Study and cross-reference

What else does Scripture say about this, and which words move together? 6 Darash MCP tools, listed below with the exact description and input schema the server itself returns. Endpoint: https://darash-api.publifye.com/mcp. See [connect](../../../docs/connect.md) to get a key.

Tool What it does
word_study THE recommended tool for studying any Greek or Hebrew word
verse_study Complete verse analysis in one call
get_cross_refs Get cross-references for a verse (related passages)
get_synonyms Get the semantic-neighbour set for a Strong's number, computed from the in-memory synonym…
synonym_stats Health check for the synonym graph built at startup
co_occurrence Find verses where two Strong's numbers appear together

word_study

Word Study — read-only, idempotent, closed-world.

THE recommended tool for studying any Greek or Hebrew word. Complete word study in ONE call — returns everything: Strong's definition, Abbott-Smith/BDB scholarly lexicon, LSJ classical Greek, Thayer's Greek-English Lexicon 1889 (for G numbers), frequency with OT/NT breakdown, etymology tree, reverse lookup (other words translated the same way), and sample verses. Use THIS instead of calling get_strongs + lookup_dictionary(thayer) + search_strongs separately. The 'thayer' field carries 'thayer_note' naming the edition — until 2026-09-02 that field held a modern gloss set that was not Thayer's text at all, so check the note rather than trusting the field name. Then sharpen it: get_synonyms for the near-synonyms, search_strongs to see the word live in its verses.[END]

Parameter Type Required Description
number string yes Strong's number with prefix (e.g., 'H2617' for Hebrew chesed, 'G26' for Greek agape)

verse_study

Verse Study — read-only, idempotent, closed-world.

Complete verse analysis in one call. Returns: verse text, all Strong's numbers with definitions, word-by-word morphological parsing (tense, voice, mood, case, gender), and cross-references. Replaces 4 separate tool calls (get_verse + strongs_in_verse + get_morphology + get_cross_refs).[END]

Parameter Type Required Description
bible string no Bible translation for verse text (default: kjv)
ref string yes Verse reference (e.g., 'Romans 3:23', 'Genesis 1:1', 'John 3:16')

get_cross_refs

Get Cross Refs — read-only, idempotent, closed-world.

Get cross-references for a verse (related passages). Shared lemmas are usually the connection — strongs_in_verse on both ends often lights it up.[END]

Parameter Type Required Description
ref string yes Bible reference (e.g., 'John 3:16')

get_synonyms

Get Synonyms — read-only, idempotent, closed-world.

Get the semantic-neighbour set for a Strong's number, computed from the in-memory synonym graph built at startup. Three signals unioned: shared Hebrew/Greek root, definition-word overlap (≥3 shared content words in def_short+def_long), and KJV rendering overlap (≥2 shared translation tokens in the Usage field). Much denser than get_related_strongs (which is limited to the thin 'See' + derivation field) — typically 20-50 neighbours per common Hebrew verb vs 0-3 for get_related_strongs. Each edge is weighted 0..1 and tagged with its contributing source(s). Use this to expand a verse's thematic fingerprint for empirical tests.[END]

Parameter Type Required Description
language string no 'hebrew' or 'greek' (optional if using H/G prefix)
limit integer no Max neighbours returned (default 30, max 50)
min_weight number no Drop edges below this weight (0..1). Default 0.3 = the same threshold the graph itself enforces.
number string yes Strong's number with prefix (e.g., 'H2388' for chazak 'to be strong')

synonym_stats

Synonym Stats — read-only, idempotent, closed-world.

Health check for the synonym graph built at startup. Returns node counts, edge counts, mean/max degree per language, and build time. Use once to confirm the graph is populated; then use get_synonyms for actual queries.[END]

co_occurrence

Co Occurrence — read-only, idempotent, closed-world.

Find verses where two Strong's numbers appear together. Useful for studying word pairs — e.g., kentron (G2759) + thanatos (G2288) to find 'sting of death'.[END]

Parameter Type Required Description
limit integer no Maximum results (default: 50, max: 200)
number1 string yes First Strong's number (e.g., 'G2759')
number2 string yes Second Strong's number (e.g., 'G2288')

Generated from the live tools/list on 2026-09-13. Regenerate rather than edit by hand.

Generated from the live service's own tools/list — not written by hand, so it cannot drift from what Darash actually answers. Source on GitHub

Questions about Darash

What people use it for

Ground my Sunday sermon in what the passage actually says.

Yes. Your assistant uses verse_study for the passage, its tagged words, parsing and cross-references, then strongs_in_verse to verify the word it wants to discuss. word_study returns the available lexicon entries, usage and provenance for that Strong’s number. You get sources to inspect before making a sermon point; the assistant must distinguish retrieved lexical data from its interpretation.

Ask your AI
Show the Greek behind Romans 8:26, its parsing and named lexicon entries.
What it does
  • verse_study
  • strongs_in_verse
  • word_study
What you get
Verse text, tagged original words, parsing and named lexical sources.
Check the Greek before I build a sermon point on it.

Yes. strongs_in_verse lists the tagged original-language words with their Strong’s numbers in each verse. Your assistant can show which number occurs at each place and open its lexicon entries before comparing meanings, rather than inferring the Greek from an English translation or memory.

Ask your AI
Compare the Greek words for love in John 21:15 and 21:17.
What it does
  • strongs_in_verse
  • get_strongs
  • get_synonyms
What you get
The words actually tagged in each verse and their lexicon entries.
Help me prepare a Greek parsing class from this passage.

Yes. Darash supplies parsing and lexicon data verse by verse, and your assistant lays it out as a student worksheet and answer key. Use get_morphology for each verse and word_study for the key words; the worksheet itself is assembled by your assistant.

Ask your AI
Give me the verbs and parsing for Philippians 2:5–8 for a worksheet.
What it does
  • get_verse
  • get_morphology
  • word_study
What you get
Parsing data and lexicon entries for my AI to arrange into a worksheet.
Compare what these translations say in the same verse.

Yes. Start with list_bibles to see the translations and identifiers available on the connected service, including Norwegian, Persian and Latin texts where held. compare_verses returns the named translations side by side, so your assistant quotes the text it retrieved.

Ask your AI
Show Psalm 23:4 in the available translations I choose.
What it does
  • list_bibles
  • compare_verses
What you get
Retrieved translation texts side by side, each identified.
Help me research a theme for the book I am writing.

Yes. Text search finds matching verses, get_cross_refs retrieves their stored cross-references, and multi_dict_lookup brings back topical entries from the dictionaries. Your assistant can organise the returned evidence into research notes and identify each source; a search page is not a promise that every passage on a theme has been found.

Ask your AI
Find wilderness passages, cross-references and named dictionary articles.
What it does
search → get_cross_refs → multi_dict_lookup
What you get
Matching verses, stored cross-references and attributed topic entries.
Make my personal Bible-study agent check its sources.

Yes. A personal MCP-capable study agent can call Darash for the verse, verify its tagged words with strongs_in_verse, and use word_study for named lexical sources. Keep edition and known gaps with quotations. Providing Darash or its outputs to your own users through an app, bot or service requires the appropriate separate licence; personal access does not authorize that use.

Ask your AI
Check every Greek or Hebrew claim against Darash and cite the entry.
What it does
  • get_verse
  • strongs_in_verse
  • word_study
What you get
Source text and lexical data my agent can quote and attribute.

All questions