Tanod Text

Name: Tanod Text
Author: dev.tanod

MCP serverMCP

Text tools: stats, language, case, lines, replace, extract, keywords, summary, sentiment, diff.

by dev.tanodhomepage ↗v0.1.0

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Observed by Wellknown

Evidence

Everything here was measured by our prober or read from a registry. Nothing is self-reported.

30-day availability47/47 checks ok

when	check	result	http	latency	detail
4 h ago	mcp initialize	ok	200	279 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools
11 h ago	mcp initialize	ok	200	283 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools
17 h ago	mcp initialize	ok	200	267 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools
27 h ago	mcp initialize	ok	200	269 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools
2 d ago	mcp initialize	ok	200	703 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools
2 d ago	mcp initialize	ok	200	751 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools
2 d ago	mcp initialize	ok	200	684 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools
2 d ago	mcp initialize	ok	200	267 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools
3 d ago	mcp initialize	ok	200	727 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools
3 d ago	mcp initialize	ok	200	741 ms	server tanod-text 0.1.0 · protocol 2025-06-18 · 24 tools

Tools observed via MCP handshake

text_stats — utilpeek: Count words and score the readability of a text. For word frequencies use text_frequency. Returns counts (characters, letters, words, unique words, se
detect_language — utilpeek: Detect the language of a text. To translate use translate_text. Returns the most likely language (ISO 639-1 and 639-3 code, name, confidence) and 3 al
text_case — utilpeek: Convert text case: title, sentence, snake, camel, kebab, ... For a URL slug use make_slug. Returns the text in another case: upper, lower, title (smal
text_lines — utilpeek: Sort, dedupe, trim, shuffle or number the lines of a text. For find and replace use text_replace. Returns the text's lines transformed by `operations`
text_replace — utilpeek: Find and replace in text. To sort, dedupe or number lines use text_lines. Returns the text with `find` replaced: literally, or as a regular expression
text_extract — utilpeek: Extract emails, URLs, domains, IPs, dates and crypto addresses from text. To mask personal data use redact_pii; for names and places use extract_entit
redact_pii — utilpeek: Redact PII from text: emails, phone numbers, card numbers, IBANs, SSNs, IPs and crypto addresses. For API keys and tokens use check_text_for_secrets.
text_frequency — utilpeek: Count word and n-gram frequencies in a text. For scored keyphrases use text_keywords. Returns the most frequent words or 2-3 word n-grams (n-grams nev
text_keywords — utilpeek: Extract the keywords and keyphrases of a text. For raw frequencies use text_frequency; for names and places use extract_entities. Returns the top keyp
text_summarize — utilpeek: Summarize a text by picking its key sentences. For paper abstracts use paper_digest; for counts use text_stats. Returns an extractive summary: the mos
text_sentiment — utilpeek: Analyze the sentiment of an English text. For your own labels use classify_zero_shot; for counts use text_stats. Returns VADER sentiment of an English
text_spellcheck — utilpeek: Spellcheck a text with suggestions. For counts and readability use text_stats. Returns the words not in the language's word-frequency dictionary (pysp
text_unicode_inspect — utilpeek: Find invisible, bidi and homoglyph Unicode characters in text. For injected instructions use check_text_for_prompt_injection. Returns a security-orien
text_numbers — utilpeek: Convert numbers to English words. For units use convert_units. Returns a number spelled out in English (cardinal, ordinal, year, or currency for 13 cu
text_lorem — utilpeek: Generate seeded lorem ipsum or English placeholder text. For random values use generate_random. Returns placeholder text: classic lorem ipsum or Engli
diff_text — utilpeek: Diff two texts: unified line diff, word or character changes. For PDF or Word files use compare_documents. Returns the differences between two texts:
make_slug — utilpeek: Make a URL slug from text. For other case styles use text_case. Returns a URL slug: accents removed, Latin ligatures, Greek and Cyrillic transliterate
markdown_to_html — utilpeek: Convert Markdown to sanitized HTML. For the reverse use html_to_text. Returns the HTML of a Markdown document (markdown-it-py; `gfm` adds tables, stri
html_to_text — utilpeek: Convert HTML to Markdown or plain text. To fetch a URL use render_page; for the reverse use markdown_to_html. Returns the readable content of an HTML
convert_subtitles — utilpeek: Convert subtitles between SRT, WebVTT and JSON, with a time shift. To make subtitles from audio use transcribe_audio. Returns a subtitle file converte
pdf_redact — pdfpeek: Redact a PDF: black out terms, emails, phone numbers, card numbers and areas. To test a file redacted elsewhere use pdf_redaction_check. Returns a PDF
pdf_redaction_check — pdfpeek: Check a PDF for failed redactions: black boxes with the text still under them. To redact properly use pdf_redact. Returns whether black boxes in a PDF
check_text_for_secrets — utilpeek: Scan text for leaked secrets: API keys, tokens, private keys and seed phrases. For personal data use redact_pii; for injected instructions use check_t
check_text_sources — findpeek: Check a text for copied sentences: web pages that contain them word for word. For a general query use web_search. Returns for up to 10 of a text's mos

Tanod Text

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