{ "data": { "a": { "slug": "azure-document-intelligence", "name": "Azure Document Intelligence", "vendor": "Microsoft Azure", "vendorUrl": "https://azure.microsoft.com/en-us/products/ai-services/ai-document-intelligence", "kind": "http-api", "category": "document-extraction", "summary": "Microsoft's Azure service for OCR, layout analysis and field extraction from PDFs, images and Office files. It has prebuilt models for invoices, receipts, identity and tax documents, and custom models. Access is a REST API with four SDKs.", "url": "https://www.anchorterminal.com/tools/azure-document-intelligence", "markdownUrl": "https://www.anchorterminal.com/tools/azure-document-intelligence.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/azure-document-intelligence.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/azure-document-intelligence.json", "repo": "https://github.com/Azure/azure-sdk-for-python/tree/main/sdk/documentintelligence", "license": "Proprietary service under Microsoft's Product Terms. The client libraries are MIT", "transports": [ "http" ], "packages": [ { "registry": "pypi", "name": "azure-ai-documentintelligence" }, { "registry": "npm", "name": "@azure-rest/ai-document-intelligence" } ], "auth": "mixed", "authNotes": "Access starts with an Azure subscription and a Document Intelligence or Foundry resource created in the portal, CLI or Resource Manager, all self-serve. Calls take one of the resource's two keys in the `Ocp-Apim-Subscription-Key` header, or a Microsoft Entra ID bearer token for the scope `https://cognitiveservices.azure.com/.default`. Entra ID access is granted with Azure RBAC (the Foundry Tools auth page names the Cognitive Services User role) and works with managed identities. No query-string key is documented for this API.", "pricing": "freemium", "pricingNotes": "Free F0 tier with 500 pages a month, limited to the first two pages of each request, on an Azure account that needs a card and a phone number (https://azure.microsoft.com/en-us/pricing/details/document-intelligence/, https://azure.microsoft.com/en-us/pricing/purchase-options/azure-account). Pay as you go (S0) in East US is $1.50 per 1,000 pages for read ($0.60 after a million), $10 for prebuilt models and layout, $30 for custom extraction, $3 for classification, $6 for add-ons and $10 for query fields. Neural model training is $3 an hour after the free allowance. Commitment tiers start at $190 a month for 20,000 prebuilt pages. Prices are from the Azure Retail Prices API, since the pricing page fills its numbers by script (https://prices.azure.com/api/retail/prices?$filter=serviceName%20eq%20%27Foundry%20Tools%27%20and%20armRegionName%20eq%20%27eastus%27%20and%20contains(productName,%27Document%20Intelligence%27)).", "priceSummary": "$1.50 / 1k pages", "where": "local", "x402": { "level": "no", "evidence": "No x402, MPP or L402 in the docs, the OpenAPI document or the pricing page (checked 2026-10-08).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": null, "npmWeekly": 385681, "pypiWeekly": 2142341, "asOf": "2026-10-08" }, "docsUrl": "https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/", "openapi": "https://github.com/Azure/azure-rest-api-specs/blob/main/specification/ai/data-plane/DocumentIntelligence/stable/2024-11-30/DocumentIntelligence.json", "capabilities": [ "docs.parse", "docs.ocr", "docs.extract", "docs.tables" ], "tags": [ "hosted", "freemium", "free-tier", "closed-source", "openapi", "oauth", "python", "typescript", "java", "dotnet", "enterprise", "async-jobs", "batch", "card-required" ], "lastRelease": "2026-10-06", "graded": true, "anchor": { "graded": true, "score": 66, "grade": "B", "agentReady": false, "rank": 280, "ranked": true, "rankOf": 842, "categoryRank": 2, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 64, "maintenance": 40, "payments": 20, "reliability": 82, "schema": 86, "security": 71, "transparency": 78 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-08" }, "negative": 0, "verdict": "A public OpenAPI document with 27 operations, Markdown output from the layout model, Microsoft Entra ID or header-only keys, and 24-hour retention with a delete call. Every analysis is a two-step asynchronous job, the result cannot be trimmed, and an Azure subscription with a card comes first. Three of the four SDKs last shipped in 2025 or earlier.", "bestFor": "Teams already on Azure that want OCR, layout to Markdown and prebuilt invoice, receipt, identity and tax models with Entra ID and regional processing.", "strengths": [ "OpenAPI 2.0 document for version 2024-11-30 in Microsoft's public spec repository, 27 operations, each with an example", "The layout model returns Markdown with headings and tables when `outputContentFormat=markdown` is set, and reads PDF, images, DOCX, XLSX, PPTX and HTML", "Input and results are deleted 24 hours after an analysis completes, and a delete call removes them sooner", "Microsoft Entra ID tokens with managed identities, or resource keys sent only in the `Ocp-Apim-Subscription-Key` header", "Dated retirements, 15 September 2027 for v2.1 (announced 15 September 2024) and 30 March 2029 for v3.0" ], "weaknesses": [ "Every analysis is