Question 1

What is Nanonets OCR MCP?

Accepted Answer

It's an MCP (Model Context Protocol) server that connects Nanonets OCR to your AI, giving the agent tools to act on your data — through a single remote link.

Question 2

Which AI clients does it work with?

Accepted Answer

Any MCP-compatible client: Claude (web, desktop and mobile), Cursor, ChatGPT with connectors, OpenClaw and other agents.

Question 3

Do I need to code?

Accepted Answer

No. Paste the remote URL into your client, authenticate once, and you're done — no packages to install, no code to write.

Question 4

Is it secure? Can the AI change my data?

Accepted Answer

Access is authorized by you and can be revoked anytime. Permissions follow what Nanonets OCR exposes; you approve them when connecting.

Question 5

How much does it cost?

Accepted Answer

You start free and upgrade when you need more usage. Billing and limits are managed in your mcp.ai account.

Question 6

Can I cancel anytime?

Accepted Answer

Yes. Plans are monthly and can be cancelled at any time, with no lock-in.

Nanonets OCR

Tools (6)

Example prompts

API & agent docs

Frequently asked questions

Related tags

Nanonets OCR

Tools (6)

nanonets_ocr_extract_from_urlSynchronously extract model-defined fields and tables from one publicly reachable document URL. Returns durable page and file IDs even when the model finds no matching fields.

nanonets_ocr_get_modelGet readiness, accuracy, extraction fields, and table configuration for one Nanonets OCR model.

nanonets_ocr_get_prediction_fileGet normalized extraction results for every page of one previously processed Nanonets OCR file. A successful page can have no extracted fields.

nanonets_ocr_get_prediction_pageGet normalized extracted fields and tables for one OCR prediction page.

nanonets_ocr_list_modelsList the OCR models available to the connected Nanonets account, including each model's ID, readiness state, and extraction categories.

nanonets_ocr_list_predictionsList compact OCR prediction-page summaries for a model within an inclusive UTC date range. Nanonets returns the entire matching range without pagination, so prefer narrow ranges when a model has subst