{ "data": { "a": { "slug": "landingai-agentic-document-extraction", "name": "LandingAI Agentic Document Extraction", "vendor": "LandingAI, Inc.", "vendorUrl": "https://landing.ai", "kind": "http-api", "category": "document-extraction", "summary": "LandingAI's Agentic Document Extraction is a hosted API that parses PDFs, images, Office files and spreadsheets into Markdown with page coordinates, then extracts fields against a JSON schema. Python and TypeScript libraries and a CLI call it.", "url": "https://www.anchorterminal.com/tools/landingai-agentic-document-extraction", "markdownUrl": "https://www.anchorterminal.com/tools/landingai-agentic-document-extraction.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/landingai-agentic-document-extraction.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/landingai-agentic-document-extraction.json", "repo": "https://github.com/landing-ai/ade-python", "license": "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", "transports": [ "http" ], "remoteUrl": "https://api.ade.landing.ai", "packages": [ { "registry": "pypi", "name": "landingai-ade" }, { "registry": "npm", "name": "landingai-ade" } ], "auth": "api-key", "authNotes": "A Bearer API key in the `Authorization` header, created by a person in the web app at ade.landing.ai after signup. Access is self-serve with no review. The Explore plan has one key, which cannot be deleted or revoked (support replaces a leaked key by email). Team and Enterprise organisations create several named keys and revoke them, and Admin and Developer roles decide who may revoke. Keys have no scopes and are specific to the US or EU deployment. Enterprise adds SSO and an IP allowlist. The CLI also accepts a browser login.", "pricing": "usage", "pricingNotes": "A credit costs $0.01 on the Explore and Team plans, and signup includes 1,000 free credits with no card, so an agent's owner can start without a contract. DPT-3 Pro parsing consumes 1 credit a page plus 0.5 credits per 1,000 output characters on the priority tier and half that on the standard tier. Extract is charged per input and output character, and Ground is free. Team plans start at $250 a month. Enterprise prices are on request (https://docs.landing.ai/ade/ade-pricing, checked 2026-10-09).", "priceSummary": "$0.01 / credit", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs index, the OpenAPI description or the pricing pages (checked 2026-10-09).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-10-09" }, "docsUrl": "https://docs.landing.ai/dpt3/overview", "llmsTxt": "https://docs.landing.ai/llms.txt", "openapi": "https://docs.landing.ai/dpt3/openapi-adev2.json", "capabilities": [ "docs.parse", "docs.extract", "docs.tables", "docs.ocr", "docs.chunk", "docs.classify" ], "tags": [ "hosted", "api-key", "openapi", "llms-txt", "python", "typescript", "cli", "webhooks", "async-jobs", "eu-region", "status-page", "soc2", "closed-source" ], "lastRelease": "2026-09-22", "graded": true, "anchor": { "graded": true, "score": 69, "grade": "B", "agentReady": false, "rank": 199, "ranked": true, "rankOf": 950, "categoryRank": 3, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 75, "maintenance": 85, "payments": 40, "reliability": 85, "schema": 88, "security": 43, "transparency": 63 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-09" }, "negative": 0, "verdict": "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.", "bestFor": "Agents that need Markdown with block-level page coordinates and schema extraction with citations, in the US or EU.", "strengths": [ "Public OpenAPI 3.1 description of the nine Gen2 operations, `llms.txt`, `llms-full.txt` and a Markdown twin of every docs page", "Credit rates published per page and per 1,000 characters, and each response reports the credits it consumed in `metadata.billing`", "1,000 free credits on signup with no card, then $0.01 a credit on the Explore and Team plans", "status.landing.ai lists US and EU components for the product and no incident since 30 April 2026", "Troubleshooting pages list each status code and 422 message with its cause and fix, and say when credits are not consumed" ], "weaknesses": [ "The Explore plan has one API key that cannot be deleted or revoked. A leaked key is replaced by emailing support", "The published terms let LandingAI use customer materials and output to train its models. Zero Data Retention, which stops that, is a Team and Enterprise setting", "The terms forbid accessing the Solution through any agent, robot or tool LandingAI does not supply, and forbid benchmarking. This matters before any probe is run", "No idempotency key on job creation and no `Retry-After` header in the reviewed documentation", "No scoped or read-only keys, and no prompt-injection guidance for parsed document text was found", "The 18-hour-55-minute parsing incident of 30 April 2026 and two in February and March 2026 were attributed to a cloud provider" ], "agentNotes": [ "Send `Authorization: Bearer \u003ckey\u003e` to `https://api.ade.landing.ai/v2/parse`. EU keys work only on `https://api.ade.eu-west-1.landing.ai`", "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", "Leave