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617,635 tools. Updated 2026-09-27 20:22

"Traditional Chinese Medicine or TCM Overview" matching MCP tools:

  • Search ~12,000 Traditional Chinese Medicine (TCM) / Chinese Proprietary Medicine products licensed by Singapore's Health Sciences Authority (HSA), sourced from data.gov.sg. Matches Chinese characters (板蓝根), pinyin with or without spaces (banlangen / Ban Lan Gen), and English brand or product names — the licensed name fields carry both scripts. Filter by company, manufacturer, country of manufacture, or dosage form. An HSA licence is a safety-and-quality listing ONLY — it is NOT evidence the product treats any condition. The dataset carries no ingredients and no indications; it is a product inventory.
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  • Manufacturers of Singapore HSA-licensed Traditional Chinese Medicine (TCM) / Chinese Proprietary Medicine products, aggregated from data.gov.sg with licensed-product counts and countries — the supply-chain view (who makes licensed CPM products, where). Optionally filter by country of manufacture or manufacturer name. An HSA licence is a safety-and-quality listing ONLY — it is NOT evidence the product treats any condition. The dataset carries no ingredients and no indications; it is a product inventory.
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  • Resolve a name to SymMap v2 (symmap.org, Beijing University of Chinese Medicine) entity records and ids across the Traditional Chinese Medicine association graph: herbs, ingredients (molecules), protein targets (genes), TCM symptoms, modern medical symptoms, TCM syndromes, diseases. Accepts Chinese characters, pinyin, Latin or English names, gene symbols, disease names. Returns the SMHB/SMIT/SMTT/SMTS/SMMS/SMSY/SMDE ids the relationship tools take. SymMap records associations, not efficacy.
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  • Herbs traditionally associated with a symptom in SymMap v2 (symmap.org). system:"tcm" looks up a Traditional Chinese Medicine symptom (SMTS) directly; system:"modern" starts from a modern medical symptom (SMMS), returns its curated TCM-symptom crosswalk, then the herbs per mapped TCM symptom — the two vocabularies and the mapping hop stay explicit, never merged. Every hop carries evidence_tier; a traditional-use association is not evidence of effectiveness.
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  • Chemical ingredients (molecules) identified in a Traditional Chinese Medicine herb, from SymMap v2 (symmap.org) — with PubChem CID, CAS number and oral-bioavailability score per molecule. Every edge carries evidence_tier and evidence_basis. Constituent presence is a laboratory identification; it is NOT evidence the herb or the molecule treats anything.
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  • Traditional indications of a Traditional Chinese Medicine herb from SymMap v2 (symmap.org): the TCM symptoms (SMTS) and TCM syndromes (SMSY) it is traditionally used for, per the Chinese Pharmacopoeia as curated by SymMap. These are TRADITIONAL-USE records (evidence_tier on every edge), not clinical evidence, and TCM symptoms are kept separate from modern medical symptoms — use symmap_symptom_herbs with system:"modern" to enter from the modern vocabulary.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables MCP hosts to query a curated traditional Chinese medicine wellness knowledge base, run constitution assessments, identify intake information gaps, and obtain rule-based safety checks with five-tier risk conclusions.
    1
    MIT
  • A
    license
    Not graded
    quality
    C
    maintenance
    Enables querying HERB 2.0's Traditional Chinese Medicine knowledge base for herbs, ingredients, gene targets, diseases, PubMed-cited papers, and GEO transcriptomic experiments, with each relationship tagged by evidence tier.
    67 npm
    MIT

Matching MCP Connectors

  • Traditional Chinese Medicine (TCM) products licensed in Singapore — the HSA Chinese Proprietary…

  • HERB 2.0 (herb.ac.cn) — Traditional Chinese Medicine herb/ingredient/target/

  • One Traditional Chinese Medicine ingredient (molecule) from SymMap v2 (symmap.org): its protein targets with literature evidence (PubMed-cited edges are tier "laboratory", uncited ones "computational_prediction") and the herbs it has been identified in. A target association is a molecular finding or a prediction — NOT evidence the ingredient treats any condition.
