Bybit MCP Server: Connecting AI Applications to Bybit's Trading API

Overview: What is Bybit MCP Server?

Bybit MCP Server is a bridge between Bybit's trading platform and machine learning (ML) applications via the Model Context Protocol (MCP). This powerful server enables developers and data scientists to integrate their AI systems with real-time market data, advanced technical indicators, and automated trading functionality. Bybit MCP Server provides a standardized interface that allows AI applications like Claude Desktop, Continue, and Cursor to access Bybit's APIs through MCP, enhancing the capabilities of these platforms for cryptocurrency traders.

🔧 Core Features & MCP Capabilities

Bybit MCP Server offers a wide range of features to support advanced trading strategies. These include real-time market data, technical analysis tools, order management functions, risk management mechanisms, and support/resistance detection. The server is designed to run locally or using Docker, making it easy for developers to deploy and manage.

Real-Time Market Data

Real-time access to current prices, market depth, and historical data facilitates dynamic trading decisions. Bybit MCP Server ensures that AI applications can respond quickly to market changes.

Advanced Technical Analysis

The server supports the calculation of numerous technical indicators such as Relative Strength Index (RSI), Moving Average Convergence Divergence (MACD), Average True Range (ATR), among others, enabling comprehensive analysis for AI-driven trading strategies.

Multi-timeframe Analysis

Analyzing market trends across different timeframes helps in identifying broader and shorter-term trading opportunities. This feature is crucial for developing sophisticated trading algorithms that can adapt to various market conditions.

Automated Trading

AI applications can place, modify, and cancel orders programmatically using the server's API. Automated trading operations ensure seamless execution of complex strategies without manual intervention.

Risk Management

Position sizing recommendations based on volatility help manage risk effectively. The server provides insights into market volatility, allowing AI applications to adjust their trades accordingly.

Support/Resistance Detection

Key price levels can be automatically detected by the server, providing valuable information for better entry and exit points. This feature is essential for building trend-following strategies.

Docker Support

Docker support simplifies deployment with both docker and docker-compose, making it easy to run Bybit MCP Server in containerized environments.

⚙️ MCP Architecture & Protocol Implementation

Bybit MCP Server implements the Model Context Protocol (MCP) as a standard interface for AI applications. The protocol ensures consistent interaction between AI systems and data sources, making it easier to integrate new features and tools into existing workflows.

MCP Protocol Flow Diagram

The following Mermaid diagram illustrates the flow of communication between an AI application, Bybit MCP Server, and external data providers:

graph TD
    A[AI Application] -->|MCP Client| B[MCP Server]
    B --> C[Data Source/Tool]
    style A fill:#e1f5fe
    style C fill:#f3e5f5

MCP Client Compatibility Matrix

The following table outlines the compatibility of Bybit MCP Server with various AI clients:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

🚀 Getting Started with Installation

Local Installation with Virtualenv

1. Clone the repository:

   git clone https://github.com/andrefigueira93/bybit-mcp-server.git
   cd bybit-mcp-server
   

2. Create and activate a virtual environment:

   uv venv
   source .venv/bin/activate
   

3. Install dependencies:

   uv pip install -e .
   

4. Create a .env file with your API credentials:

   BYBIT_API_KEY=your_api_key
   BYBIT_API_SECRET=your_api_secret
   BYBIT_TESTNET=True  # Set to False for production
   

Using Docker

1. Clone the repository:

   git clone https://github.com/andrefigueira93/bybit-mcp-server.git
   cd bybit-mcp-server
   

2. Create a .env file with your API credentials (as above):

3. Build and run with Docker Compose:

   docker-compose build
   docker-compose up -d
   

💡 Key Use Cases in AI Workflows

Bybit MCP Server offers several key use cases for integrating AI applications into cryptocurrency trading workflows:

Use Case 1: Real-time Market Analysis and Automated Trading

Developers can create an AI application that connects to the Bybit MCP Server through MCP. The server provides real-time market data, which the AI application uses to execute automated trades based on predefined criteria. For example, a trading bot could monitor price movements in several indicators and place buy/sell orders when specific thresholds are met.

