Alibaba Cloud OpenSearch MCP Server

Your AI agents just got enterprise-grade search capabilities. This MCP server bridges the gap between AI workflows and Alibaba Cloud's OpenSearch platform, giving you both traditional full-text search and vector search through a single, standardized interface.

Why This Matters for Your AI Stack

Building AI applications that need to search through enterprise data usually means wrestling with multiple APIs, custom integrations, and inconsistent interfaces. You're either limited to basic vector databases or spending weeks building custom connectors to enterprise search platforms.

This MCP server solves that integration headache. Instead of building yet another custom search adapter, you get immediate access to Alibaba Cloud's enterprise-grade search infrastructure through the standardized MCP protocol that your AI agents already understand.

What You Get

Dual Search Capabilities: Both traditional full-text search and modern vector search in one package. Perfect for hybrid RAG setups where you need semantic similarity alongside keyword matching.

Enterprise Infrastructure: Built on Alibaba Cloud's search platform, so you get the reliability, scaling, and security that enterprise applications demand - not another experimental vector database.

Standardized Integration: Your LangChain, Semantic Kernel, or custom AI agents can discover and use these search capabilities automatically through the MCP interface. No custom integration code required.

Production Ready: This isn't a proof-of-concept - it's officially maintained by Alibaba Cloud with proper authentication, error handling, and documentation.

Real-World Applications

Customer Support AI: Your support agents can search both your knowledge base (full-text) and find similar past issues (vector search) in a single query. The AI gets context from both search modes without you building separate integrations.

Document Intelligence: Process legal contracts, technical documentation, or research papers where you need both exact phrase matching and conceptual similarity search. One MCP server handles both search patterns.

Enterprise RAG Systems: Build retrieval systems that can fall back from vector search to keyword search when embeddings don't capture domain-specific terminology, all through the same interface your AI agent expects.

Integration Workflow

Add this to your MCP-compatible AI framework and you immediately get four core tools:

• search_documents - Query across your indexed content
• get_document - Retrieve specific documents by ID
• put_document - Index new content from your AI workflows
• delete_document - Clean up outdated information

Your AI agents can now read from, write to, and search your enterprise content without you writing a single line of custom integration code.

Getting Started

The setup is straightforward if you're already using Alibaba Cloud:

git clone https://github.com/aliyun/alibabacloud-opensearch-mcp-server.git
cd alibabacloud-opensearch-mcp-server
pip install -r requirements.txt

Set your Alibaba Cloud credentials and OpenSearch endpoint, start the server, and your MCP-compatible AI tools will auto-discover the search capabilities.

If you're building AI applications that need to search through real enterprise data - not just toy examples - this gives you production-grade search infrastructure without the integration overhead. Your AI agents get powerful search tools, and you get to focus on building intelligence instead of fighting with APIs.