Tanod Text

Ingested from the official MCP Registry

FastDrop pulled this entry from the official MCP Registry as dev.tanod/text and probed the endpoint. The maker did not submit it, so the outbound link is not endorsed and the description is not theirs.

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Tools this endpoint exposes

Read directly from the endpoint on 8 Oct 2026. Not supplied by the maker.

• text_stats

  utilpeek: counts (characters, letters, words, unique words, sentences, paragraphs, averages), reading and speaking time, and for English the Flesch reading ease, Flesch-Kincaid grade, Gunning fog, SMO

• detect_language

  utilpeek: the most likely language (ISO 639-1 and 639-3 code, name, confidence) and 3 alternatives, from an offline ensemble of lingua (Apache-2.0) and langid.py (BSD-2-Clause) over 75 languages; `rel

• text_case

  utilpeek: the text in another case: upper, lower, title (small words such as a, of, the kept lower-case; iPhone and domains kept), sentence, camel, pascal, snake, kebab, constant, dot or alternating;

• text_lines

  utilpeek: the text's lines transformed by `operations` in order: trim, remove_empty, dedupe (keeps the first), sort (lexical, natural or length; stable), reverse, shuffle (seeded, repeatable) and numb

• text_replace

  utilpeek: the text with `find` replaced: literally, or as a regular expression on RE2 only (linear time for any pattern: no backtracking, so no ReDoS; backreferences and lookaround are refused), with

• text_extract

  utilpeek: the emails, URLs, domains (ICANN suffixes), IPv4 / IPv6, phone-like numbers, hashtags, mentions, EVM and BTC addresses (Base58Check / Bech32 checksums verified) and dates (normalised to ISO)

• text_frequency

  utilpeek: the most frequent words or 2-3 word n-grams (n-grams never cross punctuation) with count and share, dropping stop words (en, es, fr, de, pt, it, nl, or none), and optionally character counts

• text_keywords

  utilpeek: the top keyphrases of a text by RAKE (phrases between stop words and punctuation, scored by word degree / frequency), with score and count. Input: `text` (at most 200,000 characters), option

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