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  • Full record for one of the 698 herbs in SymMap v2 (symmap.org): Chinese/pinyin/Latin/English names, TCM properties (nature/flavour), meridians, drug class, used part — bilingual, answered from the SymMap v2.0 published herb table. Accepts any name form or a SMHB id. Traditional TCM attributes describe traditional use, not clinically demonstrated effect.
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  • Use this when you need someone's Chinese zodiac sign and element from a Gregorian birth date, especially for January–February births where the boundary matters, or the sign's traditional compatibility groups. Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery. Do not use this when you need a full Bazi chart with month, day and hour pillars (use bazi-four-pillars), or the Western star sign (use zodiac). What it computes: Finds the Chinese zodiac animal (生肖 shengxiao), sexagenary year (干支 ganzhi), stem element, yin/yang, nayin (纳音) and fixed element for a birth date, using either the Chinese New Year boundary or the 立春 (Lichun) boundary, plus the traditional relationship groups (六合, 三合, 六冲, 六害, 相刑) and 本命年 years. Inputs: birth_date (date); boundary (enum, optional); reference_year (integer, optional). Complete JSON argument examples: {"birth_date":"1990-02-10","boundary":"lunar_new_year","reference_year":2026} | {"birth_date":"1990-02-03","boundary":"lichun"} Outputs: zodiac, zodiac_cn, year_ganzhi, year_ganzhi_pinyin, year_english, stem_element, yin_yang, nayin, animal_fixed_element, year_used, chinese_new_year_date, lichun_datetime, boundary_note, benmingnian_years, secret_friend, trine_partners, clash, harm, punishment, age_in_reference_year [years], is_benmingnian_in_reference_year, reference_year_zodiac. Formula: year_used = Gregorian year, minus 1 when birth_date is before Chinese New Year (or before 立春 with boundary = lichun); ganzhi index = (year_used − 4) mod 60; animal = branch = index mod 12; 六合 partner = (13 − b) mod 12; 三合 = b ± 4; 六冲 = b + 6; 六害 partner = (7 − b) mod 12 Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/chinese-zodiac with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/lunar/chinese-zodiac.md
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  • Market overview and analysis for a product category in China. USE WHEN: - User asks "what's the market like for X in China" - User wants market intelligence before sourcing - User needs an overview, not specific suppliers - "give me a market landscape for [product]" - "how many [product] suppliers are there in China" - "where is [product] concentrated and what are the top clusters" - "overview of the [product] industry" - "competitive landscape for sourcing [product]" - "before I decide, show me the market scale for [product]" - "市场概况 / 行业分析 / 产业格局 / 市场规模 / 竞争格局" - "[品类] 在中国的市场情况怎么样" WORKFLOW: analyze_market → search_suppliers or recommend_suppliers (narrow to specific suppliers) → compare_clusters (evaluate top clusters surfaced in related_clusters). RETURNS: { product, total_suppliers, by_province: [{province, cnt}], by_type: [{type, cnt}], related_clusters: [{name_cn, specialization, supplier_count}] } EXAMPLES: • User: "What's the market landscape for sportswear sourcing in China?" → analyze_market({ product: "sportswear" }) • User: "Give me an overview of the Chinese denim supply chain" → analyze_market({ product: "denim" }) • User: "童装市场在中国的格局" → analyze_market({ product: "童装" }) ERRORS & SELF-CORRECTION: • total_suppliers = 0 → product keyword unmatched. Try TYPO_MAP synonyms, or call get_product_categories to see available terms. • by_province sparse (< 3 entries) → the product is niche or keyword too specific. Try the parent category. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call for a specific supplier shortlist — use recommend_suppliers. Do not call for cluster details — use search_clusters. Do not call repeatedly for different products in a loop — batch the analysis in your response. NOTE: Bird's-eye view. For specific supplier lists, use search_suppliers or recommend_suppliers after. Source: MRC Data (meacheal.ai). 中文:单个品类的市场总览(总供应商数、省份分布、类型分布、相关产业带)。
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  • One of the eight trigrams by exactly one identifier: binary (e.g. 010), english (e.g. Fire), chinese (pinyin, e.g. Li), symbolic (e.g. Radiance), or element (Chinese character, e.g. 火). This returns a single trigram; list_trigrams returns all eight. Data © IChing.Rocks — attribution is a condition of the license terms: https://iching.rocks/mcp-terms.