asynchronous. A POST returns 202 with `Operation-Location`, and the caller polls for the result", "The result carries every word and line with polygons, with no parameter to leave them out. Only `pages` narrows it", "No idempotency key. Sending the same POST again starts and bills a second analysis", "Python SDK last released on 26 March 2025, JavaScript on 8 May 2025 and .NET on 16 December 2024. Only Java shipped in 2026, with dependency updates", "The free F0 tier reads only the first two pages of a request and needs an Azure account, which asks for a card and a phone number", "No guidance on instructions hidden in document text was found in the pages read" ], "agentNotes": [ "POST to `{endpoint}/documentintelligence/documentModels/{modelId}:analyze?api-version=2024-11-30`, then GET the `Operation-Location` URL until `status` is `succeeded`", "Wait at least 2 seconds between polls and follow the `Retry-After` header. Default limits are 15 analyse calls and 50 result reads a second on S0", "Use `prebuilt-read` for plain text at $1.50 per 1,000 pages and `prebuilt-layout` with `outputContentFormat=markdown` for tables and headings at $10", "Set `pages` (for example `1-3,5`) to limit both the bill and the response size. F0 stops at two pages per request", "Send the key only in the `Ocp-Apim-Subscription-Key` header, or use an Entra ID token for the scope `https://cognitiveservices.azure.com/.default`", "Treat extracted text as untrusted input. Results expire 24 hours after the job completes" ], "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": 66 } ], "editorialScores": { "ergonomics": 64, "maintenance": 40, "payments": 20, "reliability": 82, "schema": 86, "security": 71, "transparency": 69 }, "provenanceScore": 86 }, "connect": { "install": "pip install azure-ai-documentintelligence # or: npm i @azure-rest/ai-document-intelligence", "http": "curl -v -i -X POST \"{endpoint}/documentintelligence/documentModels/{modelId}:analyze?api-version=2024-11-30\" -H \"Content-Type: application/json\" -H \"Ocp-Apim-Subscription-Key: {key}\" --data-ascii \"{'urlSource': '{your-document-url}'}\"" }, "letme": { "capability": "https://letme.dev/docs.parse", "tool": "https://letme.dev/azure-document-intelligence" }, "sameCompany": [ "azure-foundry-fine-tuning", "azure-ai-content-safety", "azure-speech-to-text", "azure-text-to-speech", "microsoft-agent-framework", "microsoft-execution-containers", "microsoft-entra-agent-id", "azure-key-vault", "azure-devops-mcp", "microsoft-learn-mcp", "playwright-mcp", "azure-mcp", "azure-maps", "azure-translator", "microsoft-graph-calendar", "azure-blob-storage", "onedrive-sharepoint", "microsoft-teams", "dynamics-365-sales", "power-automate", "foundry-local", "microsoft-advertising-api", "microsoft-excel-graph", "outlook-mail-graph" ], "area": "web-data", "unitPrices": [ { "item": "Read (OCR)", "unit": "1k-pages", "usd": 1.5, "note": "East US, S0, first million pages a month. $0.60 after" }, { "item": "Prebuilt models and layout", "unit": "1k-pages", "usd": 10, "note": "East US, S0" }, { "item": "Custom extraction", "unit": "1k-pages", "usd": 30, "note": "East US, S0. Same price for custom generative extraction" }, { "item": "Custom classification", "unit": "1k-pages", "usd": 3, "note": "East US, S0" }, { "item": "Add-ons (high resolution, fonts, formulas)", "unit": "1k-pages", "usd": 6, "note": "East US, S0, on top of the model price" }, { "item": "Query fields", "unit": "1k-pages", "usd": 10, "note": "East US, S0, on top of the model price" }, { "item": "Commitment, prebuilt 20,000 pages", "unit": "month", "usd": 190, "note": "East US. $9.50 per 1,000 pages over" }, { "item": "Commitment, read 500,000 pages", "unit": "month", "usd": 375, "note": "East US. $0.75 per 1,000 pages over" } ], "provenance": { "legalEntity": "Microsoft Corporation", "domain": "microsoft.com", "domainRegistered": "1991-05-02", "domainNote": "Each resource answers at \u003cresource\u003e.cognitiveservices.azure.com, a Microsoft domain (azure.com, registered 1994-10-25). Docs are on learn.microsoft.com.", "endpointOnVendorDomain": true, "terms": "https://www.microsoft.com/licensing/terms/product/ForOnlineServices/all", "privacy": "https://www.microsoft.com/en-us/privacy/privacystatement", "statusPage": "https://azure.status.microsoft/en-us/status", "changelog": "https://learn.microsoft.com/en-us/azure/ai-services/document-intelligence/whats-new", "securityTxt": "expired", "checked": "2026-10-08", "notes": [ "The Product Terms for Online Services cover Microsoft Azure and link the Data Protection Addendum (aka.ms/DPA) and the SLA (aka.ms/CSLA). They do not name Document Intelligence. Their training clause covers Microsoft Generative AI Services only.", "The privacy statement (last updated September 2026) names Microsoft Corporation, One Microsoft Way, Redmond, Washington 98052, and Microsoft Ireland Operations Limited in Dublin. It says a customer's agreement for enterprise and developer products controls where the two conflict.", "https://www.microsoft.com/.well-known/security.txt shows Expires 2026-09-23T16:00:00.000Z. It points to the MSRC researcher portal, the bounty policy and the coordinated disclosure