"namespace:io.github.midasflowai-lab" matching MCP tools:

• convert_color

  rnv-color-mcp

  Convert a color between formats. Input accepts a hex, CSS name, RNV brand name, or saved-palette reference. With `to` set to one of hex/rgb/hsv/hsl/lab, returns just that format; otherwise returns all of them. Read-only and deterministic, with no side effects. Use for format conversion of a single color; to blend several colors into one use mix_colors, and to compare two colors use color_difference.

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• mix_colors

  rnv-color-mcp

  Blend up to 12 colors into one. Each color may be a hex (#d2bc93), a CSS name (red), an RNV brand name (brand gold, near-black), or a saved-palette reference (Spring line, or 'Spring line:2' for its 2nd swatch). Optional integer weights bias the blend (defaults to equal). mode selects the model: rgb/hsv/lab are digital blends (lab is perceptual and the default, best for on-screen color); paint mixes pigments via Kubelka-Munk physics (colors darken like real paint, use it for physical-media matching); ryb is the artist's color wheel; cmy is subtractive like printer inks. Returns hex and rgb. Read-only and deterministic: it computes a result and stores nothing, so it is safe to call repeatedly with no side effects. Use to combine multiple colors into a single blend; to convert one color between formats use convert_color, and to measure how far apart two colors are use color_difference.

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• search_suppliers

  MRC Data — China's Apparel Supply Chain Infrastructure

  Search verified Chinese apparel manufacturers, apparel factories, and clothing suppliers. USE WHEN user asks: - "find me a clothing manufacturer in China / Guangdong / Zhejiang" - "who makes [t-shirts / suits / denim / activewear] in China" - "I need a BSCI / OEKO-TEX certified apparel factory" - "looking for OEM / ODM apparel supplier with MOQ < N" - "find factories with production capacity > N pieces/month" - "list factories that export to the US / EU / Japan" - "show me trading companies in Yiwu / Shenzhen / Shanghai" - "which suppliers in [province] make [product]" (follow-up drill-down) - "give me another page of suppliers" (pagination via offset) - "who can produce knit tops under 300 MOQ" - "search by company name 新鑫 / Xinxin / Texhong" - "find workshop-scale suppliers for small batch sampling" - "搜供应商 / 找服装厂 / 找制衣厂 / 找代工厂 / 找外贸公司" - "帮我在[省份]找[品类]工厂，产能至少 N 件/月" Filters: province, city, factory type (factory/trading_company/workshop), product category, minimum monthly capacity, compliance status, quality score. Returns paginated supplier list with company name, location, monthly capacity (lab-verified), compliance, quality score. WORKFLOW: Primary entry point for supplier discovery. search_suppliers → get_supplier_detail (for full 60+ field profile) OR compare_suppliers (side-by-side for up to 10 IDs) OR find_alternatives (diversify the pool) OR check_compliance (verify export readiness) OR get_supplier_fabrics (see their fabric catalog). RETURNS: { has_more: boolean, available_dimensions: string[], data: [{ supplier_id, company_name_cn, company_name_en, type, province, city, product_types, quality_score, verified_dims: "5/8", coverage_pct }] } EXAMPLES: • User: "Find BSCI-certified denim factories in Guangdong with MOQ under 500" → search_suppliers({ province: "Guangdong", product_type: "denim", compliance_status: "compliant", limit: 10 }) • User: "Who makes activewear for Lululemon in China?" → search_suppliers({ product_type: "activewear" }) — then filter results by client brand in get_supplier_detail • User: "我要在浙江找做牛仔的工厂，产能大于 10 万件" → search_suppliers({ province: "Zhejiang", product_type: "denim", min_capacity: 100000 }) • User: "Show me the next 10 trading companies in Yiwu" → search_suppliers({ city: "Yiwu", type: "trading_company", limit: 10, offset: 10 }) ERRORS & SELF-CORRECTION: • Empty data array → try these in order: (1) remove min_capacity filter, (2) drop city but keep province, (3) broaden product_type to parent category (e.g. "denim" → "bottoms"), (4) drop compliance_status, (5) try recommend_suppliers for ranked fit. • "Invalid province" → use English (Guangdong) or standard Chinese (广东). Supported: 31 mainland provinces + HK/Macau. • product_type returns 0 → the TYPO_MAP normalizes common variants; try synonyms ("tee" → "t-shirt", "jeans" → "denim", "运动服" → "activewear"). • Rate limit 429 → wait 60 seconds. Do not retry immediately. • Empty after 3 retries → tell user: "I couldn't find suppliers matching [criteria]. Would you like me to broaden the search?" AVOID: Do not call this tool in a loop across provinces — call get_province_distribution first to see where supply is concentrated. Do not use this for ranked "best fit" recommendations — use recommend_suppliers. Do not fetch details by looping — use compare_suppliers with up to 10 IDs. NOTE: Use this for FILTERING by exact criteria. For ranked recommendations based on sourcing needs, use recommend_suppliers instead. Source: MRC Data (meacheal.ai). 中文：搜索经过核查的中国服装供应商档案，按地区、类型、产能、品类、合规状态等筛选。