jobs on the `standard` tier unless speed matters. It consumes half the credits of `priority`", "Run Extract on the Markdown that Parse returned, then call Ground for page numbers and boxes. Ground consumes no credits", "On a 429, read the message. One case clears with backoff and the other means the document is too large for the tier" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 69 } ], "editorialScores": { "ergonomics": 75, "maintenance": 85, "payments": 40, "reliability": 85, "schema": 88, "security": 43, "transparency": 49 }, "provenanceScore": 76 }, "connect": { "install": "pip install landingai-ade", "http": "curl -X POST 'https://api.ade.landing.ai/v2/parse' \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -F 'document=@document.pdf' \\\n -F 'model=dpt-3-pro-latest'", "claudeCode": "/plugin marketplace add landing-ai/ade-document-processing-skills\n/plugin install ade-document-processing@ade-document-processing-skills" }, "letme": { "capability": "https://letme.dev/docs.parse", "tool": "https://letme.dev/landingai-agentic-document-extraction" }, "area": "web-data", "unitPrices": [ { "item": "Credit (Explore and Team plans)", "unit": "credit", "usd": 0.01, "note": "1,000 free credits on signup" }, { "item": "DPT-3 Pro parse, standard tier, typical business page", "unit": "1k-pages", "usd": 15, "note": "vendor's median of 1.5 credits a page. Actual use is 0.5 credits a page plus 0.25 per 1,000 output characters" }, { "item": "Team plan, smallest credit pack", "unit": "month", "usd": 250, "note": "25,000 credits a month" } ], "provenance": { "legalEntity": "LandingAI, Inc.", "domain": "landing.ai", "domainRegistered": "2017-12-15", "endpointOnVendorDomain": true, "terms": "https://landing.ai/va-tos", "privacy": "https://landing.ai/privacy-policy", "statusPage": "https://status.landing.ai", "changelog": "https://docs.landing.ai/dpt3/changelog", "securityTxt": "none", "checked": "2026-10-09", "notes": [ "https://landing.ai/va-tos is titled Terms of Service (Agentic Document Extraction \u0026 Agentic Object Detection), names LandingAI, Inc., and carries no date. It is governed by California law.", "https://landing.ai/terms-of-service (last updated 6 May 2024) covers the platform services and LandingLens and says a Master Subscription Agreement supersedes it where one exists.", "landing.ai/robots.txt disallows `/legal/msa-ade-US-2026-02-11` and `/legal/msa-ade-EU-2026-02-11`. We did not read them, so we could not confirm whether an agreement dated 11 February 2026 replaces the terms we link.", "The privacy policy covers website visitors, service users and clients, names a data protection lead and EU and UK representatives, and shows no effective date in the text our reader received.", "https://landing.ai/.well-known/security.txt returns 404. The libraries' SECURITY.md asks for reports through GitHub private vulnerability reporting or support@landing.ai.", "RDAP for landing.ai gives a registration date of 2017-12-15 and Key-Systems GmbH as registrar.", "The trust centre at trust.landing.ai is drawn by script and showed our reader only its title, so the sub-processor list and compliance reports were not read." ], "score": 76 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/landingai-agentic-document-extraction.json", "live": { "slug": "landingai-agentic-document-extraction", "probe": { "target": "https://api.ade.landing.ai", "method": "get", "lastAt": "2026-10-10T02:54:59.888349762Z", "lastOk": true, "lastStatus": 404, "lastMs": 304, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 301, "p95ms24h": 363, "samples24h": 115, "samples30d": 115, "days": [ { "date": "2026-10-09", "probes": 85, "ok": 85 }, { "date": "2026-10-10", "probes": 30, "ok": 30 } ] }, "vendorStatus": { "page": "https://status.landing.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-10-10T00:50:45.144124198Z" }, "versions": [ { "registry": "github", "name": "landing-ai/ade-python", "version": "v1.18.1", "released": "2026-09-17", "seenAt": "2026-10-09T17:01:18.849971761Z" }, { "registry": "npm", "name": "landingai-ade", "version": "2.13.1", "seenAt": "2026-10-09T17:01:18.017039484Z" }, { "registry": "pypi", "name": "landingai-ade", "version": "1.18.1", "released": "2026-09-17", "seenAt": "2026-10-09T17:01:17.817666514Z" } ], "githubStars": 1034, "npmWeekly": 5401, "pypiWeekly": 27686, "pages": [ { "url": "https://docs.landing.ai/dpt3/changelog", "kind": "changelog", "status": 200, "checkedAt": "2026-10-09T18:37:36.954323206Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "57bf76e17c06" }, { "url": "https://docs.landing.ai/ade/ade-pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-10-09T18:37:34.762764189Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "ad0ee52319b9" }, { "url": "https://landing.