Serverless OCR-to-Knowledge Base pipeline on AWS
Serverless OCR-to-Knowledge Base pipeline on AWS. That is what the ragstack lambda mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
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.
The server publishes 3 tools. What each one is for:
Documents — Upload documents in various formats. Auto-detection routes to optimal processor:Images — Upload JPG, PNG, GIF, WebP with captions. Both visual content and caption text are searchableChat — Ask questions about your content. Sources show where answers came fromConfiguration is passed through the environment: RAGSTACK_GRAPHQL_ENDPOINT, RAGSTACK_API_KEY, YOUR_API_KEY. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
for on PyPI is all you need. Most clients run it directly, so configuration is a few lines and a restart.
This sits in the cloud and infrastructure group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Ragstack Lambda's toolset — Documents, Images, Chat — is a fair guide to whether it matches your workflow. It is maintained by hatmanstack; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Documents | Upload documents in various formats. Auto-detection routes to optimal processor: |
| Images | Upload JPG, PNG, GIF, WebP with captions. Both visual content and caption text are searchable. |
| Chat | Ask questions about your content. Sources show where answers came from. |
{
"mcpServers": {
"ragstack-lambda": {
"command": "uvx",
"args": ["for"],
"env": {
"RAGSTACK_GRAPHQL_ENDPOINT": "your-value",
"RAGSTACK_API_KEY": "your-value",
"YOUR_API_KEY": "your-value"
}
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
| Variable | Description | Required |
|---|---|---|
| RAGSTACK_GRAPHQL_ENDPOINT | Configuration value read at startup. | Optional |
| RAGSTACK_API_KEY | Credential the server authenticates with. | Yes |
| YOUR_API_KEY | Credential the server authenticates with. | Yes |
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Stop letting your assistant hallucinate n8n node parameters — this server hands it the real schemas, templates and validation.
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