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• list_starters

  pdfzen

  List pdfzen's 45 public starter templates — invoices, receipts, contracts, certificates, NDAs, letters, reports, resumes, boarding passes, menus, bank statements, lab reports, lease agreements, performance reviews, and more. Returns an array of { slug, name, description, icon, pageOptions, fonts, dataKeys }. Free, no payment, no auth required. Call this first to discover what fits the user request, then optionally call get_starter to see the expected data shape, then call render_template_to_pdf to produce the PDF.

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• get_founders

  Origine Paris

  Returns the two founders of Origine Paris, the house of recycled 18ct gold and IGI-certified lab-grown diamond jewellery. Use it for a quick roster (names, roles, Wikidata QIDs, short bios); for one founder's full biography and career use get_person_profile instead, not this. Read-only and side-effect-free: it returns a structured list of the founders plus a text copy, with the sources, the index timestamp and the canonical URL, taken from the site JSON-LD and Wikidata and served as published; absent values are reported as "unknown", never invented.

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• mix_colors

  rnv-color-mcp

  Blend up to 12 colors into one. Each color may be a hex (#d2bc93), a CSS name (red), an RNV brand name (brand gold, near-black), or a saved-palette reference (Spring line, or 'Spring line:2' for its 2nd swatch). Optional integer weights bias the blend (defaults to equal). mode selects the model: rgb/hsv/lab are digital blends (lab is perceptual and the default, best for on-screen color); paint mixes pigments via Kubelka-Munk physics (colors darken like real paint, use it for physical-media matching); ryb is the artist's color wheel; cmy is subtractive like printer inks. Returns hex and rgb. Read-only and deterministic: it computes a result and stores nothing, so it is safe to call repeatedly with no side effects. Use to combine multiple colors into a single blend; to convert one color between formats use convert_color, and to measure how far apart two colors are use color_difference.

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• get_supplier_detail

  MRC Data — China's Apparel Supply Chain Infrastructure

  Get the complete profile of a single Chinese apparel supplier by ID. PREREQUISITE: You MUST first call search_suppliers or recommend_suppliers to obtain a valid supplier_id. Do not guess IDs. USE WHEN user asks: - "tell me more about [supplier]" / "show full details for sup_XXX" - "what certifications does this factory hold" - "what's their monthly capacity / worker count / equipment list" - "can [supplier] export to US / EU / Japan / Korea" - "give me the full profile / dossier / fact sheet for [supplier]" - "how verified is this supplier's data" (returns coverage_pct + 8 dimensions) - "what's their ownership type — own factory or broker" - "show payment terms / lead time / sample turnaround for sup_XXX" - "这家供应商具体情况 / 详细资料 / 工厂档案" - "[供应商] 的合规 / 认证 / 出口资质" Returns 60+ fields including: monthly capacity (lab-verified), equipment list, certifications (BSCI/OEKO-TEX/GRS/SA8000), ownership type (own factory vs subcontractor vs broker), market access (US/EU/JP/KR), chemical compliance (ZDHC/MRSL), traceability depth, and verified_dimensions breakdown showing exactly which of the 8 dimensions (basic_info, geo_location, production, compliance, market_access, export, financial, contact) have data. WORKFLOW: search_suppliers → pick supplier_id → get_supplier_detail → optionally get_supplier_fabrics (fabric catalog) OR check_compliance (market export readiness) OR find_alternatives (backup pool) OR compare_suppliers (side-by-side evaluation). RETURNS: { data: { supplier_id, company_name_cn/en, type, province, city, product_types, worker_count, certifications, compliance_status, quality_score, verified_dimensions: { verified_dims: "5/8", coverage_pct, dimensions: {...} } } } EXAMPLES: • User: "Show me the full profile for sup_001" → get_supplier_detail({ supplier_id: "sup_001" }) • User: "What certifications does Texhong hold and can they export to EU?" → get_supplier_detail({ supplier_id: "sup_texhong_042" }) — then inspect certifications + eu_market_ready; follow with check_compliance for formal verification • User: "我要看 sup_123 的完整档案" → get_supplier_detail({ supplier_id: "sup_123" }) ERRORS & SELF-CORRECTION: • "Supplier not found" → the supplier_id is invalid or outside free-tier access. Re-run search_suppliers to obtain a fresh valid ID. Do not guess sequential IDs. • Field returns null → that dimension is unverified for this supplier. Check verified_dimensions.coverage_pct before asserting data. If coverage_pct < 50, warn the user: "This supplier's record has limited verified data (X/8 dimensions). Consider find_alternatives for better-documented options." • "not available for public access" → this supplier is in the reserve pool (paid tier only). Use search_suppliers filters data_confidence=verified to stay in public tier. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call this for multiple suppliers in a loop — use compare_suppliers with up to 10 IDs at once. Do not call to browse the database — use search_suppliers or get_province_distribution for discovery. NOTE: Source: MRC Data (meacheal.ai). Every numeric field shows both declared and lab-verified values where available. 中文：按 ID 获取单个供应商的完整档案（含维度覆盖率详情）。

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• search_fabrics

  MRC Data — China's Apparel Supply Chain Infrastructure

  Search the Chinese fabric and textile database with lab-tested specifications. USE WHEN user asks: - "find me a [cotton / polyester / nylon / wool / linen] fabric for [t-shirts / jeans / suits]" - "I need 180gsm jersey knit with verified composition" - "fabrics under N RMB/meter for womenswear" - "compare lab-tested fabric weight across suppliers" - "show me functional fabrics for activewear / sportswear" - "what woven fabrics work for shirting" - "list organic / GOTS / recycled fabrics" - "I want heavyweight denim above 12 oz" - "fabrics with stretch / spandex content 2-5%" - "give me another page" (pagination via offset) - "lab-verified composition for [product]" (quality check) - "找面料 / 搜面料 / 查面料 / 找布料 / 打样面料" - "我要做 T 恤，帮我找克重 180-220 的针织面料" Filters: category (woven/knit/nonwoven/leather/functional), weight range (gsm), composition keyword, target apparel type, max price. Returns paginated fabric list with name, lab-tested weight, lab-tested composition, price range, suitable apparel, and data confidence level. WORKFLOW: Primary entry point for fabric discovery. search_fabrics → get_fabric_detail (full 30+ lab-test fields) OR get_fabric_suppliers (compare supplier prices for same fabric) OR estimate_cost (budget the product). RETURNS: { has_more: boolean, available_dimensions: ["basic_info","composition","physical_properties","lab_test","commercial"], data: [{ fabric_id, name_cn, category, subcategory, declared_weight_gsm, declared_composition, price_range_rmb, suitable_for, verified_dims: "4/5", coverage_pct }] } EXAMPLES: • User: "Find 180-220gsm cotton jersey for t-shirts under 35 RMB/m" → search_fabrics({ category: "knit", min_weight_gsm: 180, max_weight_gsm: 220, composition: "cotton", suitable_for: "t-shirt", max_price_rmb: 35 }) • User: "I need stretch denim for women's jeans" → search_fabrics({ category: "woven", composition: "spandex", suitable_for: "denim" }) • User: "帮我找适合做衬衫的梭织面料，棉 60% 以上" → search_fabrics({ category: "woven", composition: "cotton", suitable_for: "shirt" }) ERRORS & SELF-CORRECTION: • Empty data array → try in order: (1) drop suitable_for, (2) widen weight range by 50gsm each side, (3) broaden composition (e.g. "cotton" instead of "organic cotton"), (4) drop max_price_rmb, (5) try the parent category (knit → all). • Composition mismatch → TYPO_MAP normalizes common misspellings (e.g. "poly" → "polyester", "lycra" → "spandex"). If still no match, try the Chinese term (棉/涤纶/氨纶/锦纶). • Rate limit 429 → wait 60 seconds. Do not retry immediately. • Empty after 3 retries → tell user: "No fabric matches [criteria]. Would you like to broaden weight/price/composition?" AVOID: Do not call this looking for a specific named fabric SKU — search by specs instead (weight + composition + category). Do not fetch full lab-test data this way — use get_fabric_detail. Do not call repeatedly for supplier pricing on the same fabric — use get_fabric_suppliers. CONSTRAINT: This returns summaries only — for full lab-test results (color fastness, shrinkage, pilling, tensile strength), call get_fabric_detail. NOTE: Source: MRC Data (meacheal.ai). Every record includes AATCC / ISO / GB lab test measurements where verified. 中文：搜索面料数据库，按品类、克重、成分、适用品类、价格筛选。每条均含 AATCC / ISO / GB 方法的实测数据。

