Advanced MCP Server
Click on "Deploy 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., "@Advanced MCP Servercreate a new session with file operations and command execution tools"
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.
Advanced MCP Server
An implementation of the Model Context Protocol (MCP) server that provides AI coding agents with a secure, flexible, and extensible environment for executing coding tasks.
Features
Session Management
Resource Management
Sandboxed Tool Execution
Policy Engine
Multi-Agent Collaboration
Extensible Tooling
Rate Limiting
Custom Tools (Code Analysis, Testing, Documentation)
Related MCP server: Docker MCP Server
Getting Started
Prerequisites
Node.js 18+
Docker (optional, for enhanced sandboxing)
Docker Compose (optional)
Installation
Clone the repository
Install dependencies:
npm install
Development
To start the development server:
npm run devTo start with Docker:
docker-compose upBuilding
To build the TypeScript code:
npm run buildTesting
To run tests:
npm testTo run tests with coverage:
npm run test:coverageAPI Documentation
Detailed API documentation is available in the following formats:
Using with Qwen Code
The MCP Server is designed to work seamlessly with Qwen Code. After starting the server:
Start the server:
npm run devConfigure Qwen Code to use the MCP server by creating a
.qwen/settings.jsonfile:{ "mcpServers": { "local-fullstack-mcp": { "name": "Local Fullstack MCP Server", "transport": "http", "url": "http://localhost:8080", "default": true } } }Initialize a session:
curl -X POST http://localhost:8080/session/init \ -H "Content-Type: application/json" \ -d '{"tools": ["readFile", "writeFile", "runCommand", "listFiles"]}'Use the session ID with Qwen Code commands to perform operations in a secure, sandboxed environment.
See the Qwen CLI Integration Guide for detailed instructions.
Architecture
The MCP server follows a modular architecture with the following components:
MCP Gateway - Accepts connections (gRPC + WebSocket for streaming)
Session Manager - Handles authentication, session lifecycle, and capability negotiation
Resource Manager - File system abstraction with policy enforcement
Execution Manager - Runs commands/tools inside sandboxed runtimes (Docker)
Policy Engine - Enforces access rules and maintains audit logs
Audit Log - Immutable logging system for accountability
Sandbox Runtime - Docker containers with controlled resources
Workspace Storage - Persistent project storage (bind-mounted or virtual FS)
Security
Sandboxed execution using Docker containers
Resource policy enforcement
Audit logging for all actions
Capability negotiation
Rate limiting
Policy-based access control
License
MIT
Related MCP Connectors
- mcp-serverOAuthai.cdbx
Build Apps and run code in 30 languages — sandboxed, with persistent sessions for agent loops.
Build, validate, and deploy multi-agent AI solutions from any AI environment.
Hosted runtime for persistent agent teams, durable workflows, memory, schedules, and goals.
Governance layer for AI coding agents: knowledge-graph grounding, session audit, policy controls.
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