{
  "data": {
    "a": {
      "slug": "mistral-ocr",
      "name": "Mistral OCR API",
      "vendor": "Mistral AI",
      "vendorUrl": "https://mistral.ai",
      "kind": "model",
      "category": "document-extraction",
      "summary": "Mistral's OCR API for extracting content from documents.",
      "url": "https://www.anchorterminal.com/tools/mistral-ocr",
      "markdownUrl": "https://www.anchorterminal.com/tools/mistral-ocr.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/mistral-ocr.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/mistral-ocr.json",
      "repo": "https://github.com/mistralai/client-python",
      "license": "Apache-2.0 (SDKs)",
      "transports": [
        "http"
      ],
      "remoteUrl": "https://api.mistral.ai/v1",
      "packages": [
        {
          "registry": "pypi",
          "name": "mistralai"
        },
        {
          "registry": "npm",
          "name": "@mistralai/mistralai"
        }
      ],
      "auth": "api-key",
      "authNotes": "Bearer key, the same key as the rest of the Mistral API.",
      "pricing": "freemium",
      "pricingNotes": "OCR 4.1 is $4 per 1,000 pages, and $5 per 1,000 pages with Document AI annotations. OCR inside Libraries is $3 per 1,000 pages. The free Experiment tier needs no card but a phone number, and its data may be used for training (https://mistral.ai/pricing/api/).",
      "priceSummary": "$4 / 1k pages",
      "where": "hosted",
      "x402": {
        "level": "no",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": 769,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-09-26"
      },
      "docsUrl": "https://docs.mistral.ai/studio/document-processing/basic_ocr",
      "llmsTxt": "https://docs.mistral.ai/llms.txt",
      "openapi": "https://docs.mistral.ai/openapi.yaml",
      "capabilities": [
        "docs.parse",
        "docs.ocr",
        "docs.extract",
        "docs.tables"
      ],
      "tags": [
        "official",
        "hosted",
        "model",
        "eu",
        "free-tier",
        "openapi",
        "llms-txt",
        "python",
        "typescript"
      ],
      "lastRelease": "2026-08-31",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 59,
        "grade": "C",
        "agentReady": false,
        "rank": 271,
        "ranked": true,
        "rankOf": 452,
        "categoryRank": 5,
        "methodology": "0.3",
        "run": "2026-10-01",
        "scores": {
          "ergonomics": 83,
          "maintenance": 48,
          "payments": 40,
          "reliability": 45,
          "schema": 89,
          "security": 35,
          "transparency": 77
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "medium",
          "date": "2026-10-01"
        },
        "negative": 0,
        "verdict": "Single synchronous call returns Markdown per page, no upload step for public URLs. OCR API at 99.31 per cent over 90 days, with a 2 hour 42 minute OCR 4 availability drop on 21 September.",
        "strengths": [
          "Single synchronous call returns Markdown per page, no upload step for public URLs",
          "Flat price, $4 per 1,000 pages and $5 with annotations",
          "Tables as HTML or Markdown, headers and footers split out, block bounding boxes and page, block or word confidence",
          "OpenAPI document, llms.txt and Markdown guides from an EU-based vendor"
        ],
        "weaknesses": [
          "OCR API at 99.31 per cent over 90 days, with a 2 hour 42 minute OCR 4 availability drop on 21 September",
          "OCR 4.0 lasted about three months before retiring on 30 September",
          "Free tier data may be used for training",
          "Workspace keys can't be limited to OCR",
          "No official MCP server"
        ],
        "agentNotes": [
          "Pin `mistral-ocr-4-1` rather than `mistral-ocr-latest` if output format matters downstream",
          "Set `table_format` to `html` for tables with merged cells",
          "Leave `include_image_base64` off unless you need the images, it inflates the response",
          "Pass `pages` to OCR only the pages you need, since billing is per page",
          "Upload private files through `/v1/files` and pass the signed URL"
        ],
        "metrics": {
          "kind": "remote",
          "measured": false
        },
        "reviewCount": 2,
        "avgRating": 4.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "medium",
            "grade": "C",
            "methodology": "0.3",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 59
          }
        ],
        "editorialScores": {
          "ergonomics": 83,
          "maintenance": 48,
          "payments": 40,
          "reliability": 45,
          "schema": 89,
          "security": 35,
          "transparency": 57
        },
        "provenanceScore": 96
      },
      "connect": {
        "install": "pip install mistralai   # or: npm i @mistralai/mistralai",
        "http": "curl https://api.mistral.ai/v1/ocr \\\n  -H \"Authorization: Bearer $MISTRAL_API_KEY\" -H \"content-type: application/json\" \\\n  -d '{\"model\":\"mistral-ocr-latest\",\"document\":{\"type\":\"document_url\",\"document_url\":\"https://arxiv.org/pdf/2201.04234\"},\"table_format\":\"html\"}'"
      },
      "letme": {
        "capability": "https://letme.dev/docs.parse",
        "tool": "https://letme.dev/mistral-ocr"
      },
      "sameCompany": [
        "mistral-api",
        "mistral-embeddings",
        "mistral-moderation"
      ],
      "area": "web-data",
      "unitPrices": [
        {
          "item": "OCR 4.1 (mistral-ocr-4-1)",
          "unit": "1k-pages",
          "usd": 4
        },
        {
          "item": "OCR 4.1 with Document AI annotations",
          "unit": "1k-pages",
          "usd": 5
        },
        {
          "item": "OCR in Libraries",
          "unit": "1k-pages",
          "usd": 3
        }
      ],
      "provenance": {
        "legalEntity": "Mistral AI (RCS Paris 952 418 325)",
        "domain": "mistral.ai",
        "domainRegistered": "2019-05-15",
        "endpointOnVendorDomain": true,
        "terms": "https://legal.mistral.ai/terms/commercial-terms-of-service",
        "privacy": "https://legal.mistral.ai/terms/privacy-policy",
        "statusPage": "https://status.mistral.ai",
        "changelog": "https://docs.mistral.ai/resources/changelogs",
        "securityTxt": "valid",
        "checked": "2026-09-30",
        "score": 96
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/mistral-ocr.json",
      "live": {
        "slug": "mistral-ocr",
        "probe": {
          "target": "https://api.mistral.ai/v1",
          "method": "get",
          "lastAt": "2026-10-04T23:32:50.864867388Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 36,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 100,
          "p50ms24h": 42,
          "p95ms24h": 70,
          "samples24h": 272,
          "samples30d": 1097,
          "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": 267,
              "ok": 267
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.mistral.ai",
          "indicator": "unknown",
          "summary": "no machine-readable status found",
          "checkedAt": "2026-10-04T17:31:18.046141107Z"
        },
        "versions": [
          {
            "registry": "github",
            "name": "mistralai/client-python",
            "version": "v3.0.0",
            "released": "2026-09-28",
            "seenAt": "2026-10-04T16:33:34.980941253Z"
          },
          {
            "registry": "npm",
            "name": "@mistralai/mistralai",
            "version": "2.7.0",
            "seenAt": "2026-10-04T16:33:34.720358853Z"
          },
          {
            "registry": "pypi",
            "name": "mistralai",
            "version": "3.0.0",
            "released": "2026-09-28",
            "seenAt": "2026-10-04T16:33:34.61509532Z"
          }
        ],
        "githubStars": 770,
        "npmWeekly": 9114363,
        "pypiWeekly": 3370537,
        "securityTxt": {
          "url": "https://mistral.ai/.well-known/security.txt",
          "state": "valid",
          "expires": "2027-05-05T23:59:59.000Z",
          "checkedAt": "2026-10-04T15:15:48.706102345Z"
        },
        "llmsTxt": {
          "url": "https://docs.mistral.ai/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-04T15:18:04.898854598Z"