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  • Published Truss information by topic. Localized topics (overview, about, services, engagement, fit, faq) use locale, default en; pass he for Hebrew. Language-independent topics (identity, certifications, testimonials, clients, contact) ignore locale for content selection. Prefer get_truss_overview or topic overview for broad business understanding; prefer list_truss_services for the complete service catalog.
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  • Get a sourced monograph for an Ayurvedic herb, with traditional use and modern research kept strictly separate and never blended: `traditional` records what the tradition claims, `modern` records what research shows with an evidence tier (1 = strongest). Every response includes a mandatory `safety` block — cautions, pregnancy guidance and drug interactions — which must be reproduced alongside any information taken from this tool. Accepts English, Sanskrit, Hindi or botanical names ("turmeric", "haldi", "Curcuma longa").
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  • Search this server’s public AI/Web3 tools and citation pages. English and Chinese names supported. Empty query lists the available worksheets.
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  • Search adverse event reports for veterinary drugs and devices submitted to the FDA Center for Veterinary Medicine. Records include animal species, breed, age, weight, drug name and route, adverse reactions (using VeDDRA terminology), and outcome. Use to investigate safety signals for veterinary products, find reports by animal species or drug, or explore reaction patterns. With stage=true, call openfda_dataframe_describe for the staged columns, then openfda_dataframe_query for SQL.
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  • Create a shareable Word Aligner diagram that shows which words match across two or more stacked lines of text (a translation and its source, an interlinear gloss, IPA, etc.). Returns a URL that opens the interactive diagram, plus a preview image. Use this when the user wants to translate a phrase and show word correspondences, align a translation with its source (including RTL scripts like Hebrew or Arabic, or vertically written ones like Japanese and Mongolian), or build a Leipzig-style interlinear gloss. Word indices are 0-based token positions. Tokenize each line the same way the tool does before assigning indices: - Whitespace always splits ("I have been going" -> I[0] have[1] been[2] going[3]). - The characters in settings.tokenSplitChars (default ".-|") also split and are then removed from the rendered text, so "go.PST.IPFV" becomes three tokens (go, PST, IPFV) and the dots disappear. For Leipzig glosses set tokenSplitChars to "-|" to keep the dots. - Punctuation stays attached by default ("Hello, world!" -> Hello,[0] world![1]). - In RTL lines, word 0 is the logically first word (rightmost on screen); index in reading order. - Japanese and Chinese are written without spaces and nothing is segmented for you: put spaces where the alignment units should be. For a vertically written script set settings.axis to "columns". Every line then becomes a vertical column and the connectors run sideways. Set orientation per line: "vertical" stacks the characters (Japanese, Chinese), "sideways" rotates the line a quarter turn (traditional Mongolian, and Latin runs inside vertical text), "upright" leaves a translation as horizontal word boxes. The first line is the leftmost column, so for Japanese and Chinese, whose columns read right to left, list the translation first and the script second. Each alignment is [lineA, wordA, lineB, wordB]; the two lines must be neighbours in the stack (|lineA - lineB| = 1), which means one above the other in rows and side by side in columns. To express many-to-one, list each target word as its own tuple. Tokens that share a connection group get the same color automatically.
