eGov MCP — Cameroun
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., "@eGov MCP — CamerounShow me the tax calendar for this quarter."
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.
eGov MCP — Cameroun
AI-native eGovernment platform for Cameroonian public services, built with MCP (Model Context Protocol).
Live Demo
Service | URL |
Frontend | |
Backend API | |
API Docs |
Related MCP server: ODIADEV MCP Server
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 |
| Tax deadlines DGI Cameroun | Business logic (CGI) |
| CNPS registration validation | Format + region logic |
| CNPS + IRPP calculation | Official rates |
| Company search | Open Data Cameroun |
| 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 --reloadFrontend
cd frontend
npm install
echo "VITE_API_URL=http://127.0.0.1:8000" > .env
npm run devDocker
docker-compose upDeployment
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 passingTech 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
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