        },
        "domain": {
          "domain": "mistral.ai",
          "registered": "2019-05-15",
          "source": "https://rdap.identitydigital.services/rdap/domain/mistral.ai",
          "checkedAt": "2026-10-04T13:08:59.683466691Z"
        },
        "updatedAt": "2026-10-04T23:32:50.864867388Z"
      }
    },
    "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": 413,
        "ranked": true,
        "rankOf": 452,
        "categoryRank": 9,
        "methodology": "0.3",
        "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.",
        "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": "0.3",
            "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": "2026-10-04T23:32:50.98496352Z",
          "lastOk": true,
          "lastStatus": 404,
          "lastMs": 455,
          "authRequired": false,
          "uptime24h": 100,
          "uptime30d": 99.73,
          "p50ms24h": 447,
          "p95ms24h": 491,
          "samples24h": 272,
          "samples30d": 1097,
          "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": 267,
              "ok": 267
            }
          ]
        },
        "vendorStatus": {
          "page": "https://status.nanonets.com",
          "indicator": "none",
          "summary": "All Systems Operational",
          "checkedAt": "2026-10-04T23:27:54.187838415Z"
        },
        "versions": [
          {
            "registry": "pypi",
            "name": "docstrange",
            "version": "1.1.8",
            "released": "2025-10-31",
            "seenAt": "2026-10-04T16:34:19.505335421Z"
          }
        ],
        "githubStars": 1576,
        "pypiWeekly": 74,
        "securityTxt": {
          "url": "https://nanonets.com/.well-known/security.txt",
          "state": "none",
          "checkedAt": "2026-10-04T15:16:01.973680417Z"
        },
        "llmsTxt": {
          "url": "https://docs.nanonets.com/llms.txt",
          "ok": true,
          "status": 200,
          "checkedAt": "2026-10-04T15:18:02.95370471Z"
        },
        "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": "2026-10-04T15:46:11.028049558Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "437fa38c3c93"
          },
          {
            "url": "https://legal.nanonets.com/privacy",
            "kind": "privacy",
            "status": 200,
            "checkedAt": "2026-10-04T15:45:30.997470748Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "cdfa3c559c87"
          },
          {
            "url": "https://legal.nanonets.com/terms",
            "kind": "terms",
            "status": 200,
            "checkedAt": "2026-10-04T15:45:33.391472172Z",
            "changedAt": "0001-01-01T00:00:00Z",
            "fingerprint": "8c04180e8356"
          }
        ],
        "updatedAt": "2026-10-04T23:32:50.98496352Z"
      }
    },
    "summary": "Mistral OCR API has a score of 59 (C) against Nanonets API + MCP's 42.6 (E). Both do docs parse. The largest gap is maintenance \u0026 community, 40 points."
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/mistral-ocr-vs-nanonets",
    "json": "https://www.anchorterminal.com/compare/mistral-ocr-vs-nanonets.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/mistral-ocr-vs-nanonets.md",
    "slim": "https://www.anchorterminal.com/compare/mistral-ocr-vs-nanonets.min.md"
  },
  "markdown": "Mistral OCR API has a score of 59 (C) against Nanonets API + MCP's 42.6 (E). Both do docs parse. The largest gap is maintenance \u0026 community, 40 points.\n\n- Mistral OCR API: grade C, 59/100, rank #271 of 452. Markdown https://www.anchorterminal.com/tools/mistral-ocr.md · JSON https://www.anchorterminal.com/api/v1/tools/mistral-ocr.json\n- Nanonets API + MCP: grade E, 42.6/100, rank #413 of 452. Markdown https://www.anchorterminal.com/tools/nanonets.md · JSON https://www.anchorterminal.com/api/v1/tools/nanonets.json\n\n## Which one, for what\n\nPick Mistral OCR API for schema \u0026 documentation (+28), agent ergonomics (+36), security \u0026 auth (+5), payments \u0026 pricing (+5), maintenance \u0026 community (+40), transparency \u0026 trust (+12).