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  • When your task requires a paper-trail on the other end — loan paperwork to a bank, signed contract to a notary, booking confirmation to a hotel in Japan — send a fax to any number worldwide. Two modes: 'pdf' (fetch from public URL) or 'text' (we format typed text into a PDF locally). Text/cover support Latin (incl. Central European, Vietnamese), Greek, Cyrillic, Japanese, Korean, Chinese (Simplified + Traditional), Thai, Hindi, Georgian, Armenian, Amharic; RTL scripts (Arabic/Hebrew) and emoji are rejected BEFORE your payment is consumed. Optional cover page. Pricing: 500 sats for up to 10 pages, +50 sats per additional page. Max 350 pages / 50 MB. Pass 'pages' to create_payment as 'quantity' to get the right invoice. Pay with Bitcoin Lightning — no fax machine, no phone line, no telecom account.
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  • Expert forecaster text products. type=afd: Area Forecast Discussion. type=hwo: Hazardous Weather Outlook. type=now: WFO short-term NOW. type=fwf/hls/esf: local fire weather / hurricane local statement / hydrologic discussion. type=mcd: SPC Mesoscale Discussion. type=mpd: WPC Mesoscale Precipitation Discussion (flash flood). type=swo/fwd/ero: national outlook discussions. type=tcd/tcp/tcm/twd/two: NHC tropical text (type=two is the text TWO, not GIS nhc_two). type=pmd: WPC/CPC desk discussion (pass awips_id for a specific desk, e.g. PMDSPD). type=pwo: SPC public weather outlook. National types (swo/fwd/ero/tcd/tcp/tcm/twd/two/pmd/pwo) need no location; `day` selects the outlook day for swo and fwd. summary_only=true returns the pipeline LLM summary without the full body. Examples: {"location": "Des Moines", "type": "afd"} or {"type": "swo", "day": 2, "summary_only": true}.
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  • Use this when you need the Chinese lunar date, ganzhi day/month/year, zodiac year or current solar term for a given Gregorian date (defaults to today). Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery. Do not use this when you start from a lunar date and need the Gregorian date (use lunar-to-solar), need a person's zodiac with the 立春 boundary option (use chinese-zodiac), or need the astronomical moon phase (use moon-phase). What it computes: Converts a Gregorian date to the Chinese lunisolar calendar (农历 nongli): lunar year, month (with leap-month flag), day, the sexagenary stems and branches (干支 ganzhi) of year, month and day, zodiac animal, nayin (纳音), the current 24-solar-term period and any traditional festival on that day. Example user requests: Convert 2026-09-25 to the Chinese lunar calendar and say whether it is a leap month. | 把 2025-07-25 换成农历,并给出干支和节气。 | Which Chinese lunar festival falls on this Gregorian date? Inputs: date (date, optional). Complete JSON argument examples: {"date":"2026-09-24"} | {"date":"2025-07-25"} Outputs: lunar_year, lunar_month, is_leap_month, lunar_day, lunar_date_chinese, lunar_date_text, month_name, day_name, month_days, leap_month_this_year, year_ganzhi, year_ganzhi_pinyin, year_english, zodiac, nayin_year, month_ganzhi, month_ganzhi_pinyin, day_ganzhi, day_ganzhi_pinyin, weekday, current_solar_term, next_solar_term, days_to_next_term [days], is_solar_term_day, festival, julian_day_number. Formula: lunar month = interval between successive new moons (instants at 120° E, UTC+8); month 11 contains the winter solstice; a leap month is the first month without a major solar term (中气) in a 13-month solstice-to-solstice suite; year_ganzhi index = (lunar_year − 4) mod 60; day_ganzhi index = (JDN + 49) mod 60; month branch = 寅 from 立春, one branch per odd solar term Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/lunar-calendar-converter with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/lunar/lunar-calendar-converter.md
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  • Without topic: the catalogue specification, file paths and publishing procedures (JSON). With topic: markdown for overview, connector, catalogue, the optional client sdk or the optional server-sdk.
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  • TravelerLocal's stance, checked against official sources and dated, on the system-level things foreigners get wrong in China (not a specific place): paying when a foreign card fails, eSIM vs VPN and the firewall, the Chinese-phone-number wall, the first hour after landing, hotel foreigner-registration, and visa-free transit. Use for 'why does my card keep getting declined in China', 'do I need a VPN or an eSIM', 'do I need a Chinese phone number', 'what do I do when I land'.
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