parse_document

io.github.razikallayi/razi-tools · Verify this server

Use this when the file ALREADY stores its text as characters: it decodes them and returns JSON { text, metadata } verbatim, with no guessing involved. That exactness is the whole difference from extract_text_ocr, which recovers text from pixels by guessing at glyph shapes and should only ever be pointed at a photo, screenshot or scan. Supported: .txt, decoded as UTF-8 and returned in full with metadata { format: "txt", words }; and .pdf, where the text layer is read page by page and joined with a `--- Page N ---` separator, returning metadata { format: "pdf", pages, words } — pages and words are counted from the document itself, never estimated. .docx and every other extension are rejected with 400. A scanned or photographed PDF has no text layer, so nothing can be extracted from it here; that case returns 422 with a metadata.imageOnly flag rather than an empty success, and extract_text_ocr is the tool for it. Limits: 50MB and 300 pages, over which the call returns 413; an unreadable or encrypted PDF returns 400. Layout is not preserved — no tables, columns or coordinates, just a flat string per page. The file type is decided by the filename extension, not by inspecting the bytes. 10 calls per minute per caller. There is no upload channel over MCP: pass `fileUrl`, a URL in razi.pro's own storage; third-party URLs are rejected. Obtain one by uploading the file over the REST API first (POST /api/v1/tools/execute with the file attached).