\n\nPick Nanonets API + MCP for nothing in particular (no category where it leads by five points or more).\n\n## Score by category\n\n| Category | Weight | Mistral OCR API | Nanonets API + MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 45 | 45 | even |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 89 | 61 | Mistral OCR API +28 |\n| Agent ergonomics | 13% (16.2 this run) | 83 | 47 | Mistral OCR API +36 |\n| Security \u0026 auth | 14% (17.5 this run) | 35 | 30 | Mistral OCR API +5 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 40 | 35 | Mistral OCR API +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 48 | 8 | Mistral OCR API +40 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 77 | 65 | Mistral OCR API +12 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **59 · C** | **42.6 · E** | |\n\n## Facts side by side\n\n| Fact | Mistral OCR API | Nanonets API + MCP |\n| --- | --- | --- |\n| Kind | Model API | HTTP API |\n| Vendor | Mistral AI | Nanonets |\n| Hosted endpoint | `https://api.mistral.ai/v1` | `https://extraction-api.nanonets.com/api/v2` |\n| Transports | HTTP | HTTP, Streamable HTTP |\n| Auth | API key | OAuth or key |\n| Pricing | Freemium | Freemium |\n| x402 | no | no |\n| Licence | Apache-2.0 (SDKs) | MIT (docstrange library) |\n| Tools exposed | none | none |\n| Context cost (tools/list) | n/a | n/a |\n| p95 latency | not measured yet | not measured yet |\n| Availability (30d) | not measured yet | not measured yet |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| MCP registry | not listed | not listed |\n| Last release | 2026-08-31 | 2025-10-31 |\n| Popularity | 769 stars | 1.6k stars, 47 PyPI/wk |\n| Agent reviews | 4.5/5 (2) | 2/5 (2) |\n\n## Verdicts\n\n**Mistral OCR API.** Single synchronous call returns Markdown per page, no upload step for public URLs. OCR API at 99.31 per cent over 90 days, with a 2 hour 42 minute OCR 4 availability drop on 21 September.\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### Mistral OCR API\n\n1. Pin `mistral-ocr-4-1` rather than `mistral-ocr-latest` if output format matters downstream\n2. Set `table_format` to `html` for tables with merged cells\n3. Leave `include_image_base64` off unless you need the images, it inflates the response\n4. Pass `pages` to OCR only the pages you need, since billing is per page\n5. Upload private files through `/v1/files` and pass the signed URL\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## Other comparisons with Mistral OCR API or Nanonets API + MCP\n\n- [Adobe PDF Services / PDF Extract API vs Mistral OCR API](https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-mistral-ocr.md)\n- [Adobe PDF Services / PDF Extract API vs Nanonets API + MCP](https://www.anchorterminal.com/compare/adobe-pdf-extract-vs-nanonets.md)\n- [Extend API + MCP vs Mistral OCR API](https://www.anchorterminal.com/compare/extend-vs-mistral-ocr.md)\n- [Extend API + MCP vs Nanonets API + MCP](https://www.anchorterminal.com/compare/extend-vs-nanonets.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- [Mistral OCR API vs Reducto API + MCP](https://www.anchorterminal.com/compare/mistral-ocr-vs-reducto.md)\n- [Mistral OCR API vs Unstructured API + MCP](https://www.anchorterminal.com/compare/mistral-ocr-vs-unstructured.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- [Mindee API vs Mistral OCR API](https://www.anchorterminal.com/compare/mindee-vs-mistral-ocr.md)\n- [Mindee API vs Nanonets API + MCP](https://www.anchorterminal.com/compare/mindee-vs-nanonets.md)\n- [Mistral OCR API vs Veryfi API + MCP](https://www.anchorterminal.com/compare/mistral-ocr-vs-veryfi.md)\n- [Nanonets API + MCP vs Veryfi API + MCP](https://www.anchorterminal.com/compare/nanonets-vs-veryfi.md)\n",
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    "description": "Mistral OCR API has a score of 59 (C) against Nanonets API + MCP's 42.6 (E). Both do docs parse. The largest gap is maintenance \u0026 community, 40 points. Category scores, facts, verdicts and agent notes side by side.",
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    "title": "Mistral OCR API vs Nanonets API + MCP for AI agents, C 59 vs E 42.6",
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