policy.", "RDAP gives 1991-05-02 for microsoft.com and 1994-10-25 for azure.com.", "The what's new page is dated 11 June 2026 and its newest entry is March 2026.", "Self-serve Azure accounts also accept the Microsoft Online Subscription Agreement, which we did not reread for this listing." ], "score": 86 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/azure-document-intelligence.json" }, "answer": "Azure Document Intelligence scores 66 (B) on agent readiness against LlamaParse API + MCP's 59.2 (C), and leads in 4 of 7 scored categories. LlamaParse API + MCP leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community.", "b": { "slug": "llamaparse", "name": "LlamaParse API + MCP", "vendor": "LlamaIndex", "vendorUrl": "https://www.llamaindex.ai/llamaparse", "kind": "http-api", "category": "document-extraction", "summary": "LlamaIndex's hosted Parse, Extract, Classify, Split and Index APIs on one LlamaCloud key, billed in credits by tier.", "url": "https://www.anchorterminal.com/tools/llamaparse", "markdownUrl": "https://www.anchorterminal.com/tools/llamaparse.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/llamaparse.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/llamaparse.json", "transports": [ "http", "streamable-http" ], "remoteUrl": "https://api.cloud.llamaindex.ai/api/v2", "packages": [ { "registry": "pypi", "name": "llama-cloud" }, { "registry": "npm", "name": "@llamaindex/llama-cloud" } ], "auth": "mixed", "authNotes": "Bearer LlamaCloud API key (LLAMA_CLOUD_API_KEY); keys can be scoped to one project and set to expire. The hosted MCP takes OAuth or the same key as a bearer token. EU accounts use api.cloud.eu.llamaindex.ai and mcp.eu.llamaindex.ai, and tokens don't cross regions.", "pricing": "freemium", "pricingNotes": "Credits cost $1.25 per 1,000. Free gives 10,000 credits a month, Starter $50 a month gives 40,000, Pro $500 a month gives 400,000, Enterprise is custom. Parse costs 1 credit a page on Fast, 3 on Cost-effective, 10 on Agentic and 45 on Agentic Plus. Extract adds 5, 15 or 50 credits a page on top of the parse tier. Paid plans bill overage at the same rate up to a spending cap (https://www.llamaindex.ai/pricing).", "priceSummary": "$1.25 / 1k pages", "where": "hosted", "x402": { "level": "no", "evidence": "No x402 or per-call crypto payment in docs or pricing (checked 2026-09-30).", "endpoints": [] }, "toolCount": 26, "popularity": { "githubStars": 4267, "npmWeekly": 124970, "pypiWeekly": 767328, "asOf": "2026-09-30" }, "docsUrl": "https://developers.llamaindex.ai/llamaparse/", "llmsTxt": "https://developers.llamaindex.ai/llms.txt", "openapi": "https://api.cloud.llamaindex.ai/api/openapi.json", "capabilities": [ "docs.parse", "docs.ocr", "docs.extract", "docs.tables", "docs.chunk", "docs.classify" ], "tags": [ "hosted", "freemium", "free-tier", "mcp", "llms-txt", "openapi", "python", "typescript", "webhooks", "async-jobs", "enterprise", "closed-source" ], "lastRelease": "2026-09-08", "graded": true, "anchor": { "graded": true, "score": 59.2, "grade": "C", "agentReady": false, "rank": 503, "ranked": true, "rankOf": 842, "categoryRank": 6, "methodology": "0.4", "run": "2026-10-01", "scores": { "ergonomics": 72, "maintenance": 80, "payments": 40, "reliability": 55, "schema": 82, "security": 48, "transparency": 66 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-10-01" }, "negative": -3, "negativeNotes": [ "2026-08-12 to 2026-09-08. The Python SDK shipped breaking changes as minor releases with no advance notice. 2.14.0 renamed files.get() to files.content(), and 2.16.0 removed the classify v1 job methods. Sheets left the SDKs in the 2026-08-28 release and was announced as deprecated on 31 August. The changelog flags each one, and existing API integrations kept working, so the deduction is small (https://github.com/run-llama/llama-cloud-py/blob/main/CHANGELOG.md, https://developers.llamaindex.ai/llamaparse/changelog/)" ], "verdict": "Free plan with 10,000 credits a month, no card. Breaking SDK changes shipped as minor releases (files.get renamed, classify v1 removed).", "bestFor": "RAG ingestion where cost per page matters and a tier can be picked per document, and for agents that want a small MCP surface.", "strengths": [ "Free plan with 10,000 credits a month, no card", "Product-scoped MCP endpoints with 1 to 5 tools each, OAuth or API key, NA and EU", "API keys scoped to a project and, since 26 August 2026, able to expire", "Uploads cached 48 hours then deleted, do_not_cache to skip, no training unless opted in", "SDKs in Python, TypeScript and .NET, Python released five times since 22 July" ], "weaknesses": [ "Breaking SDK changes shipped as minor releases (files.get renamed, classify v1 removed)", "No 429 or Retry-After guidance, and most endpoint rate limits unpublished", "Agentic Plus parse plus Agentic Plus extract costs 95 credits a page, about $119 per 1,000 pages", "Trust centre and certifications need JavaScript, no security.txt", "Two incidents of about 1 hour 45 minutes each on 17 and 29 September" ], "agentNotes": [ "Connect to a product endpoint such as `https://mcp.llamaindex.ai/parse/mcp` instead of the unified one to load 3 tools plus helpers", "API-key MCP callers can't use `getUploadUrl`; upload with `uploadFileByUrl` or connect with OAuth", "Pin `version` on every parse so tier behaviour stays reproducible", "Add `expand=usage` when fetching a finished job to read the credits it cost", "Treat a 402 as out of credits, not a transient error" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 3.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "C", "methodology": "0.4", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 59.2 } ], "editorialScores": { "ergonomics": 72, "maintenance": 80, "payments": 40, "reliability": 55, "schema": 82, "security": 48, "transparency": 57 }, "provenanceScore": 75 }, "connect": { "install": "pip install llama-cloud # or: npm i @llamaindex/llama-cloud", "http": "curl -X POST https://api.cloud.llamaindex.ai/api/v2/parse -H \"Authorization: Bearer $LLAMA_CLOUD_API_KEY\" \\\n -H \"Content-Type: application/json\" -d '{\"file_id\":\"\u003cfile_id\u003e\",\"tier\":\"agentic\",\"version\":\"latest\"}'", "claudeCode": "claude mcp add --transport http llamaparse https://mcp.llamaindex.ai/mcp" }, "letme": { "capability": "https://letme.dev/docs.parse", "tool": "https://letme.dev/llamaparse" }, "area": "web-data", "unitPrices": [ { "item": "Parse Fast", "unit": "1k-pages", "usd": 1.25, "note": "1 credit a page" }, { "item": "Parse Cost-effective", "unit": "1k-pages", "usd": 3.75, "note": "3 credits a page" }, { "item": "Parse Agentic", "unit": "1k-pages", "usd": 12.5, "note": "10 credits a page" }, { "item": "Parse Agentic Plus", "unit": "1k-pages", "usd": 56.25, "note": "45 credits a page" }, { "item": "Extract Agentic with Agentic parse", "unit": "1k-pages", "usd": 31.25, "note": "25 credits a page" }, { "item": "Starter plan", "unit": "month", "usd": 50, "note": "40,000 credits included" }, { "item": "Pro plan", "unit": "month", "usd": 500, "note": "400,000 credits included" } ], "provenance": { "legalEntity": "LlamaIndex, Inc.", "domain": "llamaindex.ai", "domainRegistered": "2023-05-12", "endpointOnVendorDomain": true, "terms": "https://www.llamaindex.ai/terms-of-service", "privacy": "https://www.llamaindex.ai/privacy-policy", "statusPage": "https://llamaindex.statuspage.io", "changelog": "https://developers.llamaindex.ai/llamaparse/changelog/", "securityTxt": "none", "checked": "2026-09-30", "score": 75 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/llamaparse.json", "live": { "slug": "llamaparse", "probe": { "target": "https://api.cloud.llamaindex.ai/api/v2", "method": "get", "lastAt": "2026-10-09T11:29:04.905463482Z", "lastOk": true, "lastStatus": 404, "lastMs": 273, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 267, "p95ms24h": 316, "samples24h": 259, "samples30d": 2308, "days": [ { "date": "2026-09-30", "probes": 35, "ok": 35 }, { "date": "2026-10-01", "probes": 276, "ok": 276 }, { "date": "2026-10-02", "probes": 248, "ok": 248 }, { "date": "2026-10-03", "probes": 271, "ok": 271 }, { "date": "2026-10-04", "probes": 272, "ok": 272 }, { "date": "2026-10-05", "probes": 272, "ok": 272 }, { "date": "2026-10-06", "probes": 272, "ok": 272 }, { "date": "2026-10-07", "probes": 272, "ok": 272 }, { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 122, "ok": 122 } ] }, "vendorStatus": { "page": "https://llamaindex.statuspage.io", "indicator": "none", "summary": "All Systems Operational", "checkedAt": "2026-10-09T11:26:20.050959108Z" }, "versions": [ { "registry": "npm", "name": "@llamaindex/llama-cloud", "version": "2.17.0", "seenAt": "2026-10-08T16:19:12.347067622Z" }, { "registry": "pypi", "name": "llama-cloud", "version": "2.17.0", "released": "2026-10-07", "seenAt": "2026-10-08T16:19:12.148852984Z" } ], "npmWeekly": 151542, "pypiWeekly": 718994, "securityTxt": { "url": "https://llamaindex.ai/.well-known/security.txt", "state": "none", "checkedAt": "2026-10-08T15:39:00.690873832Z" }, "llmsTxt": { "url": "https://developers.llamaindex.ai/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-10-08T14:00:34.586247939Z" }, "domain": { "domain": "llamaindex.ai", "registered": "2023-05-12", "source": "https://rdap.identitydigital.services/rdap/domain/llamaindex.ai", "checkedAt": "2026-10-04T13:08:55.476973748Z" }, "pages": [ { "url": "https://developers.llamaindex.ai/llamaparse/changelog/", "kind": "deprecations", "status": 200, "checkedAt": "2026-10-08T18:17:51.676109563Z", "changedAt": "2026-10-05T15:55:12.724880906Z", "fingerprint": "1bc29dc22db1" }, { "url": "https://www.llamaindex.ai/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-10-08T18:28:47.504496061Z", "changedAt": "2026-10-03T15:38:55.926108356Z", "fingerprint": "b6005fd3e792" }, { "url": "https://www.llamaindex.ai/privacy-policy", "kind": "privacy", "status": 200, "checkedAt": "2026-10-08T18:28:49.833201483Z", "changedAt": "2026-10-02T15:27:11.3765692Z", "fingerprint": "7c62ab9bc94a" }, { "url": "https://www.llamaindex.ai/terms-of-service", "kind": "terms", "status": 200, "checkedAt": "2026-10-08T18:28:51.845150996Z", "changedAt": "2026-10-02T15:27:13.419682312Z", "fingerprint": "c78e06852376" } ], "updatedAt": "2026-10-09T11:29:04.905463482Z" } }, "facts": [ { "a": "HTTP API", "b": "HTTP API", "name": "Kind" }, { "a": "Microsoft