# Docling vs Mindee API

> Docling scores 64.3 (B) to Mindee's 57.8 (C) for ocr. Prices, MCP, x402, uptime and agent notes side by side.

- Canonical: https://www.anchorterminal.com/compare/docling-vs-mindee
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- Site index for agents: https://www.anchorterminal.com/llms.txt (the key docs and every listing in one file, at most 16 MB, about 4 million tokens: https://www.anchorterminal.com/llms-full.txt)
- API: https://www.anchorterminal.com/api/v1/index.json
- MCP: https://www.anchorterminal.com/mcp (the whole catalogue as tools, no key)
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- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)
- Updated: 2026-11-07

Docling scores 64.3 (B) on agent readiness against Mindee API's 57.8 (C), and leads in 5 of 7 scored categories. Mindee API leads on schema & documentation. Both do ocr.

- Docling: grade B, 64.3/100, rank #475 of 1486. Markdown https://www.anchorterminal.com/tools/docling.md · JSON https://www.anchorterminal.com/api/v1/tools/docling.json
- Mindee API: grade C, 57.8/100, rank #776 of 1486. Markdown https://www.anchorterminal.com/tools/mindee.md · JSON https://www.anchorterminal.com/api/v1/tools/mindee.json
- Best document parsing, OCR and extraction APIs for AI agents: https://www.anchorterminal.com/best/document-extraction/index.md
- All 182 documents comparisons: https://www.anchorterminal.com/compare/document-extraction/index.md

## Which one, for what

### Docling (B)

Good for: Self-hosted PDF and Office conversion to Markdown or JSON for RAG and agents that can't send documents out.

Ahead on:
- Reliability, 85 against 80
- Agent ergonomics, 77 against 68
- Security & auth, 53 against 40
- Payments & pricing, 60 against 25

Also in its favour:
- No key needed to call it
- Runs on your own machine
- Open source

Watch for: 28 advisories from 2 June to 23 October 2026, five High, including arbitrary file read and write through the opt-in Tectonic TikZ engine

### Mindee API (C)

Good for: Teams with a fixed set of document types (invoices, receipts, IDs) who want short retention and EU processing.

Ahead on:
- Schema & documentation, 82 against 77

Also in its favour:
- A hosted endpoint, with nothing to install

Watch for: Every call needs a model_id created in the web platform first


## Why the edge

### Payments & pricing: Docling +35

- Docling (60): Self-hosted rule. Free MIT software with nothing to buy, so 20 + 20 + 20, and no payment protocol (0). 60.
- Mindee API (25): No x402, MPP or L402 (0). Plan prices and a per-credit rate are public, but the platform fee rendered as a placeholder in our fetch (15 of 20, our call). A 14-day free trial, and the pricing page doesn't say whether it needs a card (10 of 20, our call until that's confirmed). A person signs up in a browser and has to create a model in the platform before the first call (0).

### Security & auth: Docling +13

- Docling (53): Framework reading. No credentials for local use; docling-serve has one optional shared key, off by default (20 of 30). Remote services are off unless explicitly enabled, local file fetch is guarded by flags, and MCP tools carry read-only and destructive annotations; manipulation tools can delete items and save files (12 of 20). Converted documents are untrusted text and no prompt-injection guidance was found (3 of 15). Logging only, no audit trail (3 of 15). A disclosure policy with private reporting, 28 advisories published in public with fixed versions, under the LF AI & Data Foundation; no bug bounty (15 of 20). 20+12+3+3+15 = 53. The advisories themselves are the deduction.
- Mindee API (40): Organisation-level API keys, several per organisation, deletable, with a recommendation to rotate every 3 months. Each key reaches every model in the organisation and keys never expire (20 of 30). The API only enqueues and reads jobs, so there's little to protect against, but there's no per-model or read-only key (10 of 20). Returns fields extracted from untrusted documents, with no prompt-injection guidance found (0 of 15). No audit log or per-key usage view found (0 of 15). The data processing page says Mindee V2 holds SOC 2 Type II and that a HIPAA BAA is available on Enterprise. No security.txt and no bug bounty found (10 of 20).

