"Bambu Lab" matching MCP tools:

• place_lightnessA

  rnv-color-mcpA

  Hold a color's hue and chroma and set its lightness, returning one result per requested L*. color accepts a hex, CSS name, RNV brand name, or saved-palette reference; lightness is a list of L* values in 0-100. This is the operation behind a LIGHT/DARK PAIR: one hue at two lightnesses, with a and b held exactly, which is how a color that works on a dark ground gets a partner that works on a light one. Use it when you need the same color at a different lightness; use mix_colors when you need a different color. Returns the source color's LAB, and for each placement the hex, the achieved LAB, and the quantization error per axis -- 8-bit hex cannot store a and b to the precision LAB expresses, so two placements of one hue differ by a few hundredths on both axes however exactly the input held them. That is the storage format, not the operation, and it is reported rather than hidden. Read-only and deterministic. Refuses rather than clamps: not every (L*, a, b) exists in sRGB, and a lightness too far from a chromatic color's range is rejected with the reason instead of being silently moved to the nearest color that fits.

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• place_lightnessA

  rnv-color-mcpA

  Hold a color's hue and chroma and set its lightness, returning one result per requested L*. color accepts a hex, CSS name, RNV brand name, or saved-palette reference; lightness is a list of L* values in 0-100. This is the operation behind a LIGHT/DARK PAIR: one hue at two lightnesses, with a and b held exactly, which is how a color that works on a dark ground gets a partner that works on a light one. Use it when you need the same color at a different lightness; use mix_colors when you need a different color. Returns the source color's LAB, and for each placement the hex, the achieved LAB, and the quantization error per axis -- 8-bit hex cannot store a and b to the precision LAB expresses, so two placements of one hue differ by a few hundredths on both axes however exactly the input held them. That is the storage format, not the operation, and it is reported rather than hidden. Read-only and deterministic. Refuses rather than clamps: not every (L*, a, b) exists in sRGB, and a lightness too far from a chromatic color's range is rejected with the reason instead of being silently moved to the nearest color that fits.

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• mix_colorsA

  rnv-color-mcpA

  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. Reach for paint when BLENDING brand colors into a new one, and lab when SAMPLING between them: lab averages chroma toward the centroid of its ingredients, which is right for finding a midpoint and wrong for making a new color. RNV's #00b0a0 was blended in paint; the same ingredients at the same weights in lab give #9cc1a5, 15.94 away and far closer to the brand gold it exists to be distinguishable from. paint works per RGB channel, so an ingredient with an empty channel (pure digital primaries such as #0000ff or #ffff00) dominates that channel: yellow + css:blue comes out black in paint, where ryb gives green. For pigment-like results use pigment-like colors, or ryb for idealized primaries. Brand names win over CSS names on collision: 'blue' is RNV blue, css:blue is #0000ff. 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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• mix_colorsA

  rnv-color-mcpA

  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. Reach for paint when BLENDING brand colors into a new one, and lab when SAMPLING between them: lab averages chroma toward the centroid of its ingredients, which is right for finding a midpoint and wrong for making a new color. RNV's #00b0a0 was blended in paint; the same ingredients at the same weights in lab give #9cc1a5, 15.94 away and far closer to the brand gold it exists to be distinguishable from. paint works per RGB channel, so an ingredient with an empty channel (pure digital primaries such as #0000ff or #ffff00) dominates that channel: yellow + css:blue comes out black in paint, where ryb gives green. For pigment-like results use pigment-like colors, or ryb for idealized primaries. Brand names win over CSS names on collision: 'blue' is RNV blue, css:blue is #0000ff. 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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• log_lab_resultsA

  Wellness ProjectA

  Log one or more blood test or biomarker results. use: requested logging/import of lab values or a concrete result to record. Review/interpretation alone: no write. GLUCOSE ROUTING: use this tool for glucose only when it is an actual lab/blood-draw result or part of a reported lab panel. Finger-stick, CGM, home meter, wearable, Apple Health, or Health Connect glucose — including a manual correction to daily glucose — belongs in log_wearable as blood_glucose_mg_dl, not here. REQUIRED WORKFLOW: 1) call list_lab_markers for canonical names and LOINC codes. 2) for each marker the user provides, find the best match and use its canonical marker_name and loinc_code. 3) if no match exists, use the name as stated and omit loinc_code. If the user says they have lab results but hasn't shared them, prompt: "You can paste the text from your lab report PDF, or upload a photo of the results page — I'll parse all the values at once." collection_date: report or explicit user context; missing: ask, never substitute report_date or today. infer: panel_name from matched marker or context. extract: flag (H/L/HH/LL/A), ref_range_low/high and lab_name only when reported. FASTING: fasting_status is only 'fasting' or 'non_fasting' when the user explicitly states it ("I fasted for this", "hadn't eaten"). Never infer it from time of day, a meal mention in notes, or the draw being in the morning — omit the field (leaves it unknown) whenever it wasn't stated. report_date (when the lab reported results, if given separately from the collection date) and draw_id (only when the user is adding a marker to a draw already logged in this conversation) are also optional, omit otherwise. Submit all markers from a single lab visit in one call.

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• mediora__explain_panelA

  mediora-mcpA

  Return the markers that make up a lab panel by slug — each resolved to its Mediora marker slug, name and one-line summary — plus the panel's search aliases (CBC/FBC, CMP, LFT, TFT, renal panel, …). Answers "what's included in a CBC / lipid panel / CMP". Follow each marker into mediora__explain_marker for full detail.

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• get_metrc_market_landscapeA

  FindWeedNYA

  Statewide New York cannabis market aggregates, crawled from Metrc’s public Cannabis Market Landscape dashboard — the seed-to-sale system every licensee reports into. Use it for market-size and trend questions (how much does NY sell a month, which regions and product categories, how many licenses exist and how fast are they being issued, what share of lab tests pass). Returns a `summary` of the four headline numbers plus a `metrics` array: monthly retail sales, cumulative sales, units sold, transaction count, basket size, average price per unit, lab test volume and pass rate, retail sales by region and by product category, active licenses by type and by region, monthly new licenses and cumulative license growth. Narrow it with `section` or `metric`; `metricsAvailable` always lists everything in the snapshot. This is dashboard-level aggregate data, not