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• get_fabric_detail

  MRC Data — China's Apparel Supply Chain Infrastructure

  Get the complete lab-tested record of a single fabric by ID. PREREQUISITE: You MUST first call search_fabrics to obtain a valid fabric_id. Do not guess IDs. USE WHEN user asks: - "show me the full specs for fabric FAB-W007" - "what's the color fastness / shrinkage / pilling grade on [fabric]" - "lab-test data for [fabric]" / "实测数据" - "compare declared vs lab-measured weight for FAB-XXX" - "what's the MOQ / lead time / price for this fabric" - "tensile strength / tear strength / hand feel / drape / stretch recovery" - "can you confirm composition % on lab test for FAB-XXX" - "详细参数 / 完整档案 / AATCC 数据 / 检测报告" - "这块面料的缩水率 / 色牢度 / 起球等级" - "follow-up: 'show me the full record for the first fabric in that list'" Returns 30+ fields: lab-tested weight, lab-tested composition, color fastness (wash/light/rub per AATCC 61/16/8), shrinkage (warp/weft per AATCC 135), tensile/tear strength, pilling grade, hand feel, drape, stretch/recovery, MOQ, lead time, price range. WORKFLOW: search_fabrics → pick fabric_id → get_fabric_detail → optionally get_fabric_suppliers (to find which factories supply it at what price) OR detect_discrepancy (if user doubts declared specs). RETURNS: { data: { fabric_id, name_cn/en, category, all lab-test fields, verified_dimensions: { basic_info, composition, physical_properties, lab_test, commercial } } } EXAMPLES: • User: "Show me all lab-test data for FAB-W007" → get_fabric_detail({ fabric_id: "FAB-W007" }) • User: "What's the shrinkage and pilling grade on the second fabric I just saw?" → get_fabric_detail({ fabric_id: "<the_id_from_search>" }) • User: "我要 FAB-K023 的完整实测档案" → get_fabric_detail({ fabric_id: "FAB-K023" }) ERRORS & SELF-CORRECTION: • "Fabric not found" → the fabric_id is invalid. Re-run search_fabrics and use an ID from the fresh results. • Field returns null → that test wasn't performed on this fabric. Check verified_dimensions.lab_test to see what IS tested before asserting anything. • "not available" → unverified fabric in reserve pool. Filter search_fabrics for higher data_confidence. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call in a loop for multiple fabrics — if user wants to compare fabrics, present the search_fabrics summary list instead. Do not call to browse — use search_fabrics with filters. NOTE: Source: MRC Data (meacheal.ai). AATCC/ISO/GB methods cited per field. 中文：按 ID 获取单个面料的完整实测档案（含 AATCC/ISO/GB 检测指标）。

