Search, chat, upload, and scrape a serverless RAGStack knowledge base on AWS.
Runs on your machine from its package; the steps are below.
At most: only reads or looks up information.
Odel charges nothing per call. The publisher may charge for its own service.
Runs locally over stdio
This server isn't hosted — your MCP client launches it from a package registry. Use one of the commands below, or drop the config into your client (e.g. Claude Desktop).
Run
uvx ragstack-mcp
MCP client config
{
"mcpServers": {
"ragstack": {
"command": "uvx",
"args": [
"ragstack-mcp"
]
}
}
}
Serverless document and media processing with AI chat. Scale-to-zero architecture — no vector database fees, no idle costs. Upload documents, images, video, and audio — extract text with OCR or transcription — query using Amazon Bedrock or your AI assistant via MCP.
| Environment | URL | Credentials |
|---|---|---|
| Base Pipeline | dhrmkxyt1t9pb.cloudfront.net | guest@hatstack.fun / Guest@123 |
| Project Showcase | showcase-htt.hatstack.fun | Login as guest |
Base Pipeline: The core document processing tool - upload, OCR, and query documents.
Project Showcase: See RAGStack powering a real application.
REPO IS IN ACTIVE DEVELOPMENT AND WILL CHANGE OFTEN
Deploy directly from the AWS Console - no local setup required:
After deployment:
UIUrl)For customization or development:
Prerequisites:
git clone https://github.com/HatmanStack/RAGStack-Lambda.git
cd RAGStack-Lambda
# Install dependencies
uv sync
# Deploy (defaults to us-east-1 for Nova Multimodal Embeddings)
python publish.py \
--stack-name my-docs \
--admin-email admin@example.com
Deploy RAGStack as part of a larger CloudFormation stack. See Nested Stack Deployment Guide for details.
Quick example:
Resources:
RAGStack:
Type: AWS::CloudFormation::Stack
Properties:
TemplateURL: https://ragstack-quicklaunch-public.s3.us-east-1.amazonaws.com/ragstack-template.yaml
Parameters:
StackPrefix: 'my-app-ragstack' # Required: lowercase prefix
AdminEmail: admin@example.com
See RAGSTACK_CHAT.md for web component integration guide.
Server-side integrations use API key authentication. Get your key from Dashboard → Settings.
curl -X POST 'YOUR_GRAPHQL_ENDPOINT' \
-H 'x-api-key: YOUR_API_KEY' \
-H 'Content-Type: application/json' \
-d '{"query": "query { searchKnowledgeBase(query: \"...\") { results { content } } }"}'
Web component uses IAM auth (no API key needed - handled automatically).
Each UI tab shows server-side API examples in an expandable section.
Use your knowledge base directly in Claude Desktop, Cursor, VS Code, Amazon Q CLI, and other MCP-compatible tools.
# Install (or use uvx for zero-install)
pip install ragstack-mcp
Add to your AI assistant's MCP config:
{
"ragstack-kb": {
"command": "uvx",
"args": ["ragstack-mcp"],
"env": {
"RAGSTACK_GRAPHQL_ENDPOINT": "YOUR_ENDPOINT",
"RAGSTACK_API_KEY": "YOUR_API_KEY"
}
}
}
Then ask naturally: "Search my knowledge base for authentication docs"
See MCP Server docs for full setup instructions.
Upload → OCR → Embeddings → Bedrock KB
↓
Web UI (Dashboard + Chat) ←→ GraphQL API
↓
Web Component ←→ AI Chat with Sources
Upload documents in various formats. Auto-detection routes to optimal processor:
| Type | Formats | Processing |
|---|---|---|
| Text | HTML, TXT, CSV, JSON, XML, EML, EPUB, DOCX, XLSX | Direct extraction with smart analysis |
| OCR | PDF, JPG, PNG, TIFF, GIF, BMP, WebP, AVIF | Textract or Bedrock vision OCR (WebP/AVIF require Bedrock) |
| Media | MP4, WebM, MP3, WAV, M4A, OGG, FLAC | AWS Transcribe → 30s segments → searchable with timestamps |
| Passthrough | Markdown (.md) | Direct copy |
Processing time: UPLOADED → PROCESSING → INDEXED (typically 1-5 min for text, 2-15 min for OCR, 5-20 min for media)
Upload JPG, PNG, GIF, WebP with captions. Both visual content and caption text are searchable.
Scrape websites into the knowledge base. See Web Scraping.
Upload MP4, WebM, MP3, WAV, M4A, OGG, or FLAC files. Speech is transcribed using AWS Transcribe and segmented into 30-second chunks for search. Sources include timestamps (e.g., "1:30-2:00") with clickable links that play at the exact position.
Features:
See Configuration for language and speaker settings.
Ask questions about your content. Sources show where answers came from.
npm run check # Lint + test all (backend + frontend)
# Full deployment (defaults to us-east-1)
python publish.py --stack-name myapp --admin-email admin@example.com
# Skip dashboard build (still builds web component)
python publish.py --stack-name myapp --admin-email admin@example.com --skip-ui
# Skip ALL UI builds (dashboard and web component)
python publish.py --stack-name myapp --admin-email admin@example.com --skip-ui-all
# Enable demo mode (rate limits: 5 uploads/day, 30 chats/day; disables reindex/reprocess/delete)
python publish.py --stack-name myapp --admin-email admin@example.com --demo-mode
To update the one-click deploy template:
python publish.py --publish-marketplace
This packages the application and uploads to S3 for one-click deployment.
Note: Currently requires us-east-1 (Nova Multimodal Embeddings). When available in other regions, use
--region <region>.
This project was inspired by: