{ "data": { "a": { "slug": "google-cloud-document-ai", "name": "Google Cloud Document AI", "vendor": "Google Cloud", "vendorUrl": "https://cloud.google.com/document-ai", "kind": "http-api", "category": "document-extraction", "summary": "Google Cloud's service for OCR, layout parsing, chunking, form and table extraction, classification and splitting of documents. Work runs through processors created per project and location. Access is a REST and gRPC API with client libraries in eight languages.", "url": "https://www.anchorterminal.com/tools/google-cloud-document-ai", "markdownUrl": "https://www.anchorterminal.com/tools/google-cloud-document-ai.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/google-cloud-document-ai.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/google-cloud-document-ai.json", "repo": "https://github.com/googleapis/google-cloud-python/tree/main/packages/google-cloud-documentai", "license": "Proprietary service under the Google Cloud Platform Terms of Service. The client libraries are Apache-2.0", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "google-cloud-documentai" }, { "registry": "npm", "name": "@google-cloud/documentai" } ], "auth": "oauth", "authNotes": "Access starts with a Google Cloud project that has the Document AI API and billing enabled, all self-serve in the console. Calls take an OAuth 2.0 bearer token from a service account or Application Default Credentials in the `Authorization` header, with the single scope `https://www.googleapis.com/auth/cloud-platform`. IAM decides what the caller can do, through four predefined roles from `roles/documentai.apiUser` (process only) to `roles/documentai.admin`, grantable on a project or one processor. The docs show no API key flow. Three pretrained processors are open to limited access customers only, by request form.", "pricing": "freemium", "pricingNotes": "Pay as you go per page, with no plan. Enterprise Document OCR is $1.50 per 1,000 pages ($0.60 past 5 million), and the pricing page shows the first 1,000 at $0.00. Layout Parser is $10, Form Parser and Custom Extractor $30 ($20 past a million), Custom Classifier and Splitter $5 ($3 past a million), all per 1,000 pages. Invoice, expense and identity parsers are $0.10 per document of up to 10 pages. A deployed custom processor version costs $0.05 an hour to host. Failed requests are not billed. New customers get $300 of credit for 90 days, and sign-up needs a credit card or other payment method (https://cloud.google.com/document-ai/pricing, https://docs.cloud.google.com/free/docs/free-cloud-features).", "priceSummary": "$1.50 / 1k pages", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the Discovery document or the pricing page (checked 2026-10-09).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 498819, "pypiWeekly": 793248, "asOf": "2026-10-09" }, "docsUrl": "https://docs.cloud.google.com/document-ai/docs", "openapi": "https://documentai.googleapis.com/$discovery/rest?version=v1", "capabilities": [ "docs.parse", "docs.ocr", "docs.extract", "docs.tables", "docs.chunk" ], "tags": [ "hosted", "freemium", "free-tier", "closed-source", "openapi", "oauth", "python", "typescript", "java", "dotnet", "enterprise", "eu", "async-jobs", "batch", "card-required" ], "lastRelease": "2026-10-08", "graded": true, "anchor": { "graded": true, "score": 73.9, "grade": "BB", "agentReady": true, "rank": 82, "ranked": true, "rankOf": 950, "categoryRank": 1, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 70, "maintenance": 80, "payments": 20, "reliability": 90, "schema": 81, "security": 80, "transparency": 90 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-09" }, "negative": 0, "verdict": "A public Discovery document with 42 methods, IAM roles that can limit a caller to processing, a `fieldMask` that trims responses, and a 99.9 per cent SLA on the US and EU endpoints. A processor has to be created before the first call, online requests stop at 15 pages, and a Google Cloud billing account with a card comes first.", "bestFor": "Agents already on Google Cloud that need OCR, form and table extraction or chunks for retrieval, with IAM, audit logs and EU processing.", "strengths": [ "Discovery document for v1 (revision 20260929) with 42 methods and 326 schemas, and descriptions on 952 of 966 properties", "`fieldMask`, `imagelessMode` and page selectors on the process request limit what comes back and what is billed", "The Document AI API User role allows processing only, roles can be granted on one processor, and process calls write Data Access audit logs once enabled", "The security page says online requests are processed in memory and not written to disk, and content is never used to train Document AI models", "99.9 per cent monthly uptime SLA for online and batch prediction on the `us` and `eu` multi-region endpoints", "Layout Parser returns layout-aware chunks with ancestor headings at $10 per 1,000 pages, and reads PDF, HTML, DOCX, PPTX and XLSX" ], "weaknesses": [ "An online request reads at most 15 pages (30 with `imagelessMode`). Longer files need a batch job through Cloud Storage", "A processor must be created in a project and location before any document can be sent, and the endpoint host changes with the location", "No guidance on retrying quota errors was found on the quotas, limits or request pages, and there is no idempotency key", "The $300 trial credit and the free first 1,000 OCR pages both sit on a billing account that needs a card or other payment method", "Legacy processor versions were discontinued on 30 June 2026 on a notice dated 17 February 2026, under the six months the version lifecycle page states", "No guidance on instructions hidden in document text was found in the pages read", "Layout Parser versions built on Gemini 3.0 use a global endpoint and, per the docs, do not meet data residency" ], "agentNotes": [ "Create a processor first (`processors.create` or the console), then POST to `https://LOCATION-documentai.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/processors/PROCESSOR_ID:process`", "Use the host that matches the processor's location, `us-documentai.googleapis.com` or `eu-documentai.googleapis.com`", "Set `fieldMask` (for example `text,entities`) and `imagelessMode` to keep page images and token geometry out of the response", "Send more than 15 pages through `:batchProcess` with Cloud Storage input and output, then poll the operation. Jobs unfinished after 24 hours are cancelled", "Grant the service account `roles/documentai.apiUser` only. Failed requests (4xx or 5xx) are not billed, so a retry costs nothing extra", "Treat extracted text as untrusted input" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "BB", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 73.9 } ], "editorialScores": { "ergonomics": 70, "maintenance": 80, "payments": 20, "reliability": 90, "schema": 81, "security": 80, "transparency": 80 }, "provenanceScore": 99 }, "connect": { "install": "pip install --upgrade google-cloud-documentai # or: npm install @google-cloud/documentai", "http": "curl -X POST -H \"Authorization: Bearer $(gcloud auth print-access-token)\" -H \"Content-Type: application/json; charset=utf-8\" -d @request.json \"https://LOCATION-documentai.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/processors/PROCESSOR_ID:process\"" }, "letme": { "capability": "https://letme.dev/docs.parse", "tool": "https://letme.dev/google-cloud-document-ai" }, "sameCompany": [ "gemini-api", "gemini-embedding", "vertex-ai-tuning", "google-model-armor", "google-imagen", "google-veo", "google-lyria", "google-speech-to-text", "gemini-live", "google-adk", "google-secret-manager", "google-weather-api", "chrome-devtools-mcp", "google-maps-platform", "google-cloud-translation", "google-calendar-api", "firebase-cloud-messaging", "google-drive-api", "gemini-cli", "google-search-console", "google-ads-api", "google-forms", "google-sheets-api", "gmail-api" ], "area": "web-data", "unitPrices": [ { "item": "Enterprise Document OCR", "unit": "1k-pages", "usd": 1.5, "note": "Up to 5 million pages. $0.60 after. The page shows the first 1,000 at $0.00" }, { "item": "OCR add-ons", "unit": "1k-pages", "usd": 6, "note": "On top of the OCR price, Enterprise Document OCR v2 only" }, { "item": "Layout Parser", "unit": "1k-pages", "usd": 10, "note": "Includes the first chunking. DOCX and HTML count 3,000 characters as a page" }, { "item": "Form Parser", "unit": "1k-pages", "usd": 30, "note": "First million pages. $20 after" }, { "item": "Custom Extractor", "unit": "1k-pages", "usd": 30, "note": "First million pages. $20 after. Hosting is $0.05 an hour per deployed version" }, { "item": "Custom Classifier or Splitter", "unit": "1k-pages", "usd": 5, "note": "First million pages. $3 after" }, { "item": "Invoice, expense or identity parser", "unit": "tx", "usd": 0.1, "note": "Per document of up to 10 pages. Each further 10 pages is another $0.10" }, { "item": "Bank statement parser", "unit": "tx", "usd": 0.75, "note": "Per classified document" } ], "provenance": { "legalEntity": "Google LLC", "domain": "google.com", "domainRegistered": "1997-09-15", "domainNote": "The endpoints are on googleapis.com, Google's API domain. Docs are on docs.cloud.google.com.", "endpointOnVendorDomain": true, "terms": "https://cloud.google.com/terms", "privacy": "https://cloud.google.com/terms/cloud-privacy-notice", "statusPage": "https://status.cloud.google.com", "changelog": "https://docs.cloud.google.com/document-ai/docs/release-notes", "securityTxt": "valid", "checked": "2026-10-09", "notes": [ "The Google Cloud Platform Terms of Service were last modified on 2 September 2026. They set the contracting Google entity by customer region at https://cloud.google.com/terms/google-entity.", "The Service Specific Terms (https://cloud.google.com/terms/service-terms, last modified 8 October 2026) carry the training restriction and the benchmarking clause.", "The Google Cloud Privacy Notice, effective 28 September 2026, covers Service Data and names Google LLC, 1600 Amphitheatre Parkway. Customer documents fall under the Cloud Data Processing Addendum.", "https://www.google.com/.well-known/security.txt shows Expires 2030-04-01 and points to the vulnerability reward programme.", "RDAP gives 1997-09-15 for google.com." ], "score": 99 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/google-cloud-document-ai.json", "live": { "slug": "google-cloud-document-ai", "vendorStatus": { "page": "https://status.cloud.google.com", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-10T00:50:37.922164095Z" }, "versions": [ { "registry": "github", "name": "googleapis/google-cloud-python", "version": "google-devicesandservices-health-v0.1.4", "released": "2026-10-08", "seenAt": "2026-10-09T16:55:32.090616373Z" }, { "registry": "npm", "name": "@google-cloud/documentai", "version": "10.1.1", "seenAt": "2026-10-09T16:55:31.078020463Z" }, { "registry": "pypi", "name": "google-cloud-documentai", "version": "3.16.0", "released": "2026-10-01", "seenAt": "2026-10-09T16:55:30.888054925Z" } ], "githubStars": 5404, "npmWeekly": 498819, "pypiWeekly": 793248, "pages": [ { "url": "https://docs.cloud.google.com/document-ai/docs/release-notes", "kind": "changelog", "status": 200, "checkedAt": "2026-10-09T18:36:50.7725009Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "e935ad11b444" }, { "url": "https://cloud.google.com/document-ai/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-10-09T18:33:50.823409679Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "cd273ea5fefa" }, { "url": "https://cloud.google.com/terms/cloud-privacy-notice", "kind": "privacy", "status": 200, "checkedAt": "2026-10-09T18:34:03.79726444Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "98f84e10526a" }, { "url": "https://cloud.google.com/terms", "kind": "terms", "status": 200, "checkedAt": "2026-10-09T18:34:01.379172107Z", "changedAt": "2026-10-08T18:16:24.0781454Z", "fingerprint": "92f14ada0b50" } ], "updatedAt": "2026-10-10T00:50:37.922164095Z" } }, "answer": "Google Cloud Document AI scores 73.9 (BB) on agent readiness against Nanonets API + MCP's 42.6 (E), and leads in 6 of 7 scored categories. Nanonets API + MCP leads on payments \u0026 pricing.", "b": { "slug": "nanonets", "name": "Nanonets API + MCP", "vendor": "Nanonets", "vendorUrl": "https://nanonets.com", "kind": "http-api", "category": "document-extraction", "summary": "OCR and field extraction from PDFs, scans and images.", "url": "https://www.anchorterminal.com/tools/nanonets", "markdownUrl": "https://www.anchorterminal.com/tools/nanonets.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/nanonets.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/nanonets.json", "repo": "https://github.com/NanoNets/docstrange", "license": "MIT (docstrange library)", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://extraction-api.nanonets.com/api/v2", "packages": [ { "registry": "pypi", "name": "docstrange" } ], "auth": "mixed", "authNotes": "Extraction API takes a Bearer key. The older app API at app.nanonets.com/api/v2 takes the key as the HTTP Basic username with an empty password. The hosted MCP server at mcp.nanonets.com/mcp uses OAuth sign-in.", "pricing": "freemium", "pricingNotes": "Starter is free with $50 of credits and no card, then $100 a month for 100 credits. Billing is per block run, $0.02 for simple blocks, $0.10 for standard AI and $0.30 for complex AI such as data extraction, and extraction counts one run a page. Growth is quoted with up to 40% volume discount, Enterprise is custom (https://nanonets.com/pricing).", "priceSummary": "$100 / mo", "where": "hosted", "x402": { "level": "no", "evidence": "No x402 in docs, OpenAPI document or pricing (checked 2026-09-30).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 1574, "npmWeekly": null, "pypiWeekly": 47, "asOf": "2026-09-30" }, "docsUrl": "https://docs.nanonets.com", "llmsTxt": "https://docs.nanonets.com/llms.txt", "openapi": "https://extraction-api.nanonets.com/openapi.json", "capabilities": [ "docs.parse", "docs.ocr", "docs.extract", "docs.tables", "docs.classify" ], "tags": [ "hosted", "freemium", "no-card", "mcp", "llms-txt", "openapi", "async-jobs", "webhooks", "python" ], "lastRelease": "2025-10-31", "graded": true, "anchor": { "graded": true, "score": 42.6, "grade": "E", "agentReady": false, "rank": 891, "ranked": true, "rankOf": 950, "categoryRank": 15, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 47, "maintenance": 8, "payments": 35, "reliability": 45, "schema": 61, "security": 30, "transparency": 65 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": 0, "verdict": "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.", "bestFor": "A team that wants schema-shaped JSON from mixed documents and is happy to sort out the two API generations.", "strengths": [ "Extraction API returns Markdown, CSV or JSON, with named fields or a JSON schema", "$50 of free credits with no card, and failed block retries aren't charged", "Hosted MCP server with OAuth", "Published subprocessor list and US, EU and India data locations", "ISO/IEC 27001:2022 and SOC 2 Type II claimed in the privacy policy" ], "weaknesses": [ "No public changelog and no dated release in the last 90 days", "No rate-limit numbers, and the 429 guide covers only the older app API", "llms.txt indexes the older app API, not the extraction API or the MCP server", "MCP tool list not published", "Model-family prices come from an account