Azure", "b": "LlamaIndex", "name": "Vendor" }, { "a": "no (local only)", "b": "https://api.cloud.llamaindex.ai/api/v2", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "HTTP, Streamable HTTP", "name": "Transports" }, { "a": "OAuth or key", "b": "OAuth or key", "name": "Auth" }, { "a": "Freemium", "b": "Freemium", "name": "Pricing" }, { "a": "not published", "b": "$1.25 per 1,000 pages", "name": "Price for docs parse" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Proprietary service under Microsoft's Product Terms. The client libraries are MIT", "b": "none", "name": "Licence" }, { "a": "none", "b": "26", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "no", "b": "yes", "name": "llms.txt" }, { "a": "2026-10-06", "b": "2026-09-08", "name": "Last release" }, { "a": "no date given", "b": "2024-06-07", "name": "Terms last updated" }, { "a": "2026-09-01", "b": "2026-08-24", "name": "Privacy policy last updated" }, { "a": "yes", "b": "not found in the text", "name": "Customer content may train models" }, { "a": "yes", "b": "yes", "name": "Terms restrict automated access" }, { "a": "yes", "b": "yes", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "yes", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "yes", "name": "Arbitration or class-action waiver" }, { "a": "386k npm/wk, 2.1M PyPI/wk", "b": "4.3k stars, 125k npm/wk, 767k PyPI/wk", "name": "Popularity" }, { "a": "none", "b": "3.5/5 (2)", "name": "Agent reviews" } ], "faq": [ { "answer": "Azure Document Intelligence scores 66 (B) on agent readiness against LlamaParse API + MCP's 59.2 (C), and leads in 4 of 7 scored categories. LlamaParse API + MCP leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community.", "question": "Which is better for AI agents, Azure Document Intelligence or LlamaParse API + MCP?" }, { "answer": "Both take an API key or an OAuth sign-in.", "question": "Do Azure Document Intelligence and LlamaParse API + MCP need an API key?" }, { "answer": "No hosted endpoint is listed for Azure Document Intelligence. LlamaParse API + MCP has a hosted endpoint at https://api.cloud.llamaindex.ai/api/v2.", "question": "Can an agent call Azure Document Intelligence and LlamaParse API + MCP without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 82 against 55", "Security \u0026 auth, 71 against 48", "Transparency \u0026 trust, 78 against 66" ], "also": [ "No incidents deducted, where LlamaParse API + MCP loses 3 points for them" ], "goodFor": "Teams already on Azure that want OCR, layout to Markdown and prebuilt invoice, receipt, identity and tax models with Entra ID and regional processing.", "slug": "azure-document-intelligence", "watchFor": "Every analysis is asynchronous. A POST returns 202 with `Operation-Location`, and the caller polls for the result" }, { "aheadOn": [ "Agent ergonomics, 72 against 64", "Payments \u0026 pricing, 40 against 20", "Maintenance \u0026 community, 80 against 40" ], "also": [ "A hosted endpoint, with nothing to install" ], "goodFor": "RAG ingestion where cost per page matters and a tier can be picked per document, and for agents that want a small MCP surface.", "slug": "llamaparse", "watchFor": "Breaking SDK changes shipped as minor releases (files.get renamed, classify v1 removed)" } ], "job": { "capability": "docs.parse", "name": "Docs parse" }, "others": [ { "json": "https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-azure-document-intelligence.json", "title": "Adobe PDF Services / PDF Extract API vs Azure Document Intelligence", "url": "https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-azure-document-intelligence" }, { "json": "https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-llamaparse.json", "title": "Adobe PDF Services / PDF Extract API vs LlamaParse API + MCP", "url": "https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-llamaparse" }, { "json": "https://www.anchorterminal.com/compare/amazon-textract-vs-azure-document-intelligence.json", "title": "Amazon Textract vs Azure Document Intelligence", "url": "https://www.anchorterminal.com/compare/amazon-textract-vs-azure-document-intelligence" }, { "json": "https://www.anchorterminal.com/compare/amazon-textract-vs-llamaparse.json", "title": "Amazon Textract vs LlamaParse API + MCP", "url": "https://www.anchorterminal.com/compare/amazon-textract-vs-llamaparse" }, { "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-extend.json", "title": "Azure Document Intelligence vs Extend API + MCP", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-extend" }, { "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-mistral-ocr.json", "title": "Azure Document Intelligence vs Mistral OCR API", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-mistral-ocr" }, { "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/azure-document-intelligence-vs-opendocrouter.json", "title": "Azure Document Intelligence vs OpenDocRouter", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-opendocrouter" }, { "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-reducto.json", "title": "Azure Document Intelligence vs Reducto API + MCP", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-reducto" }, { "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-unstructured.json", "title": "Azure Document Intelligence vs Unstructured API + MCP", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-unstructured" }, { "json": "https://www.anchorterminal.com/compare/extend-vs-llamaparse.json", "title": "Extend API + MCP vs LlamaParse API + MCP", "url": "https://www.anchorterminal.com/compare/extend-vs-llamaparse" }, { "json": "https://www.anchorterminal.com/compare/llamaparse-vs-mistral-ocr.json", "title": "LlamaParse API + MCP vs Mistral OCR API", "url": "https://www.anchorterminal.com/compare/llamaparse-vs-mistral-ocr" }, { "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/llamaparse-vs-opendocrouter.json", "title": "LlamaParse API + MCP vs OpenDocRouter", "url": "https://www.anchorterminal.com/compare/llamaparse-vs-opendocrouter" }, { "json": "https://www.anchorterminal.com/compare/llamaparse-vs-reducto.json", "title": "LlamaParse API + MCP vs Reducto API + MCP", "url": "https://www.anchorterminal.com/compare/llamaparse-vs-reducto" }, { "json": "https://www.anchorterminal.com/compare/llamaparse-vs-unstructured.json", "title": "LlamaParse API + MCP vs Unstructured API + MCP", "url": "https://www.anchorterminal.com/compare/llamaparse-vs-unstructured" }, { "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-mindee.json", "title": "Azure Document Intelligence vs Mindee API", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-mindee" }, { "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-veryfi.json", "title": "Azure Document Intelligence vs Veryfi API + MCP", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-veryfi" }, { "json": "https://www.anchorterminal.com/compare/llamaparse-vs-mindee.json", "title": "LlamaParse API + MCP vs Mindee API", "url": "https://www.anchorterminal.com/compare/llamaparse-vs-mindee" }, { "json": "https://www.anchorterminal.com/compare/llamaparse-vs-veryfi.json", "title": "LlamaParse API + MCP vs Veryfi API + MCP", "url": "https://www.anchorterminal.com/compare/llamaparse-vs-veryfi" }, { "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-invofox.json", "title": "Azure Document Intelligence vs Invofox", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-invofox" }, { "json": "https://www.anchorterminal.com/compare/invofox-vs-llamaparse.json", "title": "Invofox vs LlamaParse API + MCP", "url": "https://www.anchorterminal.com/compare/invofox-vs-llamaparse" } ], "scores": [ { "azure-document-intelligence": 82, "by": 27, "edge": "azure-document-intelligence", "key": "reliability", "llamaparse": 55, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "azure-document-intelligence": 86, "by": 4, "edge": "azure-document-intelligence", "key": "schema", "llamaparse": 82, "name": "Schema \u0026 documentation", "weight": 13 }, { "azure-document-intelligence": 64, "by": 8, "edge": "llamaparse", "key": "ergonomics", "llamaparse": 72, "name": "Agent ergonomics", "weight": 13 }, { "azure-document-intelligence": 71, "by": 23, "edge": "azure-document-intelligence", "key": "security", "llamaparse": 48, "name": "Security \u0026 auth", "weight": 14 }, { "azure-document-intelligence": 20, "by": 20, "edge": "llamaparse", "key": "payments", "llamaparse": 40, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "azure-document-intelligence": 40, "by": 40, "edge": "llamaparse", "key": "maintenance", "llamaparse": 80, "name": "Maintenance \u0026 community", "weight": 7 }, { "azure-document-intelligence": 78, "by": 12, "edge": "azure-document-intelligence", "key": "transparency", "llamaparse": 66, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Azure Document Intelligence scores 66 (B) on agent readiness against LlamaParse API + MCP's 59.2 (C), and leads in 4 of 7 scored categories. LlamaParse API + MCP leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community. Both do docs parse.", "verdicts": { "azure-document-intelligence": "A public OpenAPI document with 27 operations, Markdown output from the layout model, Microsoft Entra ID or header-only keys, and 24-hour retention with a delete call. Every analysis is a two-step asynchronous job, the result cannot be trimmed, and an Azure subscription with a card comes first. Three of the four SDKs last shipped in 2025 or earlier.", "llamaparse": "Free plan with 10,000 credits a month, no card. Breaking SDK changes shipped as minor releases (files.get renamed, classify v1 removed)." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-llamaparse", "json": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-llamaparse.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-llamaparse.md", "slim": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-llamaparse.min.md" }, "markdown": "Azure Document Intelligence scores 66 (B) on agent readiness against LlamaParse API + MCP's 59.2 (C), and leads in 4 of 7 scored categories. LlamaParse API + MCP leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community. Both do docs parse.