Pricing

from $4.00 / 1,000 document converteds

Try for free

Go to Apify Store

PDF to Markdown Converter: Text, Tables, CSV

Try for free

Convert PDFs to clean Markdown with headings, lists and tables, plus plain text and one CSV per table. Public URLs or uploaded files, up to 2,000 pages each. Scanned pages are reported, not billed, and unreadable files are free error rows. Built for RAG and AI agents.

Pricing

from $4.00 / 1,000 document converteds

Rating

0.0

(0)

Developer

kelp forest

Actor stats

Bookmarked

Total users

Monthly active users

17 days ago

Last modified

Categories

Developer tools

You can access the PDF to Markdown Converter: Text, Tables, CSV programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in API & Integrations in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

{
  "openapi": "3.0.1",
  "info": {
    "version": "1.0",
    "x-build-id": "1DEtRTxP6EeHAgLj5"
  },
  "servers": [
    {
      "url": "https://api.apify.com/v2"
    }
  ],
  "paths": {
    "/acts/kelp_forest_labs~pdf-to-markdown/run-sync-get-dataset-items": {
      "post": {
        "operationId": "run-sync-get-dataset-items-kelp_forest_labs-pdf-to-markdown",
        "x-openai-isConsequential": false,
        "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
        "tags": [
          "Run Actor"
        ],
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/inputSchema"
              }
            }
          }
        },
        "parameters": [
          {
            "name": "token",
            "in": "query",
            "required": true,
            "schema": {
              "type": "string"
            },
            "description": "Enter your Apify token here"
          }
        ],
        "responses": {
          "200": {
            "description": "OK"
          }
        }
      }
    },
    "/acts/kelp_forest_labs~pdf-to-markdown/runs": {
      "post": {
        "operationId": "runs-sync-kelp_forest_labs-pdf-to-markdown",
        "x-openai-isConsequential": false,
        "summary": "Executes an Actor and returns information about the initiated run in response.",
        "tags": [
          "Run Actor"
        ],
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/inputSchema"
              }
            }
          }
        },
        "parameters": [
          {
            "name": "token",
            "in": "query",
            "required": true,
            "schema": {
              "type": "string"
            },
            "description": "Enter your Apify token here"
          }
        ],
        "responses": {
          "200": {
            "description": "OK",
            "content": {
              "application/json": {
                "schema": {
                  "$ref": "#/components/schemas/runsResponseSchema"
                }
              }
            }
          }
        }
      }
    },
    "/acts/kelp_forest_labs~pdf-to-markdown/run-sync": {
      "post": {
        "operationId": "run-sync-kelp_forest_labs-pdf-to-markdown",
        "x-openai-isConsequential": false,
        "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
        "tags": [
          "Run Actor"
        ],
        "requestBody": {
          "required": true,
          "content": {
            "application/json": {
              "schema": {
                "$ref": "#/components/schemas/inputSchema"
              }
            }
          }
        },
        "parameters": [
          {
            "name": "token",
            "in": "query",
            "required": true,
            "schema": {
              "type": "string"
            },
            "description": "Enter your Apify token here"
          }
        ],
        "responses": {
          "200": {
            "description": "OK"
          }
        }
      }
    }
  },
  "components": {
    "schemas": {
      "inputSchema": {
        "type": "object",
        "properties": {
          "pdfUrls": {
            "title": "PDF URLs",
            "type": "array",
            "description": "Public http(s) links to PDF files. Private, loopback and login-walled links are not supported.",
            "items": {
              "type": "string"
            }
          },
          "pdfFile": {
            "title": "Upload a PDF (optional)",
            "type": "string",
            "description": "Upload one PDF from your computer instead of (or as well as) the URLs."
          },
          "startUrls": {
            "title": "Start URLs (alternative)",
            "type": "array",
            "description": "Same as PDF URLs, in Apify's start-URL format.",
            "items": {
              "type": "object",
              "required": [
                "url"
              ],
              "properties": {
                "url": {
                  "type": "string",
                  "title": "URL of a web page",
                  "format": "uri"
                }
              }
            }
          },
          "maxPagesPerDocument": {
            "title": "Max pages per document",
            "minimum": 1,
            "maximum": 2000,
            "type": "integer",
            "description": "Only the first N pages are converted and billed.",
            "default": 100
          },
          "extractTables": {
            "title": "Extract tables",
            "type": "boolean",
            "description": "Detect ruled tables, render them as Markdown tables and save each as CSV.",
            "default": true
          },
          "includeText": {
            "title": "Include plain text",
            "type": "boolean",
            "description": "Also return the raw text layer (pages separated by a form feed).",
            "default": true
          },
          "saveFiles": {
            "title": "Save files to key-value store",
            "type": "boolean",
            "description": "Save the full .md, .txt and one .csv per table, with links in the output row.",
            "default": true
          }
        }
      },
      "runsResponseSchema": {
        "type": "object",
        "properties": {
          "data": {