manager" ], "agentNotes": [ "Use the extraction API at `extraction-api.nanonets.com`, not `app.nanonets.com`, unless you already have a trained model", "Pass a JSON schema in `json_options` when downstream code needs fixed field names", "Use the async extract endpoints for long documents and poll `/api/v1/extract/results/{record_id}`", "On a 429, wait 30 seconds and double the delay each retry", "Budget per page, since a 10-page PDF through an extraction block is 10 runs" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 2, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "E", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 42.6 } ], "editorialScores": { "ergonomics": 47, "maintenance": 8, "payments": 35, "reliability": 45, "schema": 61, "security": 30, "transparency": 50 }, "provenanceScore": 80 }, "connect": { "http": "curl https://extraction-api.nanonets.com/api/v1/extract/sync \\\n -H \"Authorization: Bearer $NANONETS_API_KEY\" \\\n -F file_url=https://example.com/invoice.pdf -F output_format=markdown", "claudeCode": "claude mcp add --transport http nanonets https://mcp.nanonets.com/mcp" }, "letme": { "capability": "https://letme.dev/docs.parse", "tool": "https://letme.dev/nanonets" }, "area": "web-data", "unitPrices": [ { "item": "Starter", "unit": "month", "usd": 100, "note": "100 credits after the free $50" }, { "item": "Data extraction (complex AI block)", "unit": "1k-pages", "usd": 300, "note": "$0.30 a run at list price, one run a page" }, { "item": "Standard AI block", "unit": "call", "usd": 0.1, "note": "classification, validation" }, { "item": "Simple block", "unit": "call", "usd": 0.02, "note": "formatting, routing, export" } ], "provenance": { "legalEntity": "Nano Net Technologies Inc.", "domain": "nanonets.com", "domainRegistered": "2005-10-15", "endpointOnVendorDomain": true, "terms": "https://legal.nanonets.com/terms", "privacy": "https://legal.nanonets.com/privacy", "statusPage": "https://status.nanonets.com", "changelog": "", "securityTxt": "none", "checked": "2026-09-30", "notes": [ "RDAP gives a 2005 registration, older than the company, so the domain was probably bought later" ], "score": 80 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/nanonets.json", "live": { "slug": "nanonets", "probe": { "target": "https://extraction-api.nanonets.com/api/v2", "method": "get", "lastAt": "2026-10-10T01:37:59.815310831Z", "lastOk": true, "lastStatus": 404, "lastMs": 443, "authRequired": false, "uptime24h": 99.6, "uptime30d": 99.55, "p50ms24h": 450, "p95ms24h": 505, "samples24h": 250, "samples30d": 2453, "days": [ { "date": "2026-09-30", "probes": 35, "ok": 35 }, { "date": "2026-10-01", "probes": 276, "ok": 276 }, { "date": "2026-10-02", "probes": 248, "ok": 245 }, { "date": "2026-10-03", "probes": 271, "ok": 271 }, { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 272, "ok": 270 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 269 }, { "date": "2026-10-08", "probes": 268, "ok": 266 }, { "date": "2026-10-09", "probes": 250, "ok": 249 }, { "date": "2026-10-10", "probes": 17, "ok": 17 } ] }, "vendorStatus": { "page": "https://status.nanonets.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-10T01:33:50.963136809Z" }, "versions": [ { "registry": "pypi", "name": "docstrange", "version": "1.1.8", "released": "2025-10-31", "seenAt": "2026-10-09T17:07:56.757677284Z" } ], "githubStars": 1578, "pypiWeekly": 50, "securityTxt": { "url": "https://nanonets.com/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-09T15:40:25.972460192Z" }, "llmsTxt": { "url": "https://docs.nanonets.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-09T14:02:27.285204067Z" }, "domain": { "domain": "nanonets.com", "registered": "2005-10-15", "source": "https://rdap.verisign.com/com/v1/domain/nanonets.com", "checkedAt": "2026-10-04T13:08:18.933907619Z" }, "pages": [ { "url": "https://nanonets.com/pricing", "kind": "pricing", "status": 304, "checkedAt": "2026-10-09T18:42:23.825223733Z", "changedAt": "2026-10-07T18:07:42.664259032Z", "fingerprint": "ac68b0ebe4e7" }, { "url": "https://legal.nanonets.com/privacy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-09T18:41:14.429599504Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "cdfa3c559c87" }, { "url": "https://legal.nanonets.com/terms", "kind": "terms", "status": 200, "checkedAt": "2026-10-09T18:41:16.909908041Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "8c04180e8356" } ], "updatedAt": "2026-10-10T01:37:59.815310831Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Google Cloud", "b": "Nanonets", "name": "Vendor" }, { "a": "no (local only)", "b": "https://extraction-api.nanonets.com/api/v2", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP, Streamable HTTP", "name": "Transports" }, { "a": "OAuth", "b": "OAuth or key", "name": "Auth" }, { "a": "Freemium", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under the Google Cloud Platform Terms of Service. The client libraries are Apache-2.0", "b": "MIT (docstrange library)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-08", "b": "2025-10-31", "name": "Last release" }, { "a": "2026-09-02", "b": "2020-12-02", "name": "Terms last