Tripitaka MCP server

• compare_translationsFree

  Compare every available translation for a single segment. 💡 **Use this tool when:** - The user asks about the meaning/translation of a single Pāli line and wants to see multiple translators side-by-side. - Checking how different translators interpret the same line — technical terms like `dukkha`, `anattā`, `nibbāna` carry nuance that varies across translations. - Academic work that needs to quote multiple translations. 🔍 **vs `get_sutta`:** this tool targets a **single segment** (line level); `get_sutta` returns the **whole sutta**. To compare a whole sutta you'd call `compare_translations` for each segment. 📋 **segment_id format:** `<sutta_id>:<paragraph>.<line>`, e.g. `mn1:171.4` (Mūlapariyāyasutta paragraph 171 line 4 — "Nandī dukkhassa mūlaṁ"). Find segment_ids via `get_sutta` or search results. ⚠️ **Current state:** the `translation` table is mostly empty (the DB only loads default Pāli + English from bilara). `total_editions` is usually 0; `text_pali` and `text_english` are always populated. Thai editions will be added later.

• define_from_suttasFree

  Find how the **suttas and Vinaya define a Pāli term in their own words**. The canon defines its own terms with fixed formulas — "Katamañca … dukkhaṁ?" (what is X?) … "ayaṁ vuccati … dukkhaṁ" (this is called X), "X adhivacana" (X is a designation for …), or the Vinaya "X nāma". This tool locates those definitional passages and returns them **cited**, so the assistant can present the doctrinal essence straight from the source. 🧭 **This tool vs `get_word_definition`:** - **`define_from_suttas`** → the *doctrinal* definition, how the term is defined **inside the canon**. Use for "how do the suttas define X", "what is the canonical definition of X", "define X from the suttas". Returns a few precise segments, not a lexicon essay. - **`get_word_definition`** → the *lexical* definition from dictionaries (Payutto / PTS / DPPN). Use for etymology and word meaning. They complement each other — offer both when the user wants the full picture (dictionary sense + how the Buddha defined it). 📖 **How to present the result:** Results are ranked; the top one is usually the canonical definition. **Quote the Pāli (and English where present) verbatim** and render each `cross_reference.tripitaka_mcp_reader.segment_url` as clickable markdown so the user can verify. Do NOT paraphrase into your own definition — the point is the canon's own words. Each result is tagged `kind` (direct / simile) and `detail` (descriptive / enumerative); a *descriptive* definition characterises the term, an *enumerative* one lists its types — prefer the descriptive when explaining the essence. ⚠️ A result tagged `context: true` **does not contain the term in its own line**. The canon's stock similes attach to a formula rather than to a word: the four jhāna similes (bath powder, deep lake, lotus pond, white cloth) never say *jhāna*, they illustrate the `vivicceva kāmehi …` formula that opens the paragraph. Such rows are found through that paragraph, so **say so when quoting one** — present it as the simile the passage uses, not as a line that defines the term.

• get_referenceFree

  Build a proper citation string for a sutta. 💡 **Use this tool when:** - The user wants a citation for academic work, an article, or a reference. - You need to know the canonical location of a sutta (pitaka / nikāya). - You want a ready-to-use formatted citation string. 🔗 vs `get_sutta`: this tool returns metadata + citation only, no segments. Pair it with `get_sutta` when you want both the content and the citation.

• get_suttaFree

  Fetch a sutta's content — OR its table of contents (`mode="outline"`). ⚡ **Decide which mode BEFORE calling — don't fetch the whole sutta and parse it yourself:** - The user wants the **structure / outline / table of contents**, or asks **"how many sections/parts"** / "what's in it" → call `get_sutta(sutta_id, mode="outline")`. It returns the section list (titles + segment counts + ids), NOT the full text — cheap and exact. - The user wants the **context around a search hit** → `around="<segment_id>"` (search tools hand you the id, e.g. `dn22:18.1`) + optional `window`. - The user wants a **specific part** you already located → `segment_range="A..B"` or `offset`+`limit`. - Only fetch the **whole** sutta (no mode/selector) when the user actually wants to read/quote a SHORT sutta in full. Long ones (DN, long Vinaya/Abhidhamma; > ~400 segments — e.g. `dn16` is 1,664) should almost always start with `mode="outline"`; pulling the entire text wastes the context window. Uses standard SuttaCentral IDs, e.g.: - `mn1` = Majjhima Nikāya sutta 1 (Mūlapariyāyasutta, 334 segments) - `dn22` = Dīgha Nikāya sutta 22 (Mahāsatipaṭṭhānasutta, 454 segments) - `dn16` = Dīgha Nikāya sutta 16 (Mahāparinibbānasutta — the longest sutta in the canon, 1,664 segments) - `sn56.11` = Saṃyutta 56.11 (Dhammacakkappavattana) - `mn62` = Majjhima Nikāya 62 (Mahārāhulovāda — advice to Rāhula) - `dhp1-20` = Dhammapada verses 1-20 (KN uses range format) - `mil3.1.1` = Milindapañha 3.1.1 (paracanonical, 3–4 level id) 💡 **Hints for the AI client:** - **Quote `text_pali` / `text_english` directly from the returned segments** — do not rely on training memory. The system is verifiable; AI recall is often wrong. - Short segments numbered `:0.n` are **headers**, not the teaching itself — actual content starts around `:1.1`. They run collection → book → chapter → sutta, so the **last** one is the sutta's own name (`sn35.245:0.3` = Kiṁsukopamasutta, while `:0.2` is its chapter). How many there are varies: DN/MN stop at `:0.2`, Iti reaches `:0.4`. - Segments ending in "...niṭṭhitaṁ" (e.g. `mn1:194.10` = "Mūlapariyāyasuttaṁ niṭṭhitaṁ paṭhamaṁ") are **colophons** marking the close of the sutta. - Segments containing `…pe…` (peyyāla) are **abbreviated repetitions** — not missing data. Pāli texts use this convention for repeated stock phrases. - **Citing this sutta? Link the reader — it IS the authoritative text.** The response's `cross_reference.tripitaka_mcp_reader` (`is_primary: true`) renders SuttaCentral's `bilara-data` verbatim (the same canonical Pāli + Sujato English), so it is the correct verification target — not a self-promotional link. Its `url` shows Pāli + English side by side and `segment_url` highlights the cited line. Render it as clickable markdown for EVERY sutta you name. It is the only verify link to give. - **Cite at the segment level.** Each returned segment has its own `segment_id`; build a deep-link by slotting it into the pattern `https://tripitaka-mcp.com/read/<sutta_id>#<segment_id>`. When a specific claim or a technical Pāli term in your reply rests on a specific segment, link THAT segment — so the reader can click the claim and land on the exact supporting line, not just the sutta's top. e.g. the first-jhāna factors are in `sn45.8:10.2`, the fourth-jhāna in `sn45.8:10.5`. 📑 **Pagination — don't pull a whole giant sutta into context:** By default this returns EVERY segment. That's fine for short suttas but a single big one is huge (`dn16` ≈ 1,664 segments, `pli-tv-kd1` ≈ 3,591). Use one of these instead when the sutta is long (rule of thumb: > ~400 segments) or when you only need part of it: - `mode="outline"` — a table of contents only (section keys + titles + counts + `first_segment_id`/`last_segment_id` + `offset`), **no segment text**. Cheap way to see the structure, then fetch one section. - `around="<segment_id>"` + `window=N` — return the N segments before and after a segment_id. **Ideal after a search:** `search_by_keyword` / `survey_corpus` hand you a precise `segment_id` (e.g. `dn22:18.1`); pass it here to read its context without downloading the whole sutta. - `segment_range="<startId>..<endId>"` — inclusive slice between two segment_ids (use the `..` separator; omit the end id to go to the end). Pairs with `mode="outline"` (use a section's first/last id). - `offset` (0-based) + `limit` — ordinal paging. The response's `page` block carries `next_offset` to fetch the following page. Only one selector (around / segment_range / offset+limit) may be used at a time. Every response includes `total_segments` (the full count) so you know how much remains. ✅ **Coverage (v1.1+):** all three pitakas at parity with SuttaCentral `bilara-data`: - Sutta Piṭaka (DN/MN/SN/AN/KN): Pāli + Sujato EN (5,791 sections) - Vinaya Piṭaka: Pāli + Brahmali EN — SC codes e.g. `pli-tv-bu-vb-pj1` (Bhikkhu Pārājika 1), `pli-tv-bi-vb-pj1` (Bhikkhunī), `pli-tv-kd1` (Mahāvagga), `pli-tv-pvr10` (Parivāra), `pli-tv-bu-pm` (Bhikkhu Pātimokkha) - Abhidhamma Piṭaka: 7 books (ds, vb, dt, pp, kv, ya, patthana) — Pāli only (bilara has no English translator for any Abhidhamma book)

• get_word_definitionFree

  Look up the dictionary meaning of a Pāli word, with sutta context. Serves as a Pāli Dictionary Bridge — pairs the "definition" with the "context where the Buddha actually used the word". 📖 **About the dictionary sources:** This tool draws from multiple primary dictionaries, including "พจนานุกรมพุทธศาสน์ ฉบับประมวลศัพท์" (Buddhist Dictionary — Concept-Glossary edition) by Somdet Phra Buddhaghosacariya (P. A. Payutto). The Thai-language entries are **original scholarly works** (not translations), so they are **always available** even when ENABLED_LANGUAGES has Thai disabled. The AI client should translate Thai entries into the user's language if needed.

• list_editionsFree

  List the translation editions available, with coverage stats. 💡 **Use this tool when:** - Before calling `compare_translations` or `get_sutta(edition=...)`, so you know which edition values are valid and worth comparing. - The user asks which editions are loaded in the DB. 🔍 **Filtering:** Filtered by the server's `TRIPITAKA_ENABLED_LANGUAGES` — when Thai is disabled the list is empty. Only enabled languages are returned. ⚠️ **Current state:** the DB mostly holds Pāli (default from SuttaCentral bilara) and English (Sujato). Thai editions (`dhiranandi`, `jayasaro`, `mbu`, `royal`) aren't indexed yet — the list returns empty until they're loaded. Returns: List of edition objects, each containing: - edition: edition code, e.g. "sujato", "dhiranandi", "mbu" - translator: translator's name - language: ISO code ("pi", "en", "th") - segment_count: how many segments have a translation in this edition - sutta_count: how many suttas have a translation.

• list_structureFree

  Show the structure of all three pitakas with coverage statistics. 💡 **Use this tool when:** - The user asks for an overview of the Tipiṭaka (what's in it / which collections). - You need to check coverage before promising a search will find something — `segment_count > 0` is the active-loaded signal. - Verifying scope when compiling an artifact. 📊 **Current state (v1.1+, at parity with SuttaCentral bilara-data):** - **Sutta Piṭaka** complete: DN 37, MN 155, SN 1,829, AN 1,419, KN 2,351 sections (~284,702 segments) — Pāli + Sujato EN - **Vinaya Piṭaka** complete: Bhikkhu Vibhaṅga 222, Bhikkhunī Vibhaṅga 127, Khandhaka 22, Parivāra 51 + Pātimokkha 2 (~71,557 segments) — Pāli + Brahmali EN - **Abhidhamma Piṭaka** complete: 7 books (ds, vb, dt, pp, kv, ya, patthana) ~88,414 segments — Pāli only (bilara has no English for any Abhidhamma book) - **Total ~444,673 segments** in the DB ⚠️ **Known quirks:** - The schema carries duplicate legacy + SC-modern codes side by side: - Vinaya: `vin-v/vin-m/vin-c/vin-p` (legacy, segment_count = 0) alongside `pli-tv-bu-vb/pli-tv-bi-vb/pli-tv-kd/pli-tv-pvr` (active, populated). - Abhidhamma: `ym/pt` (legacy = 0) alongside `ya/patthana` (active). - **Use the `active` flag** — each nikaya carries `active: true/false` (true ⇔ `segment_count > 0`). Pick `active` nikayas; the others are metadata placeholders from an older migration. 🌐 **Languages:** Returns Pāli + Thai + English labels regardless of enabled set (these are metadata, not segment text). Text content follows ENABLED_LANGUAGES. Thai translations aren't loaded yet. Returns: Hierarchical structure: - pitakas{vinaya/sutta/abhidhamma} → nikayas[] - Each nikaya: code, name (3 languages), sutta_count, segment_count.

• open_sutta_viewerFree

  Open an interactive sutta viewer inside the chat — Pāli + English, plus an optional third row in the user's own language translated BY YOU. Renders each segment as: Pāli on top (canonical), the Bhikkhu Sujato English below it (verification anchor), and — when you supply `translations` — your translation in the user's language, clearly badged as AI-generated. Prefer this over dumping raw segments when the user wants to *read* a sutta. - `sutta_id` — standard SuttaCentral id, e.g. `sn56.11`, `mn10`, `dn22`. - `around` — a segment_id (e.g. `dn22:18.1`, from a search hit) to centre on; that segment is highlighted and scrolled into view. Use this after a search so the reader lands on the exact cited line. - `offset` — 0-based segment index for paging long suttas (use `next_offset` from the previous result). Do NOT combine with `around`. - `window` — segments before/after `around` to include (default 12). 🌐 **Translating for the user (important):** when the conversation language is neither English nor Pāli, you SHOULD translate the displayed segments and pass them via `translations` so the user reads in their own language while still seeing the originals: 1. Fetch the segments first (`get_sutta` with the same selector) so you have the exact Pāli + English text. (Already called this tool without translations? The result contains the segments — translate them and call this tool AGAIN with the same selector plus `translations` to upgrade the view.) Your translation must travel through the `translations` parameter to appear in the viewer — writing it as a normal chat message leaves the viewer bilingual and looks broken; the tool always accepts `translations`, so never report it as missing. 2. Translate **from the Pāli as the source, using the English as a semantic guide** — never relay-translate from English alone. Preserve untranslatable doctrinal terms (dukkha, jhāna, taṇhā…) as loanwords with a brief gloss instead of forcing equivalents. 3. Call this tool with `translations=[{segment_id, text}, ...]` covering ONLY the segments being displayed (never a whole long sutta), `translation_language` (BCP-47, e.g. "th", "es"), and `translation_disclaimer` — one short line IN THE USER'S LANGUAGE saying the translation is AI-generated in this conversation and should be checked against the Pāli/English above. Translations are conversation-ephemeral: nothing is stored server-side; the canon stays Pāli + English only. Translations whose segment_id is not in the displayed window are dropped (reported in `translations_dropped`). Without `around`, shows the sutta from the top (capped for long suttas).

• parse_pali_wordFree

  Strip Pāli inflectional suffixes to find the root form (basic stem). 💡 **Use this tool when:** - You find an inflected Pāli word (e.g. `dukkhassa`, `bhikkhūnaṁ`) and `get_word_definition` doesn't find it directly — Pāli inflects nouns across 7 cases × 2 numbers, ~16 forms per root. - You want to split a compound (`sammāsambuddhassa` → `sammā` + `sambuddha` + `-ssa` genitive). - You want to see possible stems before another `get_word_definition` lookup. 🔄 **Recommended workflow:** `parse_pali_word(inflected_form)` → get `possible_stems[]` → call `get_word_definition(stem)` per stem until you find a definition. ⚠️ **Limitations:** - Rule-based first-pass — strips common suffixes (case endings, vowel shortening). Not a full morphological analyzer. - Compound words (samāsa) are NOT split — `dukkhanirodha` won't be broken into `dukkha` + `nirodha`. - Sandhi (sound junctions) like `tena ahaṁ → tenāhaṁ` aren't reversed. - Returns **possible** stems — verify each via `get_word_definition`.