Use Case 2: Multi-timeframe Analysis for Trend Following

An AI application can use Bybit MCP Server to perform technical analysis across multiple timeframes. This helps the application identify trends that persist across different scales, providing more robust signals for long-term trading decisions. The server's multi-timeframe capability ensures that the AI application receives accurate and timely data from various sources.

🔌 Integration with MCP Clients

Bybit MCP Server is compatible with several popular MCP clients:

1. Claude Desktop: Complete support for resources, tools, and prompts.
2. Continue: Full integration with all features except prompts.
3. Cursor: Supports resource management but lacks tool implementation.

Example MPC Request with Bybit MCP Server

# Example of using the MCP client to get a market analysis
analysis = mcp_client.call("analyze_market", symbol="BTCUSDT", intervalo="60")
print(analysis)

# Example of placing a market order
order = mcp_client.call("place_order",
                       symbol="BTCUSDT",
                       side="Buy",
                       order_type="Market",
                       qty=0.001,
                       stop_loss=25000)
print(order)

📊 Performance & Compatibility Matrix

Bybit MCP Server is designed to work seamlessly with various AI applications and tools, as shown in the following compatibility matrix:

Tool	Bybit Data Source Integration	API Support	Technical Analysis Tools	Real-time Trading Capabilities
Claude Desktop	✅	✅	✅	✅
Continue	✅	✅	✅	✅
Cursor	❌	✅	❌	❌

🛠️ Advanced Configuration & Security

Environmental Variables

The following environmental variables are required for Bybit MCP Server operation:

• BYBIT_API_KEY: API key for Bybit
• BYBIT_API_SECRET: API secret for Bybit
• BYBIT_TESTNET: Whether to use testnet (True) or mainnet (False)

By configuring these variables correctly, developers can ensure secure and reliable access to the Bybit trading platform.

MCP Configuration Sample

A sample configuration snippet for integrating Bybit MCP Server into your AI application:

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-bybit"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

Q1: How does Bybit MCP Server ensure data privacy and security?

Bybit MCP Server adheres to strict security protocols, including API key management and secure authentication. Developers should always use HTTPS for all communication to further enhance data protection.

Q2: What are the system requirements for running Bybit MCP Server locally?

The minimum system requirements include Python 3.12+, an active internet connection, and a Docker environment (optional).

Q3: Can Bybit MCP Server be used in testnet mode only?

Yes, you can run Bybit MCP Server in testnet mode by setting BYBIT_TESTNET=True in your .env file. This allows developers to thoroughly test their AI applications before going live.

Q4: How does the server handle API rate limits from Bybit?

The server is designed with built-in rate limiting to prevent hitting Bybit's API throttle limits. However, it is recommended that users monitor usage and adjust as necessary to avoid potential restrictions or bans.

Q5: What are the performance implications of running multiple MCP clients simultaneously?

Running multiple MCP clients can impact overall system performance if not managed properly. It is advisable to optimize resource allocation and manage client connections efficiently to ensure smooth operation.

👨‍💻 Development & Contribution Guidelines

Contributions to Bybit MCP Server are welcome! To contribute, follow these steps:

1. Fork the repository:

   git clone https://github.com/andrefigueira93/bybit-mcp-server.git
   cd bybit-mcp-server
   

2. Create a feature branch:

   git checkout -b feature/new-feature
   

3. Make your changes and commit them:

   git commit -m 'Add new feature'
   

4. Push the branch to GitHub:

   git push origin feature/new-feature
   

5. Open a pull request (PR) on the main repository.

Conclusion

Bybit MCP Server represents a robust solution for integrating AI applications with Bybit's trading platform through the Model Context Protocol. Its comprehensive set of features, including real-time data access, advanced technical analysis, and automated trading capabilities, makes it an invaluable asset for cryptocurrency traders and developers alike. By following best practices and understanding the implementation details, users can leverage this powerful server to develop sophisticated AI-driven trading strategies with ease.