updated" }, { "a": "2026-09-28", "b": "2026-07-22", "name": "Privacy policy last updated" }, { "a": "not found in the text", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not found in the text", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "499k npm/wk, 793k PyPI/wk", "b": "1.6k stars, 47 PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "2/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Google Cloud Document AI scores 73.9 (BB) on agent readiness against Nanonets API + MCP's 42.6 (E), and leads in 6 of 7 scored categories. Nanonets API + MCP leads on payments \u0026 pricing.", "question": "Which is better for AI agents, Google Cloud Document AI or Nanonets API + MCP?" }, { "answer": "Google Cloud Document AI uses an OAuth sign-in. Nanonets API + MCP takes an API key or an OAuth sign-in.", "question": "Do Google Cloud Document AI and Nanonets API + MCP need an API key?" }, { "answer": "No hosted endpoint is listed for Google Cloud Document AI. Nanonets API + MCP has a hosted endpoint at https://extraction-api.nanonets.com/api/v2.", "question": "Can an agent call Google Cloud Document AI and Nanonets API + MCP without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 90 against 45", "Schema \u0026 documentation, 81 against 61", "Agent ergonomics, 70 against 47", "Security \u0026 auth, 80 against 30", "Maintenance \u0026 community, 80 against 8", "Transparency \u0026 trust, 90 against 65" ], "also": [ "Agent-ready, a grade of BB or better" ], "goodFor": "Agents already on Google Cloud that need OCR, form and table extraction or chunks for retrieval, with IAM, audit logs and EU processing.", "slug": "google-cloud-document-ai", "watchFor": "An online request reads at most 15 pages (30 with `imagelessMode`). Longer files need a batch job through Cloud Storage" }, { "aheadOn": [ "Payments \u0026 pricing, 35 against 20" ], "also": [ "A hosted endpoint, with nothing to install", "Free to start without a card" ], "goodFor": "A team that wants schema-shaped JSON from mixed documents and is happy to sort out the two API generations.", "slug": "nanonets", "watchFor": "No public changelog and no dated release in the last 90 days" } ], "job": { "capability": "docs.parse", "name": "Document parsing" }, "others": [ { "json": "https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-google-cloud-document-ai.json", "title": "Adobe PDF Services / PDF Extract API vs Google Cloud Document AI", "url": "https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-google-cloud-document-ai" }, { "json": "https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-nanonets.json", "title": "Adobe PDF Services / PDF Extract API vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-nanonets" }, { "json": "https://www.anchorterminal.com/compare/amazon-textract-vs-google-cloud-document-ai.json", "title": "Amazon Textract vs Google Cloud Document AI", "url": "https://www.anchorterminal.com/compare/amazon-textract-vs-google-cloud-document-ai" }, { "json": "https://www.anchorterminal.com/compare/amazon-textract-vs-nanonets.json", "title": "Amazon Textract vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/amazon-textract-vs-nanonets" }, { "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-google-cloud-document-ai.json", "title": "Azure Document Intelligence vs Google Cloud Document AI", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-google-cloud-document-ai" }, { "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-nanonets.json", "title": "Azure Document Intelligence vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-nanonets" }, { "json": "https://www.anchorterminal.com/compare/extend-vs-google-cloud-document-ai.json", "title": "Extend API + MCP vs Google Cloud Document AI", "url": "https://www.anchorterminal.com/compare/extend-vs-google-cloud-document-ai" }, { "json": "https://www.anchorterminal.com/compare/extend-vs-nanonets.json", "title": "Extend API + MCP vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/extend-vs-nanonets" }, { "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-landingai-agentic-document-extraction.json", "title": "Google Cloud Document AI vs LandingAI Agentic Document Extraction", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-landingai-agentic-document-extraction" }, { "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-llamaparse.json", "title": "Google Cloud Document AI vs LlamaParse API + MCP", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-llamaparse" }, { "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-mistral-ocr.json", "title": "Google Cloud Document AI vs Mistral OCR API", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-mistral-ocr" }, { "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-opendocrouter.json", "title": "Google Cloud Document AI vs OpenDocRouter", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-opendocrouter" }, { "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-reducto.json", "title": "Google Cloud Document AI vs Reducto API + MCP", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-reducto" }, { "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-unstructured.json", "title": "Google