eGov MCP — Cameroun

AI-native eGovernment platform for Cameroonian public services, built with MCP (Model Context Protocol).

Live Demo

Service	URL
Frontend	https://egov-mcp.vercel.app
Backend API	https://egov-mcp-backend.onrender.com
API Docs	https://egov-mcp-backend.onrender.com/docs

Architecture

React Frontend (MCP Client) ↓ HTTP FastAPI MCP Server ↓ Tool Execution Government APIs (Open Data Cameroun, DGI, CNPS logic) ↑ Orchestration Groq / Llama 3.3 70B

MCP Tools

Tool	Description	Data Source
get_tax_calendar	Tax deadlines DGI Cameroun	Business logic (CGI)
validate_cnps_number	CNPS registration validation	Format + region logic
calculate_social_contributions	CNPS + IRPP calculation	Official rates
search_companies	Company search	Open Data Cameroun
get_public_datasets	Public datasets	data.gouv.cm

Setup Local

Prerequisites

• Python 3.11
• Node.js 18+
• Groq API key (free at console.groq.com)

Backend

cd backend
python -m venv .venv
source .venv/Scripts/activate  # Windows
pip install -r requirements.txt
cp .env.example .env
# Add your GROQ_API_KEY in .env
uvicorn app.main:app --reload

Frontend

cd frontend
npm install
echo "VITE_API_URL=http://127.0.0.1:8000" > .env
npm run dev

Docker

docker-compose up

Deployment

Service	Platform	Config
Backend	Render (free tier)	render.yaml
Frontend	Vercel (free tier)	Auto-detected Vite

Testing

cd backend
python -m pytest tests/ -v
# 14/14 tests passing

Tech Stack

Backend: Python 3.11 · FastAPI · Pydantic v2 · Groq SDK · httpx Frontend: React 18 · TypeScript · Tailwind CSS · Vite LLM: Llama 3.3 70B via Groq DevOps: Docker · GitHub Actions · Render · Vercel

Repository Structure

egov-mcp/ ├── backend/ │ ├── app/ │ │ ├── main.py # FastAPI + MCP orchestration │ │ ├── config.py # Settings │ │ ├── tools/ # 5 MCP tools │ │ ├── schemas/ # Pydantic models │ │ └── core/ # Auth + logging │ └── tests/ # 14 unit tests ├── frontend/ │ └── src/ │ ├── components/ # React components │ ├── hooks/ # useChat hook │ └── types/ # TypeScript types ├── docker-compose.yml └── .github/workflows/ci.yml

Assumptions & Tradeoffs

Groq instead of Anthropic/OpenAI: Groq offers a truly free tier with no credit card required, which is practical for this assessment. The tradeoff is that Llama 3.3 has slightly less reliable tool-calling than Claude Sonnet, requiring a more explicit system prompt.

CNPS/DGI without official API: Neither CNPS nor DGI Cameroun expose public APIs. The tools implement real business logic (official CNPS rates, real DGI tax calendar from CGI) rather than mock data. This is disclosed transparently.

Monorepo: Single repository simplifies CI/CD and submission. For a production system with multiple teams, a multi-repo or Turborepo setup would be preferable.

Future Improvements

• Add Redis caching for Open Data API responses
• Implement user authentication (JWT)
• Add support for document upload (DSF, liasse fiscale)
• Migrate to Claude Sonnet for more reliable tool orchestration
• Add WebSocket support for streaming responses
• Integrate real CNPS and DGI APIs when they become available

AI Tools Used

• Claude (Anthropic): Architecture design, code generation, debugging
• Prompts used: Available in PROMPTS.md

License

MIT