Agentflow Productivity Assistant

Overview

AgentFlow — A multi-agent AI productivity assistant built with Google ADK and MCP. Coordinates sub-agents to manage tasks, schedules, and notes. Deployed on Google Cloud Run.

Architecture

Browser / UI
     │   HTTP
     ▼
FastAPI app
     │
     ├──▶ Database — PostgreSQL
     └──▶ External services — Google Gemini

Tech Stack

• Language: Python
• Backend: FastAPI
• Database: PostgreSQL
• Integrations: Google Gemini
• Deployment: Docker container

Getting Started

Prerequisites

• Python 3.10+
• Docker (optional, for container runs)

1. Clone

git clone https://github.com/SabarishR08/agentflow-productivity-assistant.git
cd agentflow-productivity-assistant

2. Install dependencies

python -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r requirements.txt

3. Configure environment

cp .env.example .env   # then fill in values

Environment variables used: ENV, DATABASE_URL, GOOGLE_API_KEY, GEMINI_MODEL, MCP_TODOIST_URL, MCP_TODOIST_TOKEN, TODOIST_API_TOKEN, MCP_CALENDAR_URL, MCP_CALENDAR_TOKEN, PORT.

External services involved: Google Gemini.

4. Run

python main.py

(Alternative) Run with Docker

docker build -t agentflow-productivity-assistant .
docker run -p 5000:5000 agentflow-productivity-assistant

---

Overview

AgentFlow — A multi-agent AI productivity assistant built with Google ADK and MCP. Coordinates sub-agents to manage tasks, schedules, and notes. Deployed on Google Cloud Run.

Architecture

Browser / UI
     │   HTTP
     ▼
FastAPI app
     │
     ├──▶ Database — PostgreSQL
     └──▶ External services — Google Gemini

Tech Stack

• Language: Python
• Backend: FastAPI
• Database: PostgreSQL
• Integrations: Google Gemini
• Deployment: Docker container

Getting Started

Prerequisites

• Python 3.10+
• Docker (optional, for container runs)

1. Clone

git clone https://github.com/SabarishR08/agentflow-productivity-assistant.git
cd agentflow-productivity-assistant

2. Install dependencies

python -m venv .venv
source .venv/bin/activate   # Windows: .venv\Scripts\activate
pip install -r requirements.txt

3. Configure environment

cp .env.example .env   # then fill in values

Environment variables used: ENV, DATABASE_URL, GOOGLE_API_KEY, GEMINI_MODEL, MCP_TODOIST_URL, MCP_TODOIST_TOKEN, TODOIST_API_TOKEN, MCP_CALENDAR_URL, MCP_CALENDAR_TOKEN, PORT.

External services involved: Google Gemini.

4. Run

python main.py

(Alternative) Run with Docker

docker build -t agentflow-productivity-assistant .
docker run -p 5000:5000 agentflow-productivity-assistant

Project Structure

agentflow-productivity-assistant/
├── Dockerfile
├── README.md
├── agentflow-frontend.html
├── agents/
├── cloudbuild.yaml
├── db/
├── main.py
├── mcp/
├── models/
├── orchestrator/
├── requirements.txt
├── tests/
├── tools/

Deployment

Containerized via Dockerfile — deployable to any container platform (Render, Railway, Cloud Run, …).

License

Apache-2.0 — © 2026 Sabarish R.

---

License

Apache-2.0 — © 2026 Sabarish R.