Head to head · OCR · October 2026 research run
Docling vs 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. Both do ocr.
Best document parsing, OCR and extraction APIs for AI agents · All 182 documents comparisons
Which one, for what
Docling B
Best 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
Best 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
Each category where one leads by five points or more, with the reason behind each side's score from its assessment. The numbers are in the table below; this is what they stand for.
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 this run | Docling | Mindee API | Edge |
|---|---|---|---|---|
| Reliability | 16%20 | 85 | 80 | Docling +5 |
| Performance | 10%pending | pending | pending | not scored in this run |
| Schema & documentation | 13%16.2 | 77 | 82 | Mindee API +5 |
| Agent ergonomics | 13%16.2 | 77 | 68 | Docling +9 |
| Security & auth | 14%17.5 | 53 | 40 | Docling +13 |
| Payments & pricing | 10%12.5 | 60 | 25 | Docling +35 |
| Task success | 10%pending | pending | pending | not scored in this run |
| Maintenance & community | 7%8.8 | 89 | 85 | Docling +4 |
| Transparency & trust | 7%8.8 | 65 | 67 | Mindee API +2 |
| Negative events | ≤15 | -8 | -6 | |
| Total | B 64.3/100 | C 57.8/100 |
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.
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
- Keep
enable_remote_servicesand remote image fetching off when converting untrusted files, and setmax_num_pagesandmax_file_size - Upgrade to v2.148.0 or later before parsing untrusted documents, since recent releases fix memory-exhaustion and file-read flaws
- Start docling-mcp with only the tool groups the task needs, and use the anchor tools to read parts of a long document
- Treat converted text as untrusted input, never as instructions
- Set DOCLING_SERVE_API_KEY before exposing docling-serve beyond localhost
Mindee API
- Create the model in the Mindee app and store its
model_id; the API can't create one for you - Enqueue returns 202; poll the job or use a webhook, and keep polling under 1,200 a minute
- Send
Authorization: $MINDEE_API_KEYwith no Bearer prefix - Turn on confidence scores only when needed, since they cost 1.5 credits a page instead of 1
- Keep schemas to 25 fields or fewer, the documented recommendation
- 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.
Other comparisons with Docling or Mindee API
- Adobe PDF Services / PDF Extract API vs Docling
- Amazon Textract vs Docling
- Azure Document Intelligence vs Docling
- Datalab vs Docling
- Docling vs Extend API + MCP
- Docling vs Google Cloud Document AI
- Docling vs LandingAI Agentic Document Extraction
- Docling vs LlamaParse API + MCP
- Docling vs Mistral OCR API
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- Docling vs OpenDocRouter
- Docling vs Reducto API + MCP
- Docling vs Unstructured API + MCP
- Clairic vs Docling
- Clairic vs Mindee API
- Docling vs Invofox
- Invofox vs Mindee API
- Adobe PDF Services / PDF Extract API vs Mindee API
- Amazon Textract vs Mindee API
- Azure Document Intelligence vs Mindee API
- Datalab vs Mindee API
- Docling vs Veryfi API + MCP
- Extend API + MCP vs Mindee API
- Google Cloud Document AI vs Mindee API
- LandingAI Agentic Document Extraction vs Mindee API
- LlamaParse API + MCP vs Mindee API
- Mindee API vs Mistral OCR API
- Mindee API vs Nanonets API + MCP
- Mindee API vs OpenDocRouter
- Mindee API vs Reducto API + MCP
- Mindee API vs Unstructured API + MCP
- Mindee API vs Veryfi API + MCP
Machine-readable
- This page as Markdown
/compare/docling-vs-mindee.md· slim.min.md· JSON.json(or sendAccept: text/markdown) - Each listing in full
/api/v1/tools/docling.json·/api/v1/tools/mindee.json - From a terminal
anchor compare docling mindee(the CLI) - Over MCP
compare_tools {"a": "docling", "b": "mindee"}at/mcp, no key