Druling MCP Server

Install all dependencies

• Run pip install -r requirements-dev.txt

Related MCP server: Artificial Virtual Assistant (AVA)

How to run app using Docker with PostgreSQL

• Install Docker Desktop

• Run docker compose up --build

• Run docker compose down to stop all services

How to run locally without postgres or docker

• In database/core.py change the DATABASE_URL to sqlite

• Run make run

How to run tests

• Run pytest to run all tests

How to Add a New MCP Server

MCP (Model Context Protocol) servers provide tools and prompts for AI integrations. Follow these steps to add a new MCP server:

Step 1: Create the MCP Server Directory

Create a new directory under src/servers/ for your MCP server:

src/servers/<provider>/<service>/
    __init__.py
    mcp.py
    outputs.py
    prompts.py

For example, to add a new "calendar" service under Google:

src/servers/google/calendar/
    __init__.py
    mcp.py
    outputs.py
    prompts.py

Step 2: Define Output Models (outputs.py)

Create Pydantic models for your tool outputs:

Step 3: Define Prompts (prompts.py)

Create prompts for your MCP server (optional):

Step 4: Create the MCP Server (mcp.py)

Create the MCP server class by extending BaseMCPServer:

Step 5: Register the MCP Server

Update src/setup/mcp.py to register your new MCP server:

from src.servers.google.calendar.mcp import CalendarMCPServer

# Add to existing imports and initializations
calendar_server = CalendarMCPServer()

MCP_PATH = {
    # ...existing servers...
    "calendar": calendar_server,
}

The server will automatically:

• Be mounted at /<server_name> (e.g., /calendar)

• Have session management handled by the lifespan context

• Include authentication and context middleware

How to Add a New REST API

REST APIs are used for standard HTTP endpoints. Follow these steps to add a new API:

Step 1: Create the API Directory

Create a new directory under src/app/ for your API:

src/app/<feature>/
    __init__.py
    api.py

For example, to add a "users" API:

src/app/users/
    __init__.py
    api.py

Step 2: Create the API Router (api.py)

Create the FastAPI router with your endpoints:

Step 3: Register the API Router

Update src/setup/api.py to include your new router:

Project Structure Overview

src/
├── main.py                 # FastAPI app entry point
├── setup/
│   ├── api.py              # REST API route registration
│   └── mcp.py              # MCP server registration
├── app/                    # REST API endpoints
│   ├── health_check/
│   ├── auth/
│   └── <your_api>/
├── servers/                # MCP servers
│   ├── google/
│   │   ├── gmail/
│   │   ├── drive/
│   │   └── <your_service>/
│   ├── druling/
│   └── <your_provider>/
├── core/
│   ├── service/            # Base MCP server class
│   ├── middleware/         # Auth and context middleware
│   ├── exceptions/         # Custom exceptions
│   └── utils/              # Utility functions
└── clients/
    └── backend/            # Backend API client

Key Concepts

MCP Server

• Extends BaseMCPServer from src.core.service

• Provides tools (functions) and prompts for AI agents

• Uses @self._mcp.tool() decorator to register tools

• Uses mcp_meta() for tool metadata

• Access user context via self.get_context()

REST API

• Uses FastAPI's APIRouter

• Registered via app.include_router()

• Standard REST conventions with proper status codes

Backend Client

• Use BackendClient from src.clients.backend.client to call backend services

• Supports get(), post(), put(), delete() methods

• Pass context for authenticated requests