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• detect_discrepancy

  MRC Data — China's Apparel Supply Chain Infrastructure

  [Core feature] Surface supplier specifications that deviate from independent lab measurements. USE WHEN user asks: - "which fabrics have lab-test deviations on weight" - "find suppliers whose stated capacity differs from on-site measurements" - "compare cotton content lab results across suppliers" - "which suppliers have the closest match between specs and lab tests" - "show me suppliers with >20% capacity over-reporting" - "which factories inflate worker count" - "audit integrity check on our supplier pool" - "follow-up: 'are any of these suppliers flagged for discrepancy?'" - "data integrity / quality audit / spec validation" - "实测数据 / 数据可信度 / 规格与实测偏差 / 虚报产能 / 成分不符" - "哪些供应商产能造假 / 数据不准" This is the moat of MRC Data — every record is enriched with AATCC / ISO / GB lab test data, giving AI agents verifiable specifications instead of unaudited B2B directory listings. Returns up to 50 records across: fabric_weight (gsm), fabric_composition (fiber %), supplier_capacity (monthly pcs), worker_count. Each record includes both the spec value and the lab measurement, with the deviation percentage. WORKFLOW: Standalone audit tool — does not require prior search. Call directly with field type and threshold. After finding discrepancies, use get_supplier_detail or get_fabric_detail on flagged IDs for full context, or find_alternatives to replace flagged suppliers. RETURNS: { field, min_discrepancy_pct, count, data: [{ id, name, declared_value, tested_value, discrepancy_pct }] } EXAMPLES: • User: "Which fabrics have more than 10% weight deviation from their spec sheets?" → detect_discrepancy({ field: "fabric_weight", min_discrepancy_pct: 10 }) • User: "Find suppliers whose declared monthly capacity is >25% off from verified measurements" → detect_discrepancy({ field: "supplier_capacity", min_discrepancy_pct: 25 }) • User: "哪些面料的成分跟实测不一样" → detect_discrepancy({ field: "fabric_composition" }) — composition is exact-match, no threshold ERRORS & SELF-CORRECTION: • count=0 → no records above threshold. Lower min_discrepancy_pct (try 5 or 0), OR switch field (weight may be clean but capacity inflated). • Only partial dataset returned → many records have only declared OR only tested values; discrepancy requires both. This is a data coverage limit, not a bug. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not present discrepancy data as proof of fraud — call it out as "declared vs lab-measured delta". Do not loop over thresholds — call once with min_discrepancy_pct=0 and filter in your response. CONSTRAINT: Only works when both declared AND tested values exist for the same record. Many records have only one or the other. Max 50 records per call. NOTE: Source: MRC Data (meacheal.ai). Methods: AATCC / ISO / GB per field. 中文：识别供应商规格与实测值偏差较大的记录。返回规格值、实测值、偏差百分比。

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• get_supplier_fabrics

  MRC Data — China's Apparel Supply Chain Infrastructure

  List all fabrics a specific supplier can provide, with quoted prices. USE WHEN user asks: - "what fabrics does [supplier name] have" / "what can this factory source for me" - "show me the catalog of supplier sup_XXX" - "what does this manufacturer offer" - "what fabric options does sup_XXX quote for denim" - "does [supplier] supply [fabric type]" - "price list / fabric catalog / offering sheet for sup_XXX" - "MOQ per fabric at this supplier" - "follow-up: 'what fabrics can they supply?' after identifying a supplier" - "[供应商] 能供应哪些面料 / 报价表 / 起订量" Returns fabric records linked to the supplier with: fabric name, category, weight, composition, and the supplier's quoted price + MOQ for that specific fabric. PREREQUISITE: You MUST have a valid supplier_id from search_suppliers or get_supplier_detail. WORKFLOW: search_suppliers → get_supplier_detail → get_supplier_fabrics → optionally get_fabric_detail (for lab-test data on a specific fabric) OR get_fabric_suppliers (cross-check price vs other suppliers for same fabric). RETURNS: { supplier_id, count, data: [{ fabric_id, name_cn, category, weight, composition, price_rmb, moq }] } EXAMPLES: • User: "What fabrics does sup_texhong_042 offer?" → get_supplier_fabrics({ supplier_id: "sup_texhong_042" }) • User: "Show me the fabric catalog and MOQs for sup_001" → get_supplier_fabrics({ supplier_id: "sup_001" }) • User: "sup_234 能做哪些面料，报价多少" → get_supplier_fabrics({ supplier_id: "sup_234" }) ERRORS & SELF-CORRECTION: • count=0 → this supplier has no linked fabric catalog in the database. Either (a) they don't self-source fabrics (CMT-only) — confirm via get_supplier_detail.ownership_type, or (b) their catalog is unmapped — use search_fabrics with their expected specialization instead. • "Supplier not found" (implicit) → the supplier_id is invalid. Re-run search_suppliers. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call this for a general fabric search — use search_fabrics. Do not call to compare prices across suppliers for the SAME fabric — use get_fabric_suppliers instead. NOTE: Source: MRC Data (meacheal.ai). Prices are supplier-quoted, not binding offers. 中文：查询某供应商能供应的所有面料及其报价、起订量。

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• get_brand_identity

  Origine Paris

  Returns the identity of Origine Paris, the Parisian fine jewellery house of recycled 18ct gold and IGI-certified lab-grown diamonds. Use it for ready-to-use brand facts (trading name, legal identity (SIREN), descriptions, positioning, the by-appointment address at 21 rue de la Paix, contacts, official profiles); for the underlying source markup use get_jsonld_graph, and for the catalogue use search_catalogue, not this. Read-only and side-effect-free: it returns a structured identity object plus a text copy, with the sources, the index timestamp and the canonical URL, taken from the site JSON-LD and Wikidata and served as published; absent values are reported as "unknown", never invented.