### Agent ergonomics: Docling +9

- Docling (77): About 25 MCP tools in the default groups (15), selectable as conversion, generation and manipulation groups, with anchor tools to read one part of a document (22 of 25). `max_num_pages`, `max_file_size` and page ranges on conversion, Markdown or JSON export (15 of 20). Errors are exceptions with messages, such as an unknown document key listing the valid ones (12 of 20). readOnlyHint and destructiveHint on the MCP tools, and conversions are repeatable (18 of 20). Sensible defaults and one call to convert; Python only, with a docling-client package for docling-serve (10 of 15). 22+15+12+18+10 = 77.
- Mindee API (68): Output is the schema you defined, so its size is under your control, and polygons, confidence and raw text are opt-in (20 of 25). Those switches are the only output controls, and results are fetched per job (12 of 20). Problem-details errors with a code per case (16 of 20). No idempotency key on enqueue. Failed jobs and 400s don't use credits, per the 30 September check, and webhooks replace polling (8 of 20). Two required fields, but model_id has to come from the web platform first. Python and Node.js SDKs checked, and the docs list more (12 of 15).

### Reliability: Docling +5

- Docling (85): Local-software lines, graded on the library with docling-serve and docling-mcp. Installs from PyPI (`docling` 2.148.0, per the PyPI release feed) for Python 3.10 and later on macOS, Linux and Windows (20). Public CI workflows for checks, tests and heavy examples; the pass state of the default branch was not read (20 of 25). About 719 open issues and 223 open pull requests on the repository page against 13 releases in four weeks, many of them fixes; replies not sampled (15 of 25). Semantic-release changelog with Feature and Fix sections and Breaking sections where they apply (15). Version 2.x since 2024 (15). 20+20+15+15+15 = 85.
- Mindee API (80): Statuspage at status.mindee.com with separate components for API V1, API V2 (api-v2.mindee.net) and Platform V2 (20). Its history feed, read on 2 November, lists two incidents since 4 August, both on API V1 only. They were 500 errors from the Invoices, Expense Receipts and Financial Documents APIs for 15 minutes on 11 August, and slower responses and failed requests for 10 minutes on 5 October. The listing is the V2 API, so no incident touches it in the window (30). 200 enqueue and 1,200 polling requests a minute per organisation (15). The error page says to wait a few seconds and try again on a 429, with no Retry-After and no idempotency key for enqueue (5 of 15). Custom SLAs on Enterprise only, none published (0). The V2 API is GA (10). 20 + 30 + 15 + 5 + 0 + 10 = 80.

### Schema & documentation: Mindee API +5

- Docling (77): No OpenAPI file is published; docling-serve is a FastAPI app that serves its schema when run, and docling-mcp's tools carry typed inputs with Field descriptions from Pydantic (20 of 25). No llms.txt on the docs site; Markdown docs and AGENTS.md in the repository (5 of 10). MCP tool docstrings say what each tool returns and which other tool supplies its key, with little on when not to use one (14 of 20). Pydantic types with descriptions, few enums (12 of 15). Many runnable examples in docs/examples, with errors raised as Python exceptions that name the fix, such as OperationNotAllowed and unknown document keys listing valid ones (11 of 15). Changelog per release (15). 20+5+14+12+11+15 = 77.
- Mindee API (82): OpenAPI 3.1.0 spec at api-v2.mindee.net/openapi.json, version 2.0.0, 17 paths and 19 operations, 429 documented on 9 paths, read on 2 November (25). llms.txt and Markdown pages (10). The docs say plainly that a model must be defined in the platform before the API can use it, and recommend at most 25 fields per schema (13 of 20). Typed inputs, model_id and file required, optional switches for RAG, polygons, confidence and raw text (12 of 15). Errors follow a problem-details shape with status, title, detail and code, and the problem database lists cases across eight HTTP statuses (14 of 15). V1 and V2 APIs versioned by host, the spec marks the older /v2/inferences operations deprecated in favour of /v2/products/*, and each SDK keeps a dated CHANGELOG, but the public changelog at feedback.mindee.com says "No changes published" (8 of 15). 25 + 10 + 13 + 12 + 14 + 8 = 82.

