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., "@Agentic AI System MCP Serverdeploy a customer support agent 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.
MCP-Based Agentic AI System
Production-ready, self-hosted AI infrastructure with Model Context Protocol.
Quick Start
Install Dependencies
pip install -r requirements.txtConfigure Environment
cp .env.example .env
Edit .env with your configurationInitialize Database
python scripts/init_db.pyStart Services
Start MCP Server
python -m server.mcp_server
Start API Server (in new terminal)
python -m api.mainTest the System
pytest tests/Architecture
MCP Server: WebSocket-based protocol server
REST API: FastAPI application for HTTP access
Agent System: Autonomous AI agents with memory
Tool Registry: Extensible function execution
State Management: Redis + PostgreSQL persistence
API Documentation
Once running, visit: http://localhost:8000/docs
Configuration
All settings managed through environment variables:
Database: PostgreSQL connection
Redis: Caching and sessions
LLM: Model provider and settings
Security: JWT tokens and CORS
Deployment
Docker
docker-compose up -dKubernetes
kubectl apply -f kubernetes/Monitoring
Prometheus metrics available at :9090/metrics
Support
For issues and questions, see docs/ directory.
This server cannot be installed
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.