Cloud Document AI vs Unstructured API + MCP", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-unstructured" }, { "json": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.json", "title": "LandingAI Agentic Document Extraction vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets" }, { "json": "https://www.anchorterminal.com/compare/llamaparse-vs-nanonets.json", "title": "LlamaParse API + MCP vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/llamaparse-vs-nanonets" }, { "json": "https://www.anchorterminal.com/compare/mistral-ocr-vs-nanonets.json", "title": "Mistral OCR API vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/mistral-ocr-vs-nanonets" }, { "json": "https://www.anchorterminal.com/compare/nanonets-vs-opendocrouter.json", "title": "Nanonets API + MCP vs OpenDocRouter", "url": "https://www.anchorterminal.com/compare/nanonets-vs-opendocrouter" }, { "json": "https://www.anchorterminal.com/compare/nanonets-vs-reducto.json", "title": "Nanonets API + MCP vs Reducto API + MCP", "url": "https://www.anchorterminal.com/compare/nanonets-vs-reducto" }, { "json": "https://www.anchorterminal.com/compare/nanonets-vs-unstructured.json", "title": "Nanonets API + MCP vs Unstructured API + MCP", "url": "https://www.anchorterminal.com/compare/nanonets-vs-unstructured" }, { "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-mindee.json", "title": "Google Cloud Document AI vs Mindee API", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-mindee" }, { "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-veryfi.json", "title": "Google Cloud Document AI vs Veryfi API + MCP", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-veryfi" }, { "json": "https://www.anchorterminal.com/compare/mindee-vs-nanonets.json", "title": "Mindee API vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/mindee-vs-nanonets" }, { "json": "https://www.anchorterminal.com/compare/nanonets-vs-veryfi.json", "title": "Nanonets API + MCP vs Veryfi API + MCP", "url": "https://www.anchorterminal.com/compare/nanonets-vs-veryfi" }, { "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-invofox.json", "title": "Google Cloud Document AI vs Invofox", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-invofox" }, { "json": "https://www.anchorterminal.com/compare/invofox-vs-nanonets.json", "title": "Invofox vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/invofox-vs-nanonets" } ], "scores": [ { "by": 45, "edge": "google-cloud-document-ai", "google-cloud-document-ai": 90, "key": "reliability", "name": "Reliability", "nanonets": 45, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 20, "edge": "google-cloud-document-ai", "google-cloud-document-ai": 81, "key": "schema", "name": "Schema \u0026 documentation", "nanonets": 61, "weight": 13 }, { "by": 23, "edge": "google-cloud-document-ai", "google-cloud-document-ai": 70, "key": "ergonomics", "name": "Agent ergonomics", "nanonets": 47, "weight": 13 }, { "by": 50, "edge": "google-cloud-document-ai", "google-cloud-document-ai": 80, "key": "security", "name": "Security \u0026 auth", "nanonets": 30, "weight": 14 }, { "by": 15, "edge": "nanonets", "google-cloud-document-ai": 20, "key": "payments", "name": "Payments \u0026 pricing", "nanonets": 35, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 72, "edge": "google-cloud-document-ai", "google-cloud-document-ai": 80, "key": "maintenance", "name": "Maintenance \u0026 community", "nanonets": 8, "weight": 7 }, { "by": 25, "edge": "google-cloud-document-ai", "google-cloud-document-ai": 90, "key": "transparency", "name": "Transparency \u0026 trust", "nanonets": 65, "weight": 7 } ], "summary": "Google Cloud Document AI scores 73.9 (BB) on agent readiness against Nanonets API + MCP's 42.6 (E), and leads in 6 of 7 scored categories. Nanonets API + MCP leads on payments \u0026 pricing. Both do document parsing.", "verdicts": { "google-cloud-document-ai": "A public Discovery document with 42 methods, IAM roles that can limit a caller to processing, a `fieldMask` that trims responses, and a 99.9 per cent SLA on the US and EU endpoints. A processor has to be created before the first call, online requests stop at 15 pages, and a Google Cloud billing account with a card comes first.", "nanonets": "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." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-nanonets", "json": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-nanonets.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-nanonets.md", "slim": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-nanonets.min.md" }, "markdown": "Google Cloud Document AI scores 73.9 (BB) on agent readiness against Nanonets API + MCP's 42.6 (E), and leads in 6 of 7 scored categories. Nanonets API + MCP leads on payments \u0026 pricing. Both do document parsing.