docforge
12 paid document tools: PDF to markdown, OCR, tables, invoices, Word/Excel/HTML, merge/split. x402
Should I use this
Quality & Safety
Based on automated analysis of tool definitions and protocol compliance.
Context Cost
This is the approximate number of tokens consumed each time the server's tools are loaded into a model's context. Higher counts reduce the attention available for other tasks.
Install
One-Click Install
Add this to your `claude_desktop_config.json` file:
{
"mcpServers": {
"docforge": {
"url": "https://docforged.mcpize.run/mcp"
}
}
}Remote endpoints
https://docforged.mcpize.run/mcpstreamable-httpWhat it can do
Tool inventory
Tools (5)
🟢pdf_to_markdown(file_url, file_base64)
Extract the text of a PDF and convert it to clean markdown. Detects headings by font size and preserves lists and paragraphs. Input: a text-based PDF via file_url or file_base64. For scanned PDFs use ocr_image on page images instead.
Input Schema
{
"type": "object",
"properties": {
"file_url": {
"type": "string",
"format": "uri",
"description": "Public http(s) URL of the file"
},
"file_base64": {
"type": "string",
"description": "Base64-encoded file contents (data-URI prefix allowed)"
}
},
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}⚪ocr_image(file_url, file_base64, language)
Run optical character recognition on an image (png, jpg, webp, bmp) and return the recognized text with a confidence score. Supports 100+ languages via the language parameter (ISO 639-2 codes like 'eng', 'deu', 'fra', 'spa').
Input Schema
{
"type": "object",
"properties": {
"file_url": {
"type": "string",
"format": "uri",
"description": "Public http(s) URL of the file"
},
"file_base64": {
"type": "string",
"description": "Base64-encoded file contents (data-URI prefix allowed)"
},
"language": {
"type": "string",
"description": "Tesseract language code, default 'eng'"
}
},
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}🔴extract_tables(file_url, file_base64)
Detect and reconstruct tables from a text-based PDF. Returns each table as structured rows plus ready-to-use markdown and CSV renderings. Works best on PDFs with clear columnar layout (invoices, reports, statements).
Input Schema
{
"type": "object",
"properties": {
"file_url": {
"type": "string",
"format": "uri",
"description": "Public http(s) URL of the file"
},
"file_base64": {
"type": "string",
"description": "Base64-encoded file contents (data-URI prefix allowed)"
}
},
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}⚪render_pdf(content, format, title)
Render markdown (or simple HTML) into a clean, printable A4 PDF. Supports headings, paragraphs, bullet and numbered lists, blockquotes, code blocks, horizontal rules, and inline bold/italic/code. Returns the PDF as base64 plus page count.
Input Schema
{
"type": "object",
"properties": {
"content": {
"type": "string",
"minLength": 1,
"description": "The markdown or HTML source to render"
},
"format": {
"type": "string",
"enum": [
"markdown",
"html"
],
"description": "Input format, default markdown"
},
"title": {
"type": "string",
"description": "PDF document title metadata"
}
},
"required": [
"content"
],
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}🟢parse_invoice(file_url, file_base64, is_image)
Extract structured data from an invoice or receipt: vendor, invoice number, dates, currency, subtotal, tax, total, and line items. Accepts a text-based PDF, or an image when is_image is true (OCR is applied first). Returns JSON.
Input Schema
{
"type": "object",
"properties": {
"file_url": {
"type": "string",
"format": "uri",
"description": "Public http(s) URL of the file"
},
"file_base64": {
"type": "string",
"description": "Base64-encoded file contents (data-URI prefix allowed)"
},
"is_image": {
"type": "boolean",
"description": "Set true when the file is a photo/scan image rather than a PDF"
}
},
"additionalProperties": false,
"$schema": "http://json-schema.org/draft-07/schema#"
}Community
Evidence