Alibaba Cloud Tablestore MCP Server provides a Model Context Protocol implementation for interacting with Alibaba Cloud's Tablestore service. It enables AI applications to leverage Tablestore's vector database capabilities for retrieval augmented generation (RAG) and knowledge base applications. The server comes with both Java and Python implementations, making it accessible for developers working in either language ecosystem.
Alibaba Cloud Tablestore MCP Server provides a Model Context Protocol implementation for interacting with Alibaba Cloud's Tablestore service, particularly for vector search and retrieval augmented generation (RAG) applications.
This MCP server allows AI applications to connect to Alibaba Cloud Tablestore, a fully managed NoSQL database service that supports vector search capabilities. The repository provides implementations in both Java and Python, with examples for basic usage and more advanced RAG applications.
To use the Alibaba Cloud Tablestore MCP Server, you'll need to:
git clone https://github.com/aliyun/alibabacloud-tablestore-mcp-server.git
Choose either the Java or Python implementation based on your preference:
tablestore-java-mcp-server
or tablestore-java-mcp-server-rag
tablestore-python-mcp-server
Follow the setup instructions in the respective README files for your chosen implementation.
Configure your Alibaba Cloud Tablestore credentials and endpoint in the server configuration.
The Java implementation offers two options:
tablestore-java-mcp-server
- A starter implementation for connecting to Tablestore.tablestore-java-mcp-server-rag
- A more advanced implementation that builds a knowledge base question-answering system with optimizations for knowledge base construction and RAG.The Python implementation (tablestore-python-mcp-server
) provides a basic example for connecting to Tablestore using Python.
Each implementation requires configuration of your Alibaba Cloud Tablestore credentials:
Refer to the specific README files in each implementation directory for detailed configuration instructions.
For technical support or to discuss AI technology with the developers, you can join their DingTalk public group: 36165029092.