            "type": "object",
            "properties": {
              "id": {
                "type": "string"
              },
              "actId": {
                "type": "string"
              },
              "userId": {
                "type": "string"
              },
              "startedAt": {
                "type": "string",
                "format": "date-time",
                "example": "2025-01-08T00:00:00.000Z"
              },
              "finishedAt": {
                "type": "string",
                "format": "date-time",
                "example": "2025-01-08T00:00:00.000Z"
              },
              "status": {
                "type": "string",
                "example": "READY"
              },
              "meta": {
                "type": "object",
                "properties": {
                  "origin": {
                    "type": "string",
                    "example": "API"
                  },
                  "userAgent": {
                    "type": "string"
                  }
                }
              },
              "stats": {
                "type": "object",
                "properties": {
                  "inputBodyLen": {
                    "type": "integer",
                    "example": 2000
                  },
                  "rebootCount": {
                    "type": "integer",
                    "example": 0
                  },
                  "restartCount": {
                    "type": "integer",
                    "example": 0
                  },
                  "resurrectCount": {
                    "type": "integer",
                    "example": 0
                  },
                  "computeUnits": {
                    "type": "integer",
                    "example": 0
                  }
                }
              },
              "options": {
                "type": "object",
                "properties": {
                  "build": {
                    "type": "string",
                    "example": "latest"
                  },
                  "timeoutSecs": {
                    "type": "integer",
                    "example": 300
                  },
                  "memoryMbytes": {
                    "type": "integer",
                    "example": 1024
                  },
                  "diskMbytes": {
                    "type": "integer",
                    "example": 2048
                  }
                }
              },
              "buildId": {
                "type": "string"
              },
              "defaultKeyValueStoreId": {
                "type": "string"
              },
              "defaultDatasetId": {
                "type": "string"
              },
              "defaultRequestQueueId": {
                "type": "string"
              },
              "buildNumber": {
                "type": "string",
                "example": "1.0.0"
              },
              "containerUrl": {
                "type": "string"
              },
              "usage": {
                "type": "object",
                "properties": {
                  "ACTOR_COMPUTE_UNITS": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATASET_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATASET_WRITES": {
                    "type": "integer",
                    "example": 0
                  },
                  "KEY_VALUE_STORE_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "KEY_VALUE_STORE_WRITES": {
                    "type": "integer",
                    "example": 1
                  },
                  "KEY_VALUE_STORE_LISTS": {
                    "type": "integer",
                    "example": 0
                  },
                  "REQUEST_QUEUE_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "REQUEST_QUEUE_WRITES": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATA_TRANSFER_INTERNAL_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATA_TRANSFER_EXTERNAL_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_SERPS": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_UNBLOCKER_UNITS": {
                    "type": "integer",
                    "example": 0
                  }
                }
              },
              "usageTotalUsd": {
                "type": "number",
                "example": 0.00005
              },
              "usageUsd": {
                "type": "object",
                "properties": {
                  "ACTOR_COMPUTE_UNITS": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATASET_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATASET_WRITES": {
                    "type": "integer",
                    "example": 0
                  },
                  "KEY_VALUE_STORE_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "KEY_VALUE_STORE_WRITES": {
                    "type": "number",
                    "example": 0.00005
                  },
                  "KEY_VALUE_STORE_LISTS": {
                    "type": "integer",
                    "example": 0
                  },
                  "REQUEST_QUEUE_READS": {
                    "type": "integer",
                    "example": 0
                  },
                  "REQUEST_QUEUE_WRITES": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATA_TRANSFER_INTERNAL_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "DATA_TRANSFER_EXTERNAL_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_SERPS": {
                    "type": "integer",
                    "example": 0
                  },
                  "PROXY_UNBLOCKER_UNITS": {
                    "type": "integer",
                    "example": 0
                  }
                }
              }
            }
          }
        }
      }
    }
  }
}

PDF to Markdown Converter: Text & Tables for RAG OpenAPI definition

OpenAPI is a standard for designing and describing RESTful APIs, allowing developers to define API structure, endpoints, and data formats in a machine-readable way. It simplifies API development, integration, and documentation.

OpenAPI is effective when used with AI agents and GPTs by standardizing how these systems interact with various APIs, for reliable integrations and efficient communication.

By defining machine-readable API specifications, OpenAPI allows AI models like GPTs to understand and use varied data sources, improving accuracy. This accelerates development, reduces errors, and provides context-aware responses, making OpenAPI a core component for AI applications.

You can download the OpenAPI definitions for PDF to Markdown Converter: Text, Tables, CSV from the options below:

OpenAPI.json

If you’d like to learn more about how OpenAPI powers GPTs, read our blog post.

You can also check out our other API clients:

PDF to Markdown Converter: Text, Tables, CSV API in Python

PDF to Markdown Converter: Text, Tables, CSV API in JavaScript

PDF to Markdown Converter: Text, Tables, CSV API through CLI

PDF to Markdown Converter: Text, Tables, CSV API

📑 PDF to HTML Converter Lite – Pay Per Result

microtrica/pdf-to-html-lite

⚡Effortlessly transform ➡️ your PDF documents 📑 into responsive, mobile-friendly 🌐HTML pages. Boost web performance with perfect conversions and seamless browser compatibility. Maximum Pages: 20 per PDF

Microtrica

PDF URL to Markdown, Tables & RAG Extractor

thescrapelab/Apify-PDF-url-scraper

Extract clean Markdown, page text, tables, metadata, summaries, and AI-ready RAG chunks from PDF URLs.

Inus Grobler

Pdf Text Extractor Pro

dainty_screw/pdf-text-extractor-pro

PDF Text Extractor lets you quickly extract text from PDF files with high accuracy. Supports text chunking for AI, chatbots, and large language models (LLMs), making PDF-to-text conversion fast, clean, and ready for NLP or machine learning.

codemaster devops

5.0

(1)

PDF to Markdown RAG-Ready

hedelka/pdf-to-markdown-rag

Premium PDF scraper that preserves tables and structure. Optimized for RAG.

Dmitry Goncharov

PDF to Markdown Converter - AI-Powered with OCR & Tables

clearpath/pdf-to-markdown-api

Convert PDFs to clean Markdown with GPU-accelerated AI. Extracts tables, LaTeX formulas, and images from complex layouts. Supports OCR for scanned docs in 8 languages. Batch process hundreds of PDFs in parallel via URL, upload, or API.

ClearPath

PDF to JSON Parser

parseforge/pdf-to-json-parser

Extract structured JSON data from PDF files automatically. Upload one or more PDFs and get clean, organized data with AI-powered field extraction.

ParseForge

5.0

(1)

Website To Markdown

smart_api/website-to-markdown

Convert any webpage into clean, LLM-ready Markdown in seconds — perfect for AI training data, RAG pipelines, and content archiving.

SmartApi

5.0

(1)

Pandoc Document Converter

incredible_moment/pandoc-actor

Universal document converter. Transform Markdown, HTML, and text to PDF, DOCX, EPUB, and more. High-performance Rust wrapper for the Pandoc engine ensures fast execution and low memory footprint.

Daniel Rosen

Doc2RAG AI - Documentation to LLM-Ready Markdown Converter

automation_studio/doc-to-rag-markdown-converter

Convert technical documentation websites (Stripe, Supabase, Next.js, Mintlify, Docusaurus) into clean, LLM-ready Markdown with preserved multi-language code blocks, tables, and RAG frontmatter. Exports JSON dataset, single llms-full.txt, and ZIP archive.

Automation Studio

PDF Text Extractor & Document Parser: DOCX, XLSX, OCR, Markdown

yabanana99/pdf-word-excel-to-markdown

Parse Word, PowerPoint, Excel and PDF documents into clean Markdown and structured JSON: tables extracted cell-by-cell, document metadata, and RAG-ready chunks with heading paths. Built-in OCR for scans and images.