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-09T18:40:52.205925369Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "2592e638a214" }, { "url": "https://landing.ai/va-tos", "kind": "terms", "status": 200, "checkedAt": "2026-10-09T18:40:54.687010711Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "0b8a537d9745" } ], "updatedAt": "2026-10-10T02:54:59.888349762Z" } }, "answer": "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.", "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": "2026-10-10T02:55:03.105289645Z", "lastOk": true, "lastStatus": 404, "lastMs": 432, "authRequired": false, "uptime24h": 99.6, "uptime30d": 99.55, "p50ms24h": 450, "p95ms24h": 505, "samples24h": 249, "samples30d": 2466, "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": 30, "ok": 30 } ] }, "vendorStatus": { "page": "https://status.nanonets.com", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-10T02:50:28.562140159Z" }, "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": "2026-10-10T02:55:03.105289645Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "LandingAI, Inc.", "b": "Nanonets", "name": "Vendor" }, { "a": "https://api.ade.landing.ai", "b": "https://extraction-api.nanonets.com/api/v2", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP, Streamable HTTP", "name": "Transports" }, { "a": "API key", "b": "OAuth or key", "name": "Auth" }, { "a": "Pay per use", "b": "Freemium", "name": "Pricing" }, { "a": "$15 per 1,000 pages", "b": "not published", "name": "Price for document parsing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "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", "b": "MIT (docstrange library)", "name": "Licence" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "2026-09-22", "b": "2025-10-31", "name": "Last release" }, { "a": "no date given", "b": "2020-12-02", "name": "Terms last updated" }, { "a": "no date given", "b": "2026-07-22", "name": "Privacy policy last updated" }, { "a": "yes", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "not found in the text", "name": "Terms restrict automated access" }, { "a": "yes", "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": "none", "b": "1.6k stars, 47 PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "2/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "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.", "question": "Which is better for AI agents, LandingAI Agentic Document Extraction or Nanonets API + MCP?" }, { "answer": "LandingAI Agentic Document Extraction needs an API key. Nanonets API + MCP takes an API key or an OAuth sign-in.", "question": "Do LandingAI Agentic Document Extraction and Nanonets API + MCP need an API key?" }, { "answer": "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.", "question": "Can an agent call LandingAI Agentic Document Extraction and Nanonets API + MCP without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 85 against 45", "Schema \u0026 documentation, 88 against 61", "Agent ergonomics, 75 against 47", "Security \u0026 auth, 43 against 30", "Payments \u0026 pricing, 40 against 35", "Maintenance \u0026 community, 85 against 8" ], "also": null, "goodFor": "Agents that need Markdown with block-level page coordinates and schema extraction with citations, in the US or EU.", "slug": "landingai-agentic-document-extraction", "watchFor": "The Explore plan has one API key that cannot be deleted or revoked. A leaked key is replaced by emailing support" }, { "aheadOn": null, "also": [ "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-landingai-agentic-document-extraction.json", "title": "Adobe PDF Services / PDF Extract API vs LandingAI Agentic Document Extraction", "url": "https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-landingai-agentic-document-extraction" }, { "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-landingai-agentic-document-extraction.json", "title": "Amazon Textract vs LandingAI Agentic Document Extraction", "url": "https://www.anchorterminal.com/compare/amazon-textract-vs-landingai-agentic-document-extraction" }, { "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-landingai-agentic-document-extraction.json", "title": "Azure Document Intelligence vs LandingAI Agentic Document Extraction", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-landingai-agentic-document-extraction" }, { "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-landingai-agentic-document-extraction.json", "title": "Extend API + MCP vs LandingAI Agentic Document Extraction", "url": "https://www.anchorterminal.com/compare/extend-vs-landingai-agentic-document-extraction" }, { "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-nanonets.json", "title": "Google Cloud Document AI vs Nanonets API + MCP", "url": "https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-nanonets" }, { "json": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-llamaparse.json", "title": "LandingAI Agentic Document Extraction vs LlamaParse API + MCP", "url": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-llamaparse" }, { "json": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-mistral-ocr.json", "title": "LandingAI Agentic Document Extraction vs Mistral OCR API", "url": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-mistral-ocr" }, { "json": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-opendocrouter.json", "title": "LandingAI Agentic Document Extraction vs OpenDocRouter", "url": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-opendocrouter" }, { "json": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-reducto.json", "title": "LandingAI