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googyaipro

Blogger Agent MCP

by googyaipro
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Python
Hybrid

🚀 Blogger Agent MCP & AI Content Generation Engine

Blogger Agent MCP is an autonomous multi-agent system based on Google Agent Development Kit (ADK) and Gemini 3.5 Flash, designed for deep trend analysis, live web search for up-to-date facts, automatic construction of multi-point travel routes in Google Maps, writing expert longreads, publishing documents in Google Docs, and distributing them via Gmail.

🌟 Key Features

  • 🧠 Multi-Agent Pipeline (Google ADK & Gemini 3.5 Flash): Use of specialized sub-agents BlogPlanner and BlogWriter under the control of a single orchestrator Root Agent.

  • 🌐 Live Web Search in Real Time (search_web): Grounding facts to the current date to prevent hallucinations and outdated LLM data.

  • 🗺 Grand Tour Router (get_scenic_travel_route): Building complex road trips Point A ➔ B ➔ C ➔ D with generation of clickable interactive maps in Google Maps.

  • 📈 Google Trends Integration: Automatic collection of rising key audience trends.

  • 🔒 Delegated OAuth 2.0 Authorization: Creating files directly on your personal Google Drive (Google Docs API) and sending messages from your personal Gmail (Gmail API).

  • ☁️ Cloud Native & Docker Ready: Ready for instant deployment on Google Cloud Run, Docker, and Dokploy.

Related MCP server: Universal Adapter

🏗 Pipeline Architecture

[Пользовательский Запрос]
        │
        ▼
[Root Agent (Blogger)]
        │
        ├──> 1. Trends Analysis (get_google_trends / pytrends)
        │
        ├──> 2. Live Web Search (search_web / DDGS Grounding)
        │
        ├──> 3. Scenic Route Planner (get_scenic_travel_route / Places & Routes API)
        │
        ├──> 4. Outline Generation (Sub-Agent: BlogPlanner)
        │
        ├──> 5. Full Article Generation (Sub-Agent: BlogWriter)
        │
        └──> 6. Export & Delivery
                 ├── Google Drive / Docs API (save_to_google_drive)
                 ├── Google Cloud Storage Backup (save_to_cloud_storage)
                 └── Gmail API Dispatch (send_article_email)

⚙️ Environment Variables (.env)

Create a .env file in the project root directory:

# Модель и регион Google Cloud Vertex AI
MODEL=gemini-3.5-flash
GOOGLE_CLOUD_LOCATION=global
GOOGLE_GENAI_USE_VERTEXAI=TRUE

# Ключ Google Maps Platform API
GOOGLE_MAPS_API_KEY=AIzaSyYourGoogleMapsApiKeyHere12345

# Хранилище Google Cloud Storage
GCS_BUCKET_NAME=your-gcs-bucket-name

# OAuth 2.0 Desktop Credentials (для личного Google Диска и Gmail)
OAUTH_CLIENT_ID=123456789012-yourclientid.apps.googleusercontent.com
OAUTH_CLIENT_SECRET=GOCSPX-yourClientSecretHere123456
OAUTH_REFRESH_TOKEN=1//04yourRefreshTokenHere_abcdefghijklmnopqrstuvwxyz

# Email для уведомлений
NOTIFICATION_EMAIL=your_email@gmail.com

📦 Quick Installation and Local Launch

1. Clone the Repository and Create venv

git clone https://github.com/your-username/bloggeragentmcp.git
cd bloggeragentmcp

python3 -m venv .venv
source .venv/bin/activate

2. Install Dependencies

pip install -r requirements.txt

3. OAuth 2.0 Authorization (One-Time Launch)

To obtain your long-lived OAUTH_REFRESH_TOKEN, run the authorization script:

python generate_oauth_token.py

Authorize in the opened browser under your Google account and copy the obtained refresh_token into .env.

4. Local Agent Launch

python agent.py

🐳 Deployment in Docker / Dokploy / Cloud Run

1. Launch via Docker Compose

Create docker-compose.yml:

version: '3.8'

services:
  blogger-agent:
    build: .
    container_name: blogger_agent
    restart: always
    ports:
      - "8080:8080"
    env_file:
      - .env

Run the container:

docker compose up -d

2. Deploy to Google Cloud Run

gcloud run deploy bloggeragentmcpv03 \
  --source . \
  --region us-east1 \
  --allow-unauthenticated \
  --set-secrets="OAUTH_REFRESH_TOKEN=oauth-refresh-token:latest" \
  --set-env-vars GOOGLE_GENAI_USE_VERTEXAI=TRUE,MODEL="gemini-3.5-flash",GOOGLE_CLOUD_LOCATION="global",GCS_BUCKET_NAME="your-gcs-bucket-name",NOTIFICATION_EMAIL="your_email@gmail.com"

3. Deploy to Dokploy

  1. Create an Application in the Dokploy panel.

  2. In Build Type, select Dockerfile.

  3. Fill in the variables in the Environment tab.

  4. Click Deploy.

📝 License

MIT License © 2026 Blogger Agent MCP Team.

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