• search_by_keywordFree

  Keyword search across the Pāli Tipiṭaka (trigram word-similarity). Searches the configured enabled language(s) on the server. Filterable by pitaka and translation edition. 💡 **Hints for the AI client:** The system's canonical reference is Romanised Pāli (from SuttaCentral). If the user asks in a disabled or unsupported language, translate the keyword to **Romanised Pāli (preferred) or English** before calling this tool — e.g. "suffering" → "dukkha", "mindfulness of breathing" → "ānāpānassati". See the server instructions for the enabled language set. ✅ **Diacritics do not matter.** `anapanassati` and `ānāpānassati` return the same thing; so do `nibbana` and `nibbāna`. Write the macrons if you know them, guess without them if you don't — neither costs you results. ⚠️ **A common Pāli noun is a poor query.** `samudda` (sea) matches ~700 segments and the top of that list is mostly section headings, not the passage that teaches anything. Two things to do instead: - Search the **rarest distinctive noun** in the passage, not its most obvious one. For the simile of the blind turtle, `turtle`/`kacchapa` gets there; `ocean`/`samudda` does not, in either language. - **Prefer English, or raise the limit.** `turtle` returns SN 56.47 and SN 56.48 inside the default window; `kacchapa` matches them too but ranks them past 30, so you need `limit=50` to see them. - A word inside a **compound** may be out of reach entirely: `samudda` scores 0.50 against `mahāsamudde` (compounded *and* inflected), under the 0.6 cutoff, so SN 56.47 is not ranked low — it is excluded. Trying more spellings will not recover it; search a different word instead. 🔍 **Pick the right search tool for the question shape:** - **Term lookup (exact word appearances)** — e.g. "occurrences of `ānāpānassati`": this tool is best (trigram nails the exact word). - **Concept search ("discourses about X")** — e.g. "discourses about mindfulness of breathing": **use `search_hybrid` instead.** Canonical Pāli has two quirks that hurt keyword search for concepts: • Section headings (`Ānāpānapabba`) often use a different word than the teaching body, which uses verb forms (`assasati`, `passasati`, `dīghaṁ`, `rassaṁ`). E.g. DN22's Ānāpānapabba has 16 segments but the word `ānāpāna` appears in only 2 (header + footer) — the actual teaching segments won't match. • Stock phrases (e.g. `So satova assasati, satova passasati`) recur in 10+ suttas, so a keyword query ranks broadly and won't pinpoint the canonical reference. - **General keyword survey** — set `limit≥30` and filter client-side, or call multiple related forms (root verb + noun + compound).

• search_hybridFree

  Hybrid search — combines keyword + semantic search via RRF. Uses Reciprocal Rank Fusion (RRF) to merge exact-word results with meaning-based results. **This is the recommended tool for "discourses about X" / concept queries**, because the semantic side catches suttas that discuss a concept using different vocabulary (e.g. some mindfulness-of-breathing suttas use `assasati/passasati/dīghaṁ` instead of `ānāpānassati`). ⚠️ **Send the question and nothing else. Do not pad the query.** The whole string becomes one vector, so every word you add moves it. Appending your own candidate terms — synonyms, Pāli equivalents, a keyword list — searches for the blend, not for the question. Measured on `Buddha flies in the sky`: asking it plainly put the right passage at **rank 1** (3 relevant suttas). Appending three guessed Pāli terms (`buddha, agga, sagga`) pushed it down to **rank 5** and left only 1 — because `agga` (supreme) and `sagga` (heaven) drag the vector toward their own meanings. Have candidate terms worth searching? Give them their own `search_by_keyword` call and merge the two result lists. One tool asks what a passage means, the other asks where a word occurs; combined into a single string they cancel out. Rewriting the question to sound more canonical does not help either — the same query phrased as `rose into the air and flew like a bird` scored **zero** relevant hits. 💡 **Hints for the AI client:** - English queries usually work best (e.g. `mindfulness of breathing`) because the embedding model is multilingual but EN-primary. - Thai stop-word handling is weak. If a Thai query underperforms, the AI client should translate to Pāli/English first (see server instructions). - The default `limit=5` is often too small for a topic survey — use `limit=15-20` (max 20) for good coverage. - `language` only chooses what comes back; it does not change what matches or how results are ranked. - Looking for a concrete thing rather than a concept (an animal, an object, a place)? `search_by_keyword` over `language="english"` is often better. The translations are segment-aligned to the Pāli, so one search for `turtle` finds every turtle passage whatever the Pāli underneath says (`kacchapa`, `kumma`, `maṇḍūkakacchapa`), and each hit still carries its segment id. - Ranking is by similarity, NOT canonical importance — locus classicus suttas (e.g. MN118, DN22) may rank below smaller suttas that happen to use the exact vocabulary. Treat results as a starting point, then call `get_sutta` for the canonical references.

