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., "@MoluAbi MCP Server create an AI assistant for customer support with access to our knowledge base"
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.
Production-ready Model Context Protocol server for AI agent management
This is a standalone Model Context Protocol (MCP) server that provides programmatic access to MoluAbi's AI agent management platform. It offers 10 comprehensive tools for creating, managing, and interacting with AI assistants through a secure, payment-aware architecture.
This MCP server enables complete AI agent lifecycle management:
Create agents with custom instructions and capabilities
Manage permissions with granular access control
Real-time interaction with AI assistants
Usage tracking and billing integration
Payment abstraction supporting multiple billing models
Database integration with PostgreSQL
Security validation and user authentication
Related MCP server: AppsAI MCP Server
Node.js 18+ installed
PostgreSQL database (existing MoluAbi schema)
Environment variables configured
# Clone or copy this directory
cd mcp-server
# Install dependencies
npm install
# Set up environment
cp .env.example .env
# Edit .env with your configuration
# Build the server
npm run buildThis server cannot be deployed
Create and manage AI agents that collaborate and solve problems through natural language interacti…
AI agent platform: manage leads, conversations, bots, calendar and CRM via MCP.
Backend platform for AI agents: one agentstack.execute tool runs batched steps over +700 actions (hosting, storage, auth, payments, CRM, app builder).
Build, validate, and deploy multi-agent AI solutions from any AI environment.
