{"uid":"cap_zqkvQDUFmBfGgsfKbBVm-","slug":"lotus-network-api-pdf-to-markdown-5c587ed4","name":"Lotus Network API – PDF to Markdown","description":"Extracts text from a PDF and returns clean Markdown: unwrapped paragraphs, detected headings and bullet lists, no page furniture. Accepts a public PDF URL or base64 bytes. Built for agents that need to read documents they cannot parse natively.","url":"https://lotusnetworkapi.com/api/v1/pdf-to-markdown","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"pdf":{"type":"string"},"url":{"type":"string"},"pageMarkers":{"type":"boolean"}}},"responseSchema":{"type":"json","example":{"pages":12,"title":"Quarterly Report","success":true,"markdown":"# Quarterly Report\n\nRevenue grew 14% year over year...","characters":18432}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.005","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.005/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.005","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.005","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_HtXQtT_yq46vTwFe0y_63","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.005","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Converts a PDF document (via URL or base64) into clean, structured Markdown with unwrapped paragraphs, detected headings, and bullet lists","exampleAgentPrompt":"Can you extract the text from this PDF and give it to me as clean markdown? Here's the link: https://example.com/report.pdf","exampleUseCases":[{"title":"Research paper ingestion for RAG","prompt":"I need you to pull the content out of this academic PDF so I can feed it into my knowledge base — here's the URL: https://arxiv.org/pdf/2301.00001.pdf. Give me the result as markdown with headings preserved."},{"title":"Contract review by AI agent","prompt":"Please extract all the text from this legal contract PDF — https://example.com/contracts/agreement.pdf — and return it as markdown so I can analyze the clauses."},{"title":"Invoice data extraction pipeline","prompt":"I have a PDF invoice at https://mybusiness.com/invoices/inv-2024-05.pdf that I need converted to markdown so my agent can pull out the line items and totals."}],"resultDescription":"A clean Markdown string representing the PDF's content, with properly detected headings, unwrapped paragraphs, and bullet lists. Page headers/footers and other page furniture are stripped. If pageMarkers is enabled, page boundary indicators are included.","failureModes":["Invalid or inaccessible PDF URL returns an error indicating the resource could not be fetched","Malformed base64 input causes a parsing error","Password-protected or encrypted PDFs may fail to parse","Very large PDFs may time out or return partial results","Scanned image-only PDFs with no embedded text will return empty or minimal markdown (no OCR performed)"],"whenToPreferThis":"Choose this endpoint when an AI agent needs to read a PDF document it cannot natively parse — especially for structured documents like reports, papers, or contracts where heading detection and clean paragraph formatting matter. Prefer it over generic text extractors when markdown structure (headings, lists) is important for downstream processing. At $0.005 per call it is cost-effective for per-document pipelines.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T00:38:54.353Z","isFirstParty":false}