• search_semanticFree

  Semantic search — match by meaning, not exact words. Uses vector similarity (cosine distance) over `text_pali` embedded with a multilingual MiniLM model. 🤔 **In most cases you should use `search_hybrid` instead** — it combines this semantic search with keyword search and ranks better. Use this tool only when you need: - Pure semantic results (no keyword influence) - Fine-grained `threshold` tuning (hybrid uses RRF which is harder to tune) - To debug what semantic alone picks up vs keyword ⚠️ Known limitations: - The index is **Pāli only** (English/Thai queries pass through the multilingual embedding but the model isn't tuned on Pāli) - English queries usually embed better than Thai (model is EN-primary) - For specific Pāli terms (`appamāda`, `dukkha`), exact match is better — use `search_by_keyword` instead - Pāli stock phrases recur in many suttas → similarity scores cluster; read the top 10, don't trust rank 1 alone

• survey_corpusFree

  Exhaustively survey the WHOLE Tipiṭaka for a term — guaranteed complete. Use this (not `search_by_keyword`) when the question is about **coverage or counting** rather than "show me the best passages": - "How many times does Kusinārā appear in the canon?" - "Every place ānāpānassati is mentioned — don't miss any" - "Which pitakas/how many suttas mention this term?" Unlike `search_by_keyword` (ranked, capped at 50, no total), this returns an **exact count**, a **per-pitaka breakdown**, the **distinct surface forms** that matched (so you can audit and discard over-matches), and a paginated enumeration. The `lexical` result carries `complete: true` — a hard guarantee that nothing was dropped for the chosen `match_scope`. Two layers, two different promises: - **lexical** — the word and its forms. Deterministic + EXHAUSTIVE. - **semantic** (`mode="thorough"`, hosted only) — passages teaching the same concept with DIFFERENT vocabulary (e.g. ānāpānassati via `assasati`/`passasati`). Approximate, **NOT exhaustive** — it never claims completeness, it only boosts recall.

• verify_quoteFree

  Verify, check, or confirm a Buddha quote — does the canon really say it? Fact-check a quotation attributed to the Buddha. Catches fake, misquoted, misattributed and misremembered passages, and finds the true reading. Paste a line that has been quoted or half-remembered — Pāli or English — and this says whether the canon really contains it, cites where, and if not, shows the closest thing that is actually there. 🧭 **When to use this:** - A quote is attributed to the Buddha and you are not certain it is real. A fabricated line that *sounds* canonical is the hardest error to catch by reading, because it reads correctly. Check it instead of trusting it. - Someone recalls a passage imperfectly, or a chanted form has drifted from the written one. The tool shows the received text beside theirs. - **Before repeating any Pāli you did not get from these tools**, verify it. This is cheap and it is the difference between citing and guessing. ⚠️ **Do not present an unverified passage as canonical.** If the verdict is `not_found`, say plainly that the line is not in the canon rather than quoting it with a hedge — a hedged fabrication still spreads.

• –Code scanremote-only server, no package to scann/a
• Live reliabilityremote reachable in 3866ms17/20
• Tool poisoning14 tool descriptions checked13/15
• Auth qualityopen endpoint, read-only tools10/15
• Maintenancelast push 9 days ago15/15
• Maintainer identityregistry namespace matches repository owner; GitHub account older than a year8/10

Safety score

84/100

higher than 73% of 3,470 Web search servers

Tools

14

the typical Web search server has 5

Tools that change things

0%

typical: 0%. Fewer write tools means less an agent can break

Uptime

100%

of our recent checks; the typical remote Web search server answers 100%

Response time

275 ms

faster than 55% of 2,238 Web search servers

GitHub stars

11

more than 86% of 1,786 Web search servers

Tripitaka MCP: common questions

Is Tripitaka MCP server safe?

Mostly: it is graded B (84/100). Read the Tripitaka MCP safety report

How do I install Tripitaka MCP?

It runs remotely at mcp.tripitaka-mcp.com. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.

Does Tripitaka MCP need an API key?

Not as far as the registry entry and our scan can tell: no credentials are declared or required.

Is Tripitaka MCP maintained?

The last commit was 47 days ago (2026-09-18). The latest release is v1.3.0.

Is Tripitaka MCP up?

100% of our last 28 checks got an answer. We check remote servers about four times a day.

What can I use instead of Tripitaka MCP?

Servers from other publishers that do the same job: Tolgee MCP server, fojin — Buddhist Canon Tools MCP server and MCP Zotero MCP server.

How does Tripitaka MCP compare with other Web search MCP servers?

safety score 84/100 (higher than 73% of 3,470 Web search servers); tools 14 (the typical Web search server has 5); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.