server-mcp
Verified Safeby Marco-O94
Overview
AI-powered natural language interface for querying and managing data across multiple databases (MongoDB for paints, MySQL for food industry).
Installation
docker-compose up -dEnvironment Variables
- NODE_ENV
- MCP_SERVER_PORT
- FRONTEND_PORT
- OLLAMA_PORT
- NEXT_PUBLIC_API_URL
- NEXT_PUBLIC_OLLAMA_URL
- MONGO_INITDB_ROOT_USERNAME
- MONGO_INITDB_ROOT_PASSWORD
- MONGO_INITDB_DATABASE
- MONGODB_URI
- MYSQL_ROOT_PASSWORD
- MYSQL_DATABASE
- MYSQL_USER
- MYSQL_PASSWORD
- OLLAMA_MODEL
Security Notes
The core MCP server application correctly utilizes environment variables for database credentials, which is good practice. However, the `docker-utils.sh` script, used for common operations, hardcodes default passwords ('mongopassword', 'mysqlrootpassword') when accessing the database shells (e.g., `mongosh -u admin -p mongopassword ...`). While the README advises users to update their `.env` file with strong credentials, this helper script does not reference those `.env` variables for shell access, creating a potential exposure if a user updates `.env` but forgets about the script's hardcoded defaults, or if the script itself is run in an insecure environment. Additionally, `curl` commands in `docker-utils.sh` hardcode `localhost` ports (8080, 3000) for health checks, which may not align with custom `MCP_SERVER_PORT` or `FRONTEND_PORT` values in `.env`.
Similar Servers
mcp-server-mysql
A backend server application for a Modular Control Platform (MCP) or Microservice Control Plane, likely built with Node.js/TypeScript and integrating with MySQL, potentially featuring AI/LLM evaluation capabilities.
MCP-PostgreSQL-Ops
The MCP server provides professional operations, monitoring, and management capabilities for PostgreSQL databases using natural language queries.
DBchat
Transforms a database into an intelligent conversational partner, enabling natural language queries, instant answers, and data visualizations via MCP clients.
nlp2sql
Converting natural language queries to optimized SQL for enterprise databases using multiple AI providers.