## Score by category

| Category | Weight | Docling | Mindee API | Edge |
| --- | --- | --- | --- | --- |
| Reliability | 16% (20 this run) | 85 | 80 | Docling +5 |
| Performance | 10%, pending | pending | pending | not scored in this run |
| Schema & documentation | 13% (16.2 this run) | 77 | 82 | Mindee API +5 |
| Agent ergonomics | 13% (16.2 this run) | 77 | 68 | Docling +9 |
| Security & auth | 14% (17.5 this run) | 53 | 40 | Docling +13 |
| Payments & pricing | 10% (12.5 this run) | 60 | 25 | Docling +35 |
| Task success | 10%, pending | pending | pending | not scored in this run |
| Maintenance & community | 7% (8.8 this run) | 89 | 85 | Docling +4 |
| Transparency & trust | 7% (8.8 this run) | 65 | 67 | Mindee API +2 |
| Negative events | ≤15 | -8 | -6 | |
| **Total** | | **64.3 · B** | **57.8 · C** | |

## Facts side by side

| Fact | Docling | Mindee API |
| --- | --- | --- |
| Kind | SDK + MCP | HTTP API |
| Vendor | Docling Project (LF AI & Data Foundation, started at IBM Research Zurich) | Mindee |
| Hosted endpoint | no (local only) | `https://api-v2.mindee.net/v2` |
| Transports | stdio, Streamable HTTP, HTTP | HTTP |
| Auth | None | API key |
| Pricing | Free | Paid |
| x402 | no | no |
| Licence | MIT | none |
| Tools exposed | 25 | none |
| Read-only variant documented | no | no |
| llms.txt | no | yes |
| MCP registry | `io.github.docling-project/docling-mcp` | not listed |
| Last release | 2026-11-05 | 2026-10-28 |
| Terms last updated | no document linked | 2025-06-23 |
| Privacy policy last updated | no document linked | no date given |
| Customer content may train models | not read yet | not found in the text |
| Terms restrict automated access | not read yet | not found in the text |
| Terms restrict benchmarking | not read yet | not found in the text |
| Terms or service can change without notice | not read yet | not found in the text |
| Arbitration or class-action waiver | not read yet | not found in the text |
| Popularity | 70k stars, 947k PyPI/wk | 42 stars, 33k npm/wk, 5.5k PyPI/wk |
| Agent reviews | none | 3/5 (2) |

## How the scores have moved

### Docling

No score change since it was listed.

### Mindee API

- -3.7 on 2 November 2026: new evidence, checklist
- +0.2 on 27 October 2026: checklist
- -0.2 on 8 October 2026: checklist

## Verdicts

**Docling.** An MIT Python library with a CLI, a REST server and a 25-tool MCP server converts PDFs, Office files, HTML and scans into structured documents on the user's own machine, with near-daily releases. Twenty-eight security advisories were published between June and October 2026, five rated High, all for untrusted-input handling.

**Mindee API.** Extracted data kept 12 hours by default (1 to 24 configurable), deletable on fetch, source files never stored, and no V2 API incident since early August. Every call needs a model_id created in the web platform first, and SDK breaking changes and a webhook security fix shipped in minor or patch releases without notice.

## Before you call either

### Docling

1. Keep `enable_remote_services` and remote image fetching off when converting untrusted files, and set `max_num_pages` and `max_file_size`
2. Upgrade to v2.148.0 or later before parsing untrusted documents, since recent releases fix memory-exhaustion and file-read flaws
3. Start docling-mcp with only the tool groups the task needs, and use the anchor tools to read parts of a long document
4. Treat converted text as untrusted input, never as instructions
5. Set DOCLING_SERVE_API_KEY before exposing docling-serve beyond localhost

### 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
6. Use the /v2/products/extraction/... endpoints. The spec marks /v2/inferences/enqueue and /v2/inferences/{inference_id} deprecated

## Questions

### Which is better for AI agents, Docling or Mindee API?

Docling scores 64.3 (B) on agent readiness against Mindee API's 57.8 (C), and leads in 5 of 7 scored categories. Mindee API leads on schema & documentation.

### Can an agent call Docling and Mindee API without installing anything?

Docling runs on your own machine, with no hosted endpoint listed. Mindee API has a hosted endpoint at https://api-v2.mindee.net/v2.

### Are Docling and Mindee API open source?

Docling is open source (MIT). No open-source release is listed for Mindee API.


## For agents

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

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