RAG MCP Server (Lambda + OpenSearch Serverless)
@0x00000002
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
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
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
More Memory & Knowledge MCP servers
MCP server for Obsidian
MarkusPfundsteinMCP server that interacts with Obsidian via the Obsidian rest API community plugin
minutes
silversteinEvery meeting, every idea, every voice note — searchable by your AI. Open-source, privacy-first conversation memory layer.

PLUR
plur-aiAI agents start every session with amnesia — you re-explain the project, repeat your preferences, and correct the same mistakes over and over. PLUR gives them a memory that persists. Your agent's corrections, preference
MemoryMesh
CheMiguel23A knowledge graph server that uses the Model Context Protocol (MCP) to provide structured memory persistence for AI models.
Mcp Knowledge Graph
shanehollomanMCP server enabling persistent memory for Claude through a local knowledge graph - fork focused on local development
Comments