\n\n- Google Cloud Document AI: grade BB, 73.9/100, rank #82 of 950. Markdown https://www.anchorterminal.com/tools/google-cloud-document-ai.md · JSON https://www.anchorterminal.com/api/v1/tools/google-cloud-document-ai.json\n- 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\n- Best document parsing, OCR and extraction APIs for AI agents: https://www.anchorterminal.com/best/document-extraction/index.md\n- All 109 documents comparisons: https://www.anchorterminal.com/compare/document-extraction/index.md\n\n## Which one, for what\n\n### Google Cloud Document AI (BB)\n\nGood for: Agents already on Google Cloud that need OCR, form and table extraction or chunks for retrieval, with IAM, audit logs and EU processing.\n\nAhead on:\n- Reliability, 90 against 45\n- Schema \u0026 documentation, 81 against 61\n- Agent ergonomics, 70 against 47\n- Security \u0026 auth, 80 against 30\n- Maintenance \u0026 community, 80 against 8\n- Transparency \u0026 trust, 90 against 65\n\nAlso in its favour:\n- Agent-ready, a grade of BB or better\n\nWatch for: An online request reads at most 15 pages (30 with `imagelessMode`). Longer files need a batch job through Cloud Storage\n\n### Nanonets API + MCP (E)\n\nGood for: A team that wants schema-shaped JSON from mixed documents and is happy to sort out the two API generations.\n\nAhead on:\n- Payments \u0026 pricing, 35 against 20\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n- Free to start without a card\n\nWatch for: No public changelog and no dated release in the last 90 days\n\n\n## Score by category\n\n| Category | Weight | Google Cloud Document AI | Nanonets API + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 90 | 45 | Google Cloud Document AI +45 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 81 | 61 | Google Cloud Document AI +20 |\n| Agent ergonomics | 13% (16.2 this run) | 70 | 47 | Google Cloud Document AI +23 |\n| Security \u0026 auth | 14% (17.5 this run) | 80 | 30 | Google Cloud Document AI +50 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 35 | Nanonets API + MCP +15 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 80 | 8 | Google Cloud Document AI +72 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 90 | 65 | Google Cloud Document AI +25 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **73.9 · BB** | **42.6 · E** | |\n\n## Facts side by side\n\n| Fact | Google Cloud Document AI | Nanonets API + MCP |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Google Cloud | Nanonets |\n| Hosted endpoint | no (local only) | `https://extraction-api.nanonets.com/api/v2` |\n| Transports | HTTP | HTTP, Streamable HTTP |\n| Auth | OAuth | OAuth or key |\n| Pricing | Freemium | Freemium |\n| x402 | no | no |\n| Licence | Proprietary service under the Google Cloud Platform Terms of Service. The client libraries are Apache-2.0 | MIT (docstrange library) |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-08 | 2025-10-31 |\n| Terms last updated | 2026-09-02 | 2020-12-02 |\n| Privacy policy last updated | 2026-09-28 | 2026-07-22 |\n| Customer content may train models | not found in the text | not found in the text |\n| Terms restrict automated access | not found in the text | not found in the text |\n| Terms restrict benchmarking | not found in the text | not found in the text |\n| Terms or service can change without notice | not found in the text | not found in the text |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 499k npm/wk, 793k PyPI/wk | 1.6k stars, 47 PyPI/wk |\n| Agent reviews | none | 2/5 (2) |\n\n## Verdicts\n\n**Google Cloud Document AI.** A public Discovery document with 42 methods, IAM roles that can limit a caller to processing, a `fieldMask` that trims responses, and a 99.9 per cent SLA on the US and EU endpoints. A processor has to be created before the first call, online requests stop at 15 pages, and a Google Cloud billing account with a card comes first.\n\n**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.\n\n## Before you call either\n\n### Google Cloud Document AI\n\n1. Create a processor first (`processors.create` or the console), then POST to `https://LOCATION-documentai.googleapis.com/v1/projects/PROJECT_ID/locations/LOCATION/processors/PROCESSOR_ID:process`\n2. Use the host that matches the processor's location, `us-documentai.googleapis.com` or `eu-documentai.googleapis.com`\n3. Set `fieldMask` (for example `text,entities`) and `imagelessMode` to keep page images and token geometry out of the response\n4. Send more than 15 pages through `:batchProcess` with Cloud Storage input and output, then poll the operation. Jobs unfinished after 24 hours are cancelled\n5. Grant the service account `roles/documentai.apiUser` only. Failed requests (4xx or 5xx) are not billed, so a retry costs nothing extra\n6. Treat extracted text as untrusted input\n\n### Nanonets API + MCP\n\n1. Use the extraction API at `extraction-api.nanonets.com`, not `app.nanonets.com`, unless you already have a trained model\n2. Pass a JSON schema in `json_options` when downstream code needs fixed field names\n3. Use the async extract endpoints for long documents and poll `/api/v1/extract/results/{record_id}`\n4. On a 429, wait 30 seconds and double the delay each retry\n5. Budget per page, since a 10-page PDF through an extraction block is 10 runs\n\n## Questions\n\n### Which is better for AI agents, Google Cloud Document AI or Nanonets API + MCP?