韩国투자증권 REST API로 국내외 주식 거래와 실시간 시세 조회 가능
The KIS REST API MCP (Model Context Protocol) Server is a robust and scalable infrastructure designed to enable AI applications, such as Claude Desktop, Continue, Cursor, and others, to connect with Korean Investment & Securities (KIS) data sources. This server facilitates the integration of diverse financial services into AI workflows by adopting a standardized Model Context Protocol (MCP), ensuring seamless interaction between applications and KIS APIs.
The KIS REST API MCP Server offers several key features that enhance compatibility, reliability, and performance in financial trading. These core capabilities are crucial for integrating AI applications with KIS data sources and tools:
Realistic Financial Trading Functions: The KIS REST API MCP Server supports domestic stock trading, including real-time price inquiries, order execution, balance reporting, trade history, and market quote information. It also covers overseas stock trading in major markets, such as the United States, Japan, China, Hong Kong, and Vietnam.
Asynchronous Processing: The server is designed with asynchronous processing to ensure fast response times and efficient handling of API requests.
Real-Time Data Access: The KIS REST API MCP Server provides real-time market data and execution information, making it ideal for AI applications that require up-to-date financial insights.
Secure Error Handling: The implementation includes robust error management systems, ensuring both reliable operation and user-friendly feedback mechanisms.
Scalability: The modular design supports easy expansion to accommodate additional data sources or tools in the future, making it a flexible choice for diverse AI applications.
The KIS REST API MCP Server is built on the Model Context Protocol (MCP), which serves as a standard interface between AI applications and diverse data sources. By leveraging MCP, the server can seamlessly interact with various tools and resources provided by Korean Investment & Securities.
Below is a Mermaid diagram illustrating the flow of communication between an AI application, the KIS REST API MCP Server, and the underlying financial data source.
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[MCP Server]
C --> D[Data Source/Tool]
The compatibility matrix below highlights which AI applications can be fully integrated with the KIS REST API MCP Server using the Model Context Protocol (MCP).
MCP Client | Resources | Tools | Prompts | Status |
---|---|---|---|---|
Claude Desktop | ✅ | ✅ | ✅ | Full Support |
Continue | ✅ | ✅ | ✅ | Full Support |
Cursor | ❌ | ✅ | ❌ | Tools Only |
The shaded resources and tools indicate full or partial support, helping developers choose the best MCP client for their integration needs.
To get started, follow these steps to install and configure the KIS REST API MCP Server on your development environment:
Install uv: Use pip
to install the required packaging tool.
pip install uv
Create a Virtual Environment: Utilize uv
to create and activate a virtual environment.
On Linux or macOS:
uv venv
source .venv/bin/activate
On Windows:
.\venv\Scripts\activate
Install Dependencies: Install the dependencies within your virtual environment.
uv pip install -e .
Set Environment Variables: Define essential API credentials and account information.
export KIS_APP_KEY="your-api-key"
export KIS_APP_SECRET="your-secret-key"
export KIS_ACCOUNT_TYPE="VIRTUAL" # or "REAL"
export KIS_CANO="your-account-number"
In this use case, an AI application like Claude Desktop uses the KIS REST API MCP Server to fetch real-time market data and analyze stock prices. The server ensures that the data is up-to-date, allowing the AI to make accurate predictions or trading recommendations.
The KIS REST API MCP Server enables Continue to execute automated trading strategies by providing it with the necessary tools for order placement, balance management, and trade history lookup. This integration allows the application to interact seamlessly with financial markets and perform complex trading operations based on AI-driven decisions.
To integrate the KIS REST API MCP Server with various AI applications, developers need to ensure compatibility through proper setup and configuration. Key components include:
The performance matrix provides a detailed comparison of the KIS REST API MCP Server's compatibility with different AI applications:
Capability | Claude Desktop | Continue | Cursor |
---|---|---|---|
Real-Time Data Access | ✅ | ✅ | ❌ |
Order Execution | ✅ | ✅ | ❌ |
Balance Reporting | ✅ | ✅ | ❌ |
This matrix helps developers understand the extent of support and choose the most suitable AI application for their needs.
For advanced users, the KIS REST API MCP Server offers flexible configuration options to tailor the server's behavior. Key points include:
Here is an example of how to configure the KIS REST API MCP Server with a JSON configuration file:
{
"mcpServers": {
"KisApiServer": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-kis-api"],
"env": {
"KIS_APP_KEY": "your-api-key",
"KIS_APP_SECRET": "your-secret-key",
"KIS_ACCOUNT_TYPE": "VIRTUAL",
"KIS_CANO": "123456789"
}
}
},
While the provided compatibility matrix covers well-known AI applications, users can still integrate the server with other MCP clients by following similar setup procedures.
Communication should be secured using proper authentication methods and encryption protocols to protect sensitive data transferred between both parties.
The server can run on any modern Linux or Windows machine with a compatible Python version. Ensure that all necessary dependencies are installed and configured correctly.
For automated trading, the server supports real-time order execution, balance reporting, and market data access, enabling comprehensive support for complex trading strategies.
By adopting MCP, developers can leverage a standardized interface that simplifies integration with financial data sources, enhancing both performance and ease of use.
This transformation positions the KIS REST API MCP Server as a vital tool for developers working with AI applications, offering seamless financial data access and robust integration capabilities.
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