should be executed

Returns: * On success: Command output (stdout) * On failure: Error message and any command output (stderr)

change_directory

Changes the current working directory.

Parameters: * path (string, required): Path to change to

Returns: * On success: Success message with new path * On failure: Error message

File System Tools

read_file

Reads the contents of a file.

Parameters: * path (string, required): Path to the file to read

Returns: * On success: File contents * On failure: Error message

read_multiple_files

Reads multiple files simultaneously.

Parameters: * paths (array, required): List of file paths to read

Returns: * On success: Combined contents of all files * On failure: Error message and partial results

write_file

Writes content to a file.

Parameters: * path (string, required): Path where the file will be written * content (string, required): Content to write to the file

Returns: * On success: Success message * On failure: Error message

edit_file

Makes selective edits to a file.

Parameters: * path (string, required): Path to the file to edit * edits (array, required): List of edit operations * Each edit contains oldText and newText * dryRun (boolean, optional): Preview changes without applying

Returns: * On success: Git-style diff of changes * On failure: Error message

list_directory

Lists contents of a directory.

Parameters: * path (string, required): Path for the directory to list

Returns: * On success: List of files and directories * On failure: Error message

create_directory

Creates a new directory.

Parameters: * path (string, required): Path for the directory to create

Returns: * On success: Success message * On failure: Error message

move_file

Moves or renames files and directories.

Parameters: * source (string, required): Source path of the file or directory to move * destination (string, required): Destination path where the file or directory will be moved to

Returns: * On success: Success message * On failure: Error message

search_files

Searches for files matching a pattern.

Parameters: * path (string, required): Starting path for the search * pattern (string, required): Search pattern to match file and directory names * excludePatterns (array, optional): List of glob patterns to exclude

Returns: * On success: List of matching files * On failure: Error message

directory_tree

Generates a recursive tree view of files and directories.

Parameters: * path (string, required): Path for the directory to generate tree from

Returns: * On success: JSON structure representing the directory tree * On failure: Error message

get_file_info

Retrieves detailed metadata about a file or directory.

Parameters: * path (string, required): Path to the file or directory

Returns: * On success: File/directory metadata * On failure: Error message

list_allowed_directories

Lists all directories the server is allowed to access.

Parameters: * None

Returns: * On success: List of allowed directories * On failure: Error message

show_security_rules

Shows current security configuration.

Parameters: * None

Returns: * On success: Security configuration details * On failure: Error message

Security Considerations

STeLA MCP provides direct access to execute commands and file operations on the local system. Consider the following security practices:

• Run with appropriate permissions (avoid running as root/administrator)
• Use in trusted environments only
• Consider implementing additional authorization mechanisms for production use
• Be cautious about which directories you allow command execution and file operations in
• Implement path validation to prevent unauthorized access to system files
• Use the most restrictive configuration possible for your use case
• Regularly review and update allowed commands and directories
• Validate symlinks to prevent access outside allowed directories
• Ensure parent directory checks for file creation operations

Platform-Specific Security Notes

Linux/macOS

• Run with a dedicated user with limited permissions
• Consider using a chroot environment to restrict file system access
• Use chmod to restrict executable permissions
• Consider using SELinux/AppArmor for additional security

Windows

• Run as a standard user, not an administrator
• Consider using Windows Security features to restrict access
• Use folder/file permissions to limit access to sensitive directories
• Consider using Windows Defender Application Control

Development

Adding New Tools

To extend STeLA MCP with additional functionality, follow this pattern:

1. Define a Pydantic model for the tool's input parameters in server.py
2. Add a new method to the appropriate class in shell.py or filesystem.py
3. Register the tool in server.py using the @server.call_tool() decorator
4. Implement the tool handler with proper error handling and return types

Example:

from pydantic import BaseModel, Field

class MyToolInput(BaseModel):
    param1: str = Field(description="Description of param1")
    param2: int = Field(description="Description of param2")

@server.call_tool()
async def my_tool(request: Request[MyToolInput, str], arguments: MyToolInput) -> Dict[str, Any]:
    """Description of the tool."""
    try:
        # Tool implementation
        result = await do_something(arguments.param1, arguments.param2)
        return {"success": True, "result": result}
    except Exception as e:
        return {"error": str(e)}

License

Apache-2.0 License

Acknowledgements

• Built with the MCP Python SDK