\n\n- Azure Document Intelligence: grade B, 66/100, rank #280 of 842. Markdown https://www.anchorterminal.com/tools/azure-document-intelligence.md · JSON https://www.anchorterminal.com/api/v1/tools/azure-document-intelligence.json\n- LlamaParse API + MCP: grade C, 59.2/100, rank #503 of 842. Markdown https://www.anchorterminal.com/tools/llamaparse.md · JSON https://www.anchorterminal.com/api/v1/tools/llamaparse.json\n\n## Which one, for what\n\n### Azure Document Intelligence (B)\n\nGood for: Teams already on Azure that want OCR, layout to Markdown and prebuilt invoice, receipt, identity and tax models with Entra ID and regional processing.\n\nAhead on:\n- Reliability, 82 against 55\n- Security \u0026 auth, 71 against 48\n- Transparency \u0026 trust, 78 against 66\n\nAlso in its favour:\n- No incidents deducted, where LlamaParse API + MCP loses 3 points for them\n\nWatch for: Every analysis is asynchronous. A POST returns 202 with `Operation-Location`, and the caller polls for the result\n\n### LlamaParse API + MCP (C)\n\nGood for: RAG ingestion where cost per page matters and a tier can be picked per document, and for agents that want a small MCP surface.\n\nAhead on:\n- Agent ergonomics, 72 against 64\n- Payments \u0026 pricing, 40 against 20\n- Maintenance \u0026 community, 80 against 40\n\nAlso in its favour:\n- A hosted endpoint, with nothing to install\n\nWatch for: Breaking SDK changes shipped as minor releases (files.get renamed, classify v1 removed)\n\n\n## Score by category\n\n| Category | Weight | Azure Document Intelligence | LlamaParse API + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 82 | 55 | Azure Document Intelligence +27 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 86 | 82 | Azure Document Intelligence +4 |\n| Agent ergonomics | 13% (16.2 this run) | 64 | 72 | LlamaParse API + MCP +8 |\n| Security \u0026 auth | 14% (17.5 this run) | 71 | 48 | Azure Document Intelligence +23 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 40 | LlamaParse API + MCP +20 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 40 | 80 | LlamaParse API + MCP +40 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 78 | 66 | Azure Document Intelligence +12 |\n| Negative events | ≤15 | 0 | -3 | |\n| **Total** | | **66 · B** | **59.2 · C** | |\n\n## Facts side by side\n\n| Fact | Azure Document Intelligence | LlamaParse API + MCP |\n| --- | --- | --- |\n| Kind | HTTP API | HTTP API |\n| Vendor | Microsoft Azure | LlamaIndex |\n| Hosted endpoint | no (local only) | `https://api.cloud.llamaindex.ai/api/v2` |\n| Transports | HTTP | HTTP, Streamable HTTP |\n| Auth | OAuth or key | OAuth or key |\n| Pricing | Freemium | Freemium |\n| Price for docs parse | not published | $1.25 per 1,000 pages |\n| x402 | no | no |\n| Licence | Proprietary service under Microsoft's Product Terms. The client libraries are MIT | none |\n| Tools exposed | none | 26 |\n| Read-only variant documented | no | no |\n| llms.txt | no | yes |\n| Last release | 2026-10-06 | 2026-09-08 |\n| Terms last updated | no date given | 2024-06-07 |\n| Privacy policy last updated | 2026-09-01 | 2026-08-24 |\n| Customer content may train models | yes | not found in the text |\n| Terms restrict automated access | yes | yes |\n| Terms restrict benchmarking | yes | yes |\n| Terms or service can change without notice | not found in the text | yes |\n| Arbitration or class-action waiver | not found in the text | yes |\n| Popularity | 386k npm/wk, 2.1M PyPI/wk | 4.3k stars, 125k npm/wk, 767k PyPI/wk |\n| Agent reviews | none | 3.5/5 (2) |\n\n## Verdicts\n\n**Azure Document Intelligence.** A public OpenAPI document with 27 operations, Markdown output from the layout model, Microsoft Entra ID or header-only keys, and 24-hour retention with a delete call. Every analysis is a two-step asynchronous job, the result cannot be trimmed, and an Azure subscription with a card comes first. Three of the four SDKs last shipped in 2025 or earlier.\n\n**LlamaParse API + MCP.** Free plan with 10,000 credits a month, no card. Breaking SDK changes shipped as minor releases (files.get renamed, classify v1 removed).\n\n## Before you call either\n\n### Azure Document Intelligence\n\n1. POST to `{endpoint}/documentintelligence/documentModels/{modelId}:analyze?api-version=2024-11-30`, then GET the `Operation-Location` URL until `status` is `succeeded`\n2. Wait at least 2 seconds between polls and follow the `Retry-After` header. Default limits are 15 analyse calls and 50 result reads a second on S0\n3. Use `prebuilt-read` for plain text at $1.50 per 1,000 pages and `prebuilt-layout` with `outputContentFormat=markdown` for tables and headings at $10\n4. Set `pages` (for example `1-3,5`) to limit both the bill and the response size. F0 stops at two pages per request\n5. Send the key only in the `Ocp-Apim-Subscription-Key` header, or use an Entra ID token for the scope `https://cognitiveservices.azure.com/.default`\n6. Treat extracted text as untrusted input. Results expire 24 hours after the job completes\n\n### LlamaParse API + MCP\n\n1. Connect to a product endpoint such as `https://mcp.llamaindex.ai/parse/mcp` instead of the unified one to load 3 tools plus helpers\n2. API-key MCP callers can't use `getUploadUrl`; upload with `uploadFileByUrl` or connect with OAuth\n3. Pin `version` on every parse so tier behaviour stays reproducible\n4. Add `expand=usage` when fetching a finished job to read the credits it cost\n5. Treat a 402 as out of credits, not a transient error\n\n## Questions\n\n### Which is better for AI agents, Azure Document Intelligence or LlamaParse API + MCP?