Chatbot Assistant with Gemini + gRPC
LocalAbout Chatbot Assistant with Gemini + gRPC
A Python chatbot backend that uses the Google Gemini API and gRPC, with context maintained per session. It is for developers building conversational services with a modular client, server, and inference engine.
Key features
- 01gRPC client-server communication
- 02Google Gemini API integration
- 03Per-session conversation context
- 04Modular client and inference engine
Use cases
- 01Building a Gemini chatbot backend
- 02Maintaining context across conversation turns
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEChatbot Assistant with Gemini + gRPC
This project is a simple chatbot backend powered by Google's Gemini API and uses gRPC for client-server communication. It maintains context per session and provides interactive conversational experiences.
Architecture

Features
- gRPC-based communication
- Google Gemini API integration
- Session-based context management
- Clean modular design (client, server, context manager, inference engine)
📂 Project Structure
assistant_backend/
│
├── assets/
│ └── image.png # (Optional) Image asset
│
├── protos/
│ └── (Protobuf files for gRPC definitions)
│
├── assistant_pb2.py # Generated from .proto
├── assistant_pb2_grpc.py # Generated from .proto
├── client.py # gRPC client
├── server.py # gRPC server with Gemini integration
├── context_manager.py # Manages chat context per session
├── inference_engine.py # Contains the logic to generate a reply
├── requirements.txt # Python dependencies
└── .env # Gemini API Key
1. Install Dependencies
pip install -r requirements.txt
2. Set Up Environment
Create a .env file with your Gemini API key:
GEMINI_API=your_api_key_here
3. Run the Server
python server.py
4. Run the Client
python client.py
Example Usage
Type 'exit' to stop chatting.
You: Hello
AI: I received: Hello. Previous context: 0 messages.
Notes
- Ensure your
.protofiles are compiled toassistant_pb2.pyandassistant_pb2_grpc.py - Python version 3.10 or higher is recommended
Built With
- Python
- gRPC
- Google Gemini API
- dotenv
© 2025 Om Jamnekar. All rights reserved.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.