Agentic Document Extraction vs Reducto API + MCP", "url": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-reducto" }, { "json": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-unstructured.json", "title": "LandingAI Agentic Document Extraction vs Unstructured API + MCP", "url": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-unstructured" }, { "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/landingai-agentic-document-extraction-vs-mindee.json", "title": "LandingAI Agentic Document Extraction vs Mindee API", "url": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-mindee" }, { "json": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-veryfi.json", "title": "LandingAI Agentic Document Extraction vs Veryfi API + MCP", "url": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-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/invofox-vs-landingai-agentic-document-extraction.json", "title": "Invofox vs LandingAI Agentic Document Extraction", "url": "https://www.anchorterminal.com/compare/invofox-vs-landingai-agentic-document-extraction" }, { "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": 40, "edge": "landingai-agentic-document-extraction", "key": "reliability", "landingai-agentic-document-extraction": 85, "name": "Reliability", "nanonets": 45, "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 27, "edge": "landingai-agentic-document-extraction", "key": "schema", "landingai-agentic-document-extraction": 88, "name": "Schema \u0026 documentation", "nanonets": 61, "weight": 13 }, { "by": 28, "edge": "landingai-agentic-document-extraction", "key": "ergonomics", "landingai-agentic-document-extraction": 75, "name": "Agent ergonomics", "nanonets": 47, "weight": 13 }, { "by": 13, "edge": "landingai-agentic-document-extraction", "key": "security", "landingai-agentic-document-extraction": 43, "name": "Security \u0026 auth", "nanonets": 30, "weight": 14 }, { "by": 5, "edge": "landingai-agentic-document-extraction", "key": "payments", "landingai-agentic-document-extraction": 40, "name": "Payments \u0026 pricing", "nanonets": 35, "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 77, "edge": "landingai-agentic-document-extraction", "key": "maintenance", "landingai-agentic-document-extraction": 85, "name": "Maintenance \u0026 community", "nanonets": 8, "weight": 7 }, { "by": 2, "edge": "nanonets", "key": "transparency", "landingai-agentic-document-extraction": 63, "name": "Transparency \u0026 trust", "nanonets": 65, "weight": 7 } ], "summary": "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.", "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": "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/landingai-agentic-document-extraction-vs-nanonets", "json": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.md", "slim": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets.min.md" }, "markdown": "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.\n\n- 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\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### LandingAI Agentic Document Extraction (B)\n\nGood for: Agents that need Markdown with block-level page coordinates and schema extraction with citations, in the US or EU.\n\nAhead on:\n- Reliability, 85 against 45\n- Schema \u0026 documentation, 88 against 61\n- Agent ergonomics, 75 against 47\n- Security \u0026 auth, 43 against 30\n- Payments \u0026 pricing, 40 against 35\n- Maintenance \u0026 community, 85 against 8\n\nWatch for: The Explore plan has one API key that cannot be deleted or revoked. A leaked key is replaced by emailing support\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\nAlso in its favour:\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 | LandingAI Agentic Document Extraction | Nanonets API + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 85 | 45 | LandingAI Agentic Document Extraction +40 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 88 | 61 | LandingAI Agentic Document Extraction +27 |\n| Agent ergonomics | 13% (16.2 this run) | 75 | 47 | LandingAI Agentic Document Extraction +28 |\n| Security \u0026 auth | 14% (17.5 this run) | 43 | 30 | LandingAI Agentic Document Extraction +13 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 35 | LandingAI Agentic Document Extraction +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 85 | 8 | LandingAI Agentic Document Extraction +77 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 63 | 65 | Nanonets API + MCP +2 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **69 · B** | **42.6 · E** | |\n\n## Facts side by side\n\n| Fact | LandingAI Agentic Document Extraction | Nanonets API + MCP |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | LandingAI, Inc. | Nanonets |\n| Hosted endpoint | `https://api.ade.landing.ai` | `https://extraction-api.nanonets.com/api/v2` |\n| Transports | HTTP | HTTP, Streamable HTTP |\n| Auth | API key | OAuth or key |\n| Pricing | Pay per use | Freemium |\n| Price for document parsing | $15 per 1,000 pages | not published |\n| x402 | no | no |\n| 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) |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| Last release | 2026-09-22 | 2025-10-31 |\n| Terms last updated | no date given | 2020-12-02 |\n| Privacy policy last updated | no date given | 2026-07-22 |\n| Customer content may train models | yes | not found in the text |\n| Terms restrict automated access | yes | not found in the text |\n| Terms restrict benchmarking | yes | 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 | none | 1.6k stars, 47 PyPI/wk |\n| Agent reviews | none | 2/5 (2) |\n\n## Verdicts\n\n**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.\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### LandingAI Agentic Document Extraction\n\n1. Send `Authorization: Bearer \u003ckey\u003e` to `https://api.ade.landing.ai/v2/parse`. EU keys work only on `https://api.ade.eu-west-1.landing.ai`\n2. 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\n3. Leave jobs on the `standard` tier unless speed matters. It consumes half the credits of `priority`\n4. Run Extract on the Markdown that Parse returned, then call Ground for page numbers and boxes. Ground consumes no credits\n5. On a 429, read the message. One case clears with backoff and the other means the document is too large for the tier\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, LandingAI Agentic Document Extraction or Nanonets API + MCP?\n\nLandingAI 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.\n\n### Do LandingAI Agentic Document Extraction and Nanonets API + MCP need an API key?\n\nLandingAI Agentic Document Extraction needs an API key. Nanonets API + MCP takes an API key or an OAuth sign-in.\n\n### Can an agent call LandingAI Agentic Document Extraction and Nanonets API + MCP without installing anything?\n\nYes. 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.\n\n\n## For agents\n\n- 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\n- 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`\n- 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\n\n## Other comparisons with LandingAI Agentic Document Extraction or Nanonets API + MCP\n\n- [Adobe PDF Services / PDF Extract API vs LandingAI Agentic Document Extraction](https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-landingai-agentic-document-extraction.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 LandingAI Agentic Document Extraction](https://www.anchorterminal.com/compare/amazon-textract-vs-landingai-agentic-document-extraction.md)\n- [Amazon Textract vs Nanonets API + MCP](https://www.anchorterminal.com/compare/amazon-textract-vs-nanonets.md)\n- [Azure Document Intelligence vs LandingAI Agentic Document Extraction](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-landingai-agentic-document-extraction.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 LandingAI Agentic Document Extraction](https://www.anchorterminal.com/compare/extend-vs-landingai-agentic-document-extraction.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 Nanonets API + MCP](https://www.anchorterminal.com/compare/google-cloud-document-ai-vs-nanonets.md)\n- [LandingAI Agentic Document Extraction vs LlamaParse API + MCP](https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-llamaparse.md)\n- [LandingAI Agentic Document Extraction vs Mistral OCR API](https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-mistral-ocr.md)\n- [LandingAI Agentic Document Extraction vs OpenDocRouter](https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-opendocrouter.md)\n- [LandingAI Agentic Document Extraction vs Reducto API + MCP](https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-reducto.md)\n- [LandingAI Agentic Document Extraction vs Unstructured API + MCP](https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-unstructured.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- [LandingAI Agentic Document Extraction vs Mindee API](https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-mindee.md)\n- [LandingAI Agentic Document Extraction vs Veryfi API + MCP](https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-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- [Invofox vs LandingAI Agentic Document Extraction](https://www.anchorterminal.com/compare/invofox-vs-landingai-agentic-document-extraction.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": "LandingAI Agentic Document Extraction vs Nanonets API + MCP", "url": "" } ], "description": "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.", "facts": [ "LandingAI Agentic Document Extraction B 69", "Nanonets API + MCP E 42.6", "scores" ], "h1": "LandingAI Agentic Document Extraction vs Nanonets API + MCP", "image": "https://www.anchorterminal.com/assets/og/compare-landingai-agentic-document-extraction-vs-nanonets.png", "path": "/compare/landingai-agentic-document-extraction-vs-nanonets", "published": "2026-10-01", "section": "tools", "title": "LandingAI Agentic Document Extraction vs Nanonets for AI agents (2026)", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/landingai-agentic-document-extraction-vs-nanonets" }, "tokens": { "markdown": 2900, "slim": 730 }, "version": 1 }