About Zerodha MCP Server & Client
A Python trading assistant that connects to a Zerodha MCP server to manage orders, positions and margins through natural language. It ships with Agno and Google ADK agent clients plus a command line and Gradio web interface.
Key features
- 01Place, modify, cancel and query orders
- 02Query holdings, positions and margins
- 03Agno agent client
- 04Google ADK agent client
- 05Gradio web chat interface
Use cases
- 01Querying Zerodha holdings and margins in natural language
- 02Placing or cancelling stock orders from a chat interface
- 03Comparing Agno and Google ADK client implementations
MCP support
The project includes both an MCP server and MCP clients. The server wraps Zerodha API operations as tools, and the clients connect to it over SSE or stdio to call them.
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 READMEZerodha MCP Server & Client
A Python-based trading assistant that connects to a Zerodha MCP server to help users manage their trading account.
Features
- Account Management: Manage Zerodha trading account, orders, and positions
- Interactive Chat Interface: Natural language interface for trading operations
- MCP Integration: Built on the Model Context Protocol for standardized communication
- Zerodha API Integration: Uses Zerodha's API to interact with the trading platform
- Agno Agent: Uses Agno Agent to interact with the trading platform
- Google ADK Agent: Uses Google ADK Agent to interact with the trading platform
Tech Stack
- Protocol: Model Context Protocol (MCP)
- Agent Framework:
Tools
- Place Orders: Place orders in the trading platform
- Modify Orders: Modify orders in the trading platform
- Cancel Orders: Cancel orders in the trading platform
- Get Orders: Get orders in the trading platform
- Get Order History: Get order history in the trading platform
- Get Order Trades: Get order trades in the trading platform
- Get Margins: Get margins in the trading platform
- Get Holdings: Get holdings in the trading platform
- Get Positions: Get positions in the trading platform
- Get User Profile: Get user profile in the trading platform
Prerequisites
- Python
- Zerodha trading account with Personal API access from here
- Zerodha API key and secret
- OpenAI API key (for Agno Agent)
- Gemini API key or Application Default Credentials (for Google ADK Agent)
Installation
- Clone the repository:
git clone https://github.com/mtwn105/zerodha-mcp-server-client.git
cd zerodha-mcp-server-client
- Create and activate a virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Set up environment variables:
# Copy the example environment file
cp .env.example .env
# Edit the .env file with your credentials
- Create a
.envfile with your configuration:
# Server Configuration
ZERODHA_API_KEY=your_api_key
ZERODHA_API_SECRET=your_api_secret
PORT=8001
SERVER_MODE=sse # or stdio
# Client Configuration
MCP_HOST=localhost
MCP_PORT=8001
OPENAI_API_KEY=your_openai_api_key
# GOOGLE_API_KEY=your_google_api_key
Server Usage
The server provides a set of tools for interacting with the Zerodha trading platform. To start the server:
-
Make sure your
.envfile is properly configured with your Zerodha API credentials. -
Start the server using one of the following methods:
# Using environment variables
python server.py
# Or using command line arguments
python server.py --api-key your_api_key --api-secret your_api_secret --port 8001 --mode sse
The server provides the following tools:
get_login_url: Get the login URL for user authenticationget_access_token: Generate access token using request tokenget_user_profile: Get user's Zerodha profile informationget_margins: Get available margins and fund detailsget_holdings: Get portfolio holdingsget_positions: Get current positionsget_orders: Get all orders for the dayget_order_history: Get history of a specific orderget_order_trades: Get trades generated by an orderplace_order: Place a new ordermodify_order: Modify an existing ordercancel_order: Cancel an order
Client Usage
This project provides three client implementations:
- Using the Agno framework (
client/agno_client.py) - Using Agno with Gradio web interface (
client/agno_gradio_client.py) - Using Google ADK (
client/google_adk_client.py)
All clients connect to the MCP server and provide an interactive interface for trading operations.
Running the Agno Client
- Ensure your
.envfile includesOPENAI_API_KEY. - Start the client using one of the following methods:
# Using environment variables from .env file
python client/agno_client.py
# Using command line arguments
python client/agno_client.py --host localhost --port 8001
# Using a combination (command line arguments take precedence)
MCP_HOST=localhost MCP_PORT=8001 python client/agno_client.py --host otherhost --port 9000
Running the Google ADK Client
- Ensure you have authenticated with Google AI, either by setting the
GOOGLE_API_KEYenvironment variable (and uncommenting it in.env) or by using Application Default Credentials (rungcloud auth application-default login). - Start the client using one of the following methods:
# Using environment variables from .env file
python client/google_adk_client.py
# Using command line arguments
python client/google_adk_client.py --host localhost --port 8001
# Using a combination (command line arguments take precedence)
MCP_HOST=localhost MCP_PORT=8001 python client/google_adk_client.py --host otherhost --port 9000
Running the Gradio Web Interface
- Ensure your
.envfile includesOPENAI_API_KEY. - Start the Gradio web interface:
# Using environment variables from .env file
python client/agno_gradio_client.py
# Using command line arguments for server configuration
python client/agno_gradio_client.py --host localhost --port 8001
-
Open your web browser and navigate to the URL shown in the terminal (typically
http://localhost:7860). -
Use the web interface to:
- Connect to the MCP server by entering the host and port
- Chat with the AI assistant using natural language
- Manage your Zerodha account through a user-friendly interface
The Gradio interface provides:
- Easy connection management with host/port configuration
- Real-time chat interface with the AI assistant
- Visual feedback for connection status
- Mobile-friendly responsive design
Client Configuration
Both clients support configuration through multiple sources, with the following precedence:
- Command-line arguments (highest precedence)
- Environment variables
.envfile variables
Configuration options:
- Environment variables:
MCP_HOSTandMCP_PORT - Command-line arguments:
--hostand--port .envfile variables:MCP_HOST,MCP_PORT,OPENAI_API_KEY, andGOOGLE_API_KEY
Default values (if no configuration is provided):
- Host: localhost
- Port: 8001
The client automatically loads environment variables from the .env file in the project root directory. Make sure your .env file contains the necessary configuration:
# Client Configuration
MCP_HOST=localhost
MCP_PORT=8001
OPENAI_API_KEY=your_openai_api_key
# GOOGLE_API_KEY=your_google_api_key
-
The client will automatically connect to the MCP server using the provided configuration.
-
Once connected, you can interact with the assistant using natural language commands. For example:
- "Show me my portfolio holdings"
- "What are my current positions?"
- "Place a market order for 10 shares of RELIANCE"
- "Cancel order ID 123456"
-
To exit the client, type 'quit' when prompted.
Development
Project Structure
client/agno_client.py: MCP client implementation using Agnoclient/google_adk_client.py: MCP client implementation using Google ADKclient/agno_gradio_client.py: Web interface using Gradio and Agnoserver.py: MCP server implementation with Zerodha API integrationgenerate_token.py: Utility for generating access tokensrequirements.txt: Project dependencies.env: Environment configuration
Contributing
- Fork the repository
- Create a feature branch
- Commit your changes
- Push to the branch
- Create a Pull Request
License
This project is licensed under the Apache License 2.0 - see the LICENSE file for details.
Acknowledgments
- Built using Agno
- Built using Google ADK
- Uses MCP for standardized communication
- Powered by KiteConnect for Zerodha API integration
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.