RAG MCP Server (Lambda + OpenSearch Serverless)
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About RAG MCP Server (Lambda + OpenSearch Serverless)
No overview available yet
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"rag-mcp-server": {
"command": "python",
"args": [
"example.py"
]
}
}
}Tools
No tools detected
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Overview
What is RAG MCP Server (Lambda + OpenSearch Serverless)?
It is an MCP (Model Context Protocol) server implementing a RAG (Retrieval-Augmented Generation) system using a serverless AWS architecture. The server integrates AWS Lambda, API Gateway, OpenSearch Serverless, OpenAI, and S3, and is intended for developers building AI agents that need a document retrieval and generation backend.
How to use RAG MCP Server (Lambda + OpenSearch Serverless)?
Deploy the server to your AWS account using the provided Makefile. The typical workflow is: install dependencies (make deps), bootstrap CDK (make bootstrap), create required secrets in AWS Secrets Manager (an OpenAI API key and an application API key), then deploy (make deploy). After deployment, interact with the API using the endpoint URL and the application API key in the X-API-Key header; the server exposes a /mcp endpoint for MCP discovery and execution.
Key features of RAG MCP Server (Lambda + OpenSearch Serverless)
- Serverless RAG server on AWS
- MCP (Model Context Protocol) compatible
- Vector search via OpenSearch Serverless
- Embeddings and generation with OpenAI
- Persistent document storage on S3
- Infrastructure defined with AWS CDK
Use cases of RAG MCP Server (Lambda + OpenSearch Serverless)
- Add documents to a knowledge base for retrieval
- Query the knowledge base with RAG retrieval and generation
- List all stored documents via the API
- Integrate with AI agents using the MCP protocol
- Deploy a production
Basic information
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