RAG MCP Server (Lambda + OpenSearch Serverless)

Name: RAG MCP Server (Lambda + OpenSearch Serverless)
Author: 0x00000002

@0x00000002

代码仓库

基本信息

分类

记忆与知识

传输方式

stdio

作者

0x00000002

关于 RAG MCP Server

暂无概览

RAG MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "rag-mcp-server": {
      "command": "python",
      "args": [
        "example.py"
      ]
    }
  }
}

RAG MCP Server 工具

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工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

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

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