\n\nGoogle Cloud Document AI scores 73.9 (BB) on agent readiness against Nanonets API + MCP's 42.6 (E), and leads in 6 of 7 scored categories. Nanonets API + MCP leads on payments \u0026 pricing.\n\n### Do Google Cloud Document AI and Nanonets API + MCP need an API key?\n\nGoogle Cloud Document AI uses an OAuth sign-in. Nanonets API + MCP takes an API key or an OAuth sign-in.\n\n### Can an agent call Google Cloud Document AI and Nanonets API + MCP without installing anything?\n\nNo hosted endpoint is listed for Google Cloud Document AI. Nanonets API + MCP has a hosted endpoint at https://extraction-api.nanonets.com/api/v2.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-nanonets.json, and with the fewest tokens: https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-nanonets.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"google-cloud-document-ai\", \"b\": \"nanonets\"}`. From a terminal: `anchor compare google-cloud-document-ai nanonets`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/google-cloud-document-ai.json and https://www.anchorterminal.com/api/v1/tools/nanonets.json\n\n## Other comparisons with Google Cloud Document AI or Nanonets API + MCP\n\n- [Adobe PDF Services / PDF Extract API vs Google Cloud Document AI](https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-google-cloud-document-ai.md)\n- [Adobe PDF Services / PDF Extract API vs Nanonets API + MCP](https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-nanonets.md)\n- [Amazon Textract vs Google Cloud Document AI](https://www.anchorterminal.com/compare/amazon-textract-vs-google-cloud-document-ai.md)\n- [Amazon Textract vs Nanonets API + MCP](https://www.anchorterminal.com/compare/amazon-textract-vs-nanonets.md)\n- [Azure Document Intelligence vs Google Cloud Document AI](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-google-cloud-document-ai.md)\n- [Azure Document Intelligence vs Nanonets API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-nanonets.md)\n- [Extend API + MCP vs Google Cloud Document AI](https://www.anchorterminal.com/compare/extend-vs-google-cloud-document-ai.md)\n- [Extend API + MCP vs Nanonets API + MCP](https://www.anchorterminal.com/compare/extend-vs-nanonets.md)\n- [Google Cloud Document AI vs LandingAI Agentic Document Extraction](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-landingai-agentic-document-extraction.md)\n- [Google Cloud Document AI vs LlamaParse API + MCP](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-llamaparse.md)\n- [Google Cloud Document AI vs Mistral OCR API](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-mistral-ocr.md)\n- [Google Cloud Document AI vs OpenDocRouter](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-opendocrouter.md)\n- [Google Cloud Document AI vs Reducto API + MCP](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-reducto.md)\n- [Google Cloud Document AI vs Unstructured API + MCP](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-unstructured.md)\n- [LandingAI Agentic Document Extraction vs Nanonets API + MCP](https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.md)\n- [LlamaParse API + MCP vs Nanonets API + MCP](https://www.anchorterminal.com/compare/llamaparse-vs-nanonets.md)\n- [Mistral OCR API vs Nanonets API + MCP](https://www.anchorterminal.com/compare/mistral-ocr-vs-nanonets.md)\n- [Nanonets API + MCP vs OpenDocRouter](https://www.anchorterminal.com/compare/nanonets-vs-opendocrouter.md)\n- [Nanonets API + MCP vs Reducto API + MCP](https://www.anchorterminal.com/compare/nanonets-vs-reducto.md)\n- [Nanonets API + MCP vs Unstructured API + MCP](https://www.anchorterminal.com/compare/nanonets-vs-unstructured.md)\n- [Google Cloud Document AI vs Mindee API](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-mindee.md)\n- [Google Cloud Document AI vs Veryfi API + MCP](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-veryfi.md)\n- [Mindee API vs Nanonets API + MCP](https://www.anchorterminal.com/compare/mindee-vs-nanonets.md)\n- [Nanonets API + MCP vs Veryfi API + MCP](https://www.anchorterminal.com/compare/nanonets-vs-veryfi.md)\n- [Google Cloud Document AI vs Invofox](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-invofox.md)\n- [Invofox vs Nanonets API + MCP](https://www.anchorterminal.com/compare/invofox-vs-nanonets.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-10", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.4", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Google Cloud Document AI vs Nanonets API + MCP", "url": "" } ], "description": "Google Cloud Document AI scores 73.9 (BB) to Nanonets's 42.6 (E) for document parsing. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Google Cloud Document AI BB 73.9", "Nanonets API + MCP E 42.6", "scores" ], "h1": "Google Cloud Document AI vs Nanonets API + MCP", "image": "https://www.anchorterminal.com/assets/og/compare-google-cloud-document-ai-vs-nanonets.png", "path": "/compare/google-cloud-document-ai-vs-nanonets", "published": "2026-10-01", "section": "tools", "title": "Google Cloud Document AI vs Nanonets for AI agents (2026)", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-nanonets" }, "tokens": { "markdown": 2800, "slim": 680 }, "version": 1 }