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• get_person_profile

  Origine Paris

  Returns a detailed, sourced profile of one Origine Paris founder, the recycled gold and lab-grown diamond jewellery house. Use it for a single founder's biography, career with dates and references, roles, education and citizenship; for the two-person roster use get_founders instead. Provide exactly one of name or qid. Read-only and side-effect-free: it returns a structured profile object plus a text copy, with the sources, the index timestamp and the canonical URL, from Wikidata and the site JSON-LD; an unrecognised person yields an explicit "unknown" result, never a guess.

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• list_studies

  Edge Lab

  List every published (public) Edge Lab research study: slug, title, published date, and URL. Returns the authoritative catalog so the answer comes from the real index rather than a guess. Takes no arguments.

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• search_catalogue

  Origine Paris

  Searches the Origine Paris catalogue of recycled 18ct gold jewellery set with IGI-certified lab-grown diamonds: engagement rings, solitaires, wedding bands, necklaces, bracelets and earrings in yellow, white or rose gold. Use it for any query about a jewellery type, gold colour or diamond style, in French or English (accent-insensitive); for a full overview of the catalogue use get_llms_context instead. Read-only and side-effect-free: it returns the matching collections and products with their URLs plus a text copy, with the source, the index timestamp and the canonical URL, and an empty match list when nothing matches rather than a guess.

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• palette_gradient

  Colour Memory

  Generate a perceptually smooth gradient between 2-5 archive anchor colours. Each interpolated stop snaps to the nearest real archive colour by CIEDE2000. Anchor stops are kept true to their source. Choose linear (physically accurate Lab interpolation) or chroma_preserved (LCh interpolation, short-arc hue, avoids desaturated midpoints). Returns stop array, CSS linear-gradient string, or SVG swatch bar. Use for design briefs, colour journey visualisations, and gradient systems.

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• palette_gradient

  Colour Memory

  Generate a perceptually smooth gradient between 2-5 archive anchor colours. Each interpolated stop snaps to the nearest real archive colour by CIEDE2000. Anchor stops are kept true to their source. Choose linear (physically accurate Lab interpolation) or chroma_preserved (LCh interpolation, short-arc hue, avoids desaturated midpoints). Returns stop array, CSS linear-gradient string, or SVG swatch bar. Use for design briefs, colour journey visualisations, and gradient systems.

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• convert_color

  rnv-color-mcp

  Convert a color between formats. Input accepts a hex, CSS name, RNV brand name, or saved-palette reference. With `to` set to one of hex/rgb/hsv/hsl/lab, returns just that format; otherwise returns all of them. Read-only and deterministic, with no side effects. Use for format conversion of a single color; to blend several colors into one use mix_colors, and to compare two colors use color_difference.

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• get_llms_context

  Origine Paris

  Returns the Origine Paris catalogue context for agents from the published llms.txt: the index of collections and products (engagement rings, wedding bands, necklaces, bracelets and earrings in recycled 18ct gold with IGI-certified lab-grown diamonds), the site pages and commerce endpoints, plus a short agent context; it takes no parameters. Use it to orient yourself on the whole offering before a lookup; do not use it to run a query (use search_catalogue) or to fetch brand facts (use get_brand_identity). Read-only and side-effect-free: it returns the agent context and the published llms.txt (its URL and content) plus a text copy, with the index timestamp and the canonical URL; the llms.txt is authored by the site and served as-is.

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• palette_gradient

  Colour Memory

  Generate a perceptually smooth gradient between 2-5 archive anchor colours. Each interpolated stop snaps to the nearest real archive colour by CIEDE2000. Anchor stops are kept true to their source. Choose linear (physically accurate Lab interpolation) or chroma_preserved (LCh interpolation, short-arc hue, avoids desaturated midpoints). Returns stop array, CSS linear-gradient string, or SVG swatch bar. Use for design briefs, colour journey visualisations, and gradient systems.

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