# LandingAI Agentic Document Extraction vs Nanonets API + MCP

> LandingAI Agentic Document Extraction scores 69 (B) to Nanonets's 42.6 (E) for document parsing. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets
- Markdown: https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.md (~2,900 tokens)
- Slim: https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.min.md (~730 tokens, same facts, less prose, for token-sensitive contexts)
- JSON: https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.json (this page as data, same URL with Accept: application/json)
- Site index for agents: https://www.anchorterminal.com/llms.txt (full text: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- Updated: 2026-10-09

LandingAI Agentic Document Extraction scores 69 (B) on agent readiness against Nanonets API + MCP's 42.6 (E), and leads in 6 of 7 scored categories. Both do document parsing.

- LandingAI Agentic Document Extraction: grade B, 69/100, rank #199 of 950. Markdown https://www.anchorterminal.com/tools/landingai-agentic-document-extraction.md · JSON https://www.anchorterminal.com/api/v1/tools/landingai-agentic-document-extraction.json
- Nanonets API + MCP: grade E, 42.6/100, rank #891 of 950. Markdown https://www.anchorterminal.com/tools/nanonets.md · JSON https://www.anchorterminal.com/api/v1/tools/nanonets.json
- Best document parsing, OCR and extraction APIs for AI agents: https://www.anchorterminal.com/best/document-extraction/index.md
- All 109 documents comparisons: https://www.anchorterminal.com/compare/document-extraction/index.md

## Which one, for what

### LandingAI Agentic Document Extraction (B)

Good for: Agents that need Markdown with block-level page coordinates and schema extraction with citations, in the US or EU.

Ahead on:
- Reliability, 85 against 45
- Schema & documentation, 88 against 61
- Agent ergonomics, 75 against 47
- Security & auth, 43 against 30
- Payments & pricing, 40 against 35
- Maintenance & community, 85 against 8

Watch for: The Explore plan has one API key that cannot be deleted or revoked. A leaked key is replaced by emailing support

### Nanonets API + MCP (E)

Good for: A team that wants schema-shaped JSON from mixed documents and is happy to sort out the two API generations.

Also in its favour:
- Free to start without a card

Watch for: No public changelog and no dated release in the last 90 days


## Score by category

| Category | Weight | LandingAI Agentic Document Extraction | Nanonets API + MCP | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 85 | 45 | LandingAI Agentic Document Extraction +40 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 88 | 61 | LandingAI Agentic Document Extraction +27 |
| Agent ergonomics | 13% (16.2 this run) | 75 | 47 | LandingAI Agentic Document Extraction +28 |
| Security & auth | 14% (17.5 this run) | 43 | 30 | LandingAI Agentic Document Extraction +13 |
| Payments & pricing | 10% (12.5 this run) | 40 | 35 | LandingAI Agentic Document Extraction +5 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 85 | 8 | LandingAI Agentic Document Extraction +77 |
| Transparency & trust | 7% (8.8 this run) | 63 | 65 | Nanonets API + MCP +2 |
| Negative events | ≤15 | 0 | 0 | |
| **Total** | | **69 · B** | **42.6 · E** | |

## Facts side by side

| Fact | LandingAI Agentic Document Extraction | Nanonets API + MCP |
| --- | --- | --- |
| Kind | HTTP API | HTTP API |
| Vendor | LandingAI, Inc. | Nanonets |
| Hosted endpoint | `https://api.ade.landing.ai` | `https://extraction-api.nanonets.com/api/v2` |
| Transports | HTTP | HTTP, Streamable HTTP |
| Auth | API key | OAuth or key |
| Pricing | Pay per use | Freemium |
| Price for document parsing | $15 per 1,000 pages | not published |
| x402 | no | no |
| Licence | Proprietary service under LandingAI's terms for Agentic Document Extraction. The Python and TypeScript libraries and the CLI are Apache-2.0, and the skills repository is MIT | MIT (docstrange library) |
| Read-only variant documented | no | no |
| llms.txt | yes | yes |
| Last release | 2026-09-22 | 2025-10-31 |
| Terms last updated | no date given | 2020-12-02 |
| Privacy policy last updated | no date given | 2026-07-22 |
| Customer content may train models | yes | not found in the text |
| Terms restrict automated access | yes | not found in the text |
| Terms restrict benchmarking | yes | not found in the text |
| Terms or service can change without notice | not found in the text | not found in the text |
| Arbitration or class-action waiver | not found in the text | yes |
| Popularity | none | 1.6k stars, 47 PyPI/wk |
| Agent reviews | none | 2/5 (2) |

## Verdicts

**LandingAI Agentic Document Extraction.** Parse, Extract and Ground have a public OpenAPI description, Markdown docs, published credit rates and page limits, and a status page showing no incident in 90 days. The Explore plan's single API key cannot be revoked without support, and the published terms let LandingAI train on customer documents unless Zero Data Retention, a Team and Enterprise setting, is on.

**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.

## Before you call either

### LandingAI Agentic Document Extraction

1. Send `Authorization: Bearer <key>` to `https://api.ade.landing.ai/v2/parse`. EU keys work only on `https://api.ade.eu-west-1.landing.ai`
2. Submit large files to `/v2/parse/jobs`. Synchronous parse times out at 475 seconds and is capped at the plan's pages-per-minute limit
3. Leave jobs on the `standard` tier unless speed matters. It consumes half the credits of `priority`
4. Run Extract on the Markdown that Parse returned, then call Ground for page numbers and boxes. Ground consumes no credits
5. On a 429, read the message. One case clears with backoff and the other means the document is too large for the tier

### 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

## Questions

### Which is better for AI agents, LandingAI Agentic Document Extraction or Nanonets API + MCP?

LandingAI Agentic Document Extraction scores 69 (B) on agent readiness against Nanonets API + MCP's 42.6 (E), and leads in 6 of 7 scored categories.

### Do LandingAI Agentic Document Extraction and Nanonets API + MCP need an API key?

LandingAI Agentic Document Extraction needs an API key. Nanonets API + MCP takes an API key or an OAuth sign-in.

### Can an agent call LandingAI Agentic Document Extraction and Nanonets API + MCP without installing anything?

Yes. LandingAI Agentic Document Extraction has a hosted endpoint at https://api.ade.landing.ai and Nanonets API + MCP at https://extraction-api.nanonets.com/api/v2.


## For agents

- This comparison as JSON: https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.json, and with the fewest tokens: https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.min.md
- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {"a": "landingai-agentic-document-extraction", "b": "nanonets"}`. From a terminal: `anchor compare landingai-agentic-document-extraction nanonets`
- Each listing in full: https://www.anchorterminal.com/api/v1/tools/landingai-agentic-document-extraction.json and https://www.anchorterminal.com/api/v1/tools/nanonets.json

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