Mindee API vs Nanonets API + MCP

Mindee API

Extracted data kept 12 hours by default (1 to 24 configurable), deletable on fetch, source files never stored. Every call needs a model_id created in the web platform first.

Nanonets API + MCP

Extraction API returns Markdown, CSV or JSON, with named fields or a JSON schema. No public changelog and no dated release in the last 90 days.

Mindee API

1. Create the model in the Mindee app and store its model_id; the API can't create one for you
2. Enqueue returns 202; poll the job or use a webhook, and keep polling under 1,200 a minute
3. Send Authorization: $MINDEE_API_KEY with no Bearer prefix
4. Turn on confidence scores only when needed, since they cost 1.5 credits a page instead of 1
5. Keep schemas to 25 fields or fewer, the documented recommendation

Nanonets API + MCP

1. Use the extraction API at extraction-api.nanonets.com, not app.nanonets.com, unless you already have a trained model
2. Pass a JSON schema in json_options when downstream code needs fixed field names
3. Use the async extract endpoints for long documents and poll /api/v1/extract/results/{record_id}
4. On a 429, wait 30 seconds and double the delay each retry
5. Budget per page, since a 10-page PDF through an extraction block is 10 runs