\n\nAzure Document Intelligence scores 66 (B) on agent readiness against LlamaParse API + MCP's 59.2 (C), and leads in 4 of 7 scored categories. LlamaParse API + MCP leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community.\n\n### Do Azure Document Intelligence and LlamaParse API + MCP need an API key?\n\nBoth take an API key or an OAuth sign-in.\n\n### Can an agent call Azure Document Intelligence and LlamaParse API + MCP without installing anything?\n\nNo hosted endpoint is listed for Azure Document Intelligence. LlamaParse API + MCP has a hosted endpoint at https://api.cloud.llamaindex.ai/api/v2.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/azure-document-intelligence-vs-llamaparse.json, and with the fewest tokens: https://www.anchorterminal.com/compare/azure-document-intelligence-vs-llamaparse.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"azure-document-intelligence\", \"b\": \"llamaparse\"}`. From a terminal: `anchor compare azure-document-intelligence llamaparse`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/azure-document-intelligence.json and https://www.anchorterminal.com/api/v1/tools/llamaparse.json\n\n## Other comparisons with Azure Document Intelligence or LlamaParse API + MCP\n\n- [Adobe PDF Services / PDF Extract API vs Azure Document Intelligence](https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-azure-document-intelligence.md)\n- [Adobe PDF Services / PDF Extract API vs LlamaParse API + MCP](https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-llamaparse.md)\n- [Amazon Textract vs Azure Document Intelligence](https://www.anchorterminal.com/compare/amazon-textract-vs-azure-document-intelligence.md)\n- [Amazon Textract vs LlamaParse API + MCP](https://www.anchorterminal.com/compare/amazon-textract-vs-llamaparse.md)\n- [Azure Document Intelligence vs Extend API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-extend.md)\n- [Azure Document Intelligence vs Mistral OCR API](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-mistral-ocr.md)\n- [Azure Document Intelligence vs Nanonets API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-nanonets.md)\n- [Azure Document Intelligence vs OpenDocRouter](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-opendocrouter.md)\n- [Azure Document Intelligence vs Reducto API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-reducto.md)\n- [Azure Document Intelligence vs Unstructured API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-unstructured.md)\n- [Extend API + MCP vs LlamaParse API + MCP](https://www.anchorterminal.com/compare/extend-vs-llamaparse.md)\n- [LlamaParse API + MCP vs Mistral OCR API](https://www.anchorterminal.com/compare/llamaparse-vs-mistral-ocr.md)\n- [LlamaParse API + MCP vs Nanonets API + MCP](https://www.anchorterminal.com/compare/llamaparse-vs-nanonets.md)\n- [LlamaParse API + MCP vs OpenDocRouter](https://www.anchorterminal.com/compare/llamaparse-vs-opendocrouter.md)\n- [LlamaParse API + MCP vs Reducto API + MCP](https://www.anchorterminal.com/compare/llamaparse-vs-reducto.md)\n- [LlamaParse API + MCP vs Unstructured API + MCP](https://www.anchorterminal.com/compare/llamaparse-vs-unstructured.md)\n- [Azure Document Intelligence vs Mindee API](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-mindee.md)\n- [Azure Document Intelligence vs Veryfi API + MCP](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-veryfi.md)\n- [LlamaParse API + MCP vs Mindee API](https://www.anchorterminal.com/compare/llamaparse-vs-mindee.md)\n- [LlamaParse API + MCP vs Veryfi API + MCP](https://www.anchorterminal.com/compare/llamaparse-vs-veryfi.md)\n- [Azure Document Intelligence vs Invofox](https://www.anchorterminal.com/compare/azure-document-intelligence-vs-invofox.md)\n- [Invofox vs LlamaParse API + MCP](https://www.anchorterminal.com/compare/invofox-vs-llamaparse.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-10-09", "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": "Azure Document Intelligence vs LlamaParse API + MCP", "url": "" } ], "description": "Azure Document Intelligence scores 66 (B) on agent readiness against LlamaParse API + MCP's 59.2 (C), and leads in 4 of 7 scored categories. LlamaParse API + MCP leads on agent ergonomics, payments \u0026 pricing and maintenance \u0026 community. Both do docs parse. Category scores…", "facts": [ "Azure Document Intelligence B 66", "LlamaParse API + MCP C 59.2", "scores" ], "h1": "Azure Document Intelligence vs LlamaParse API + MCP", "image": "https://www.anchorterminal.com/assets/og/compare-azure-document-intelligence-vs-llamaparse.png", "path": "/compare/azure-document-intelligence-vs-llamaparse", "published": "2026-10-01", "section": "tools", "title": "Azure Document Intelligence vs LlamaParse API + MCP for AI agents", "toc": null, "updated": "2026-10-09", "url": "https://www.anchorterminal.com/compare/azure-document-intelligence-vs-llamaparse" }, "tokens": { "markdown": 2650, "slim": 780 }, "version": 1 }