Answered what happens to math
The site never said what txtfetch does with equations. Word equations vanish and the response still says success. PDF math loses its layout. The new page shows real output for each input and the fix for each.
/docs/equations →
Answered the prompt-injection question
The site never said what txtfetch does about injected instructions. It does nothing: every character comes back. The new page shows where hidden text hides and adds a paste-in checker for invisible characters.
/docs/untrusted-documents →
Added an MCP server recipe for AI agents
txtfetch ships no MCP server, so the site never answered whether an agent like Claude Code or Cursor could call it as a tool. The new page gives a tested one, in Python and Node.js, that you run yourself.
/integrations/mcp →
Answered the handwriting question directly
The site never said whether txtfetch reads handwriting. It doesn't, on the standard tier. The new page states that plainly, and shows what comes back for each kind of input.
/docs/handwriting →
Rewrote the homepage copy and fixed two stale claims
The homepage said every request 'always answers with text.' It does not: a bad request returns an error code. The format wall's '+ ~976 more' was also hard-coded and stale; it is now derived from the checked Tika coverage count.
/ →
A re-indexing guide for changed documents
/docs/re-indexing answers the daily-churn question. txtfetch keeps no content cache, so a full nightly run pays for every file. The page gives four steps to pay for changed files only. It adds a monthly cost table and a stdlib Python manifest.
/docs/re-indexing →
Ingest pages for keyword search engines
/ingest now covers keyword search engines as well as vector stores. The new pages are Elasticsearch, OpenSearch, Meilisearch, Typesense, and Postgres full-text search. Each page names the point where a long document stops counting. On Postgres, that is word position 16,383.
/ingest →
Where your file goes
A new page traces one document hop by hop inside txtfetch, from the edge to the S3 buffer to usage records. The premium-tier row states plainly that it is switched off by default today.
/docs/where-your-file-goes →
What happens if you leave?
This page answers it: the full API surface, the six response fields, and why there is nothing to export. It also names three replacements — self-hosted Tika, an open-source parser, another vendor — and what each one costs you to take back.
/docs/leaving →
Why not just send the file to the model?
GPT, Claude, and Gemini all read PDFs natively. This page names the documented token cost per vendor. It also names the formats none of them accept, and where txtfetch's own vision-language tier fits in.
/compare/multimodal-llm →
Extract from Drive, SharePoint, S3, and more
The /sources page names every place a document can live before txtfetch reads it. It states which ones hand over a URL, and which need a file upload.
/sources →
What pgvector, Pinecone, Qdrant, Chroma, and Weaviate need next
txtfetch stops at extracted text. /ingest covers the chunk, embed, and upsert step for five vector stores, cited and dated.
/ingest →
How txtfetch compares to five open-source parsers
/compare/libraries checks txtfetch against Docling, MarkItDown, PyMuPDF4LLM, Marker, and MinerU on licence, GPU need, format coverage, and OCR.
/compare/libraries →
Document-language pages, with the honest OCR limit stated
/languages covers nine document languages: legacy encodings, chunking risk, and where OCR support actually stops.
/languages →