Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@VSCode MCP Python ServerAnalyze the functions in tools.py and explain their purpose."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server - Model Context Protocol Server
A production-ready MCP (Model Context Protocol) server for VSCode and Claude integration with comprehensive tool support, performance monitoring, and diagnostics.
Version
Current Version: 1.0.0
Release Date: January 13, 2026
Status: Development
Features
⚡ Technical Optimizations
Reduced Token Overhead: Instead of pasting large datasets into the chat, the MCP server allows Claude to query only the specific data it needs. This results in faster responses and lower cost/token usage.
Asynchronous Execution: By leveraging Python’s asynchronous capabilities, the server can handle multiple data requests simultaneously without freezing the interaction.
Custom Tool Mapping: You can wrap complex Python libraries (like
pandas,beautifulsoup, oros) into simple tools that Claude can call instantly.
🌟 Value Added to Projects
Bridging the Gap: It turns Claude from a "chatbot" into a "developer agent" that can actually see and modify your local code or databases.
Workflow Automation: You can automate repetitive tasks like log analysis, local file reorganization, or database querying simply by talking to Claude.
Private Data Context: Since the server runs locally, you can provide Claude with context from private documents or internal company data without ever uploading those files to the cloud.
Core Capabilities
10 Professional Tools - Complete file operations, code analysis, and VSCode integration
LRU Caching - Intelligent request caching for 2-3x performance improvement
Type Safety - 100% type hints (PEP 484 compliant)
Enterprise Architecture - SOLID principles, design patterns, professional structure
Comprehensive Logging - Structured logging to stderr for debugging
Error Handling - Production-grade error handling with specific exceptions
Installation
Prerequisites
Python 3.8 or higher
VSCode (optional, for VSCode integration features)
Windows, Linux, or macOS
Setup
Clone or download this repository
Ensure all files are in the same directory:
mcp_server.py- Main servertools.py- Tool implementationsvscode_detector.py- VSCode integrationdiagnostics.py- Health checksperformance_monitor.py- Performance trackinglanguages.json- Language configuration
Configure your Artifical intelligence Desktop(for claude) to use this server (see Configuration section)
Quick Start
Configuration
Add to your Claude Desktop config file:
Windows
%APPDATA%\Claude\claude_desktop_config.json
macOS
~/Library/Application Support/Claude/claude_desktop_config.json
Configuration Example
Usage Examples
Reading Files
Code Analysis
Writing Code
Modifying Code
Project Overview
Architecture
Main Components
MCPServer Class
Protocol handler implementing MCP 2024-11-05
JSON-RPC 2.0 communication
Async/await patterns
Request/response management
ToolRegistry Class
Tool registration and management
Input schema validation
Tool invocation
RequestCache Class
LRU caching mechanism
Configurable cache size
Automatic eviction
LanguageConfig Class
Language configuration management
Pattern matching for code analysis
File extension handling
Design Patterns
Registry Pattern - Tool management
Cache Pattern - Request caching
Dataclass Pattern - Type-safe metadata
Dependency Injection - Configuration management
Strategy Pattern - Tool execution
Performance
Optimization Features
LRU cache for safe tool requests
Async/await for non-blocking operations
Efficient file system scanning
Smart VSCode process detection
Minimal memory footprint
Performance Metrics
Metric | Value |
Startup Time | < 1 second |
Tool Execution | 10-100ms (cached: <1ms) |
Memory Usage | ~50MB |
Cache Hit Rate | 70-90% |
Diagnostics
Health Checks
Run comprehensive diagnostics:
Diagnostic Tests
Python version compatibility
Required files existence
File permissions
Configuration validity
Module imports
Syntax checking
Disk space
Memory usage
VSCode status
Network connectivity
Development
Code Quality Standards
PEP 8 - Style guide compliance
PEP 257 - Docstring conventions
PEP 484 - Type annotations
Google Style - Docstring format
Testing
Troubleshooting
Common Issues
Server Won't Start
Check Python version:
python --version(must be 3.8+)Run diagnostics:
python diagnostics.pyCheck syntax:
python -m py_compile mcp_server.py
Tools Not Working
Verify file permissions
Check languages.json is valid JSON
Run import test:
python -c "import tools"
VSCode Detection Fails
Ensure VSCode is running
Check process permissions (Windows)
Verify workspace directory is accessible
Permission Errors
Run as administrator (if needed)
Check file/directory permissions
Verify paths in configuration
Code Contribution Guidelines
Follow PEP 8 style guide
Add type hints to all functions
Write comprehensive docstrings
Include error handling
Add tests for new features
Update README for new tools
Adding New Tools
Implement tool function in
tools.pyAdd tool definition in
mcp_server.pyTOOL_DEFINITIONSRegister tool in
main()functionUpdate README documentation
Add diagnostic checks if needed
License
MIT License - See LICENSE file for details
Support
Documentation
Full API reference in code docstrings
Usage examples in this README
Diagnostic tools for troubleshooting
Getting Help
Run diagnostics:
python diagnostics.pyCheck logs in stderr output
Review error messages carefully
Verify configuration files
Credits
Author: Kommandant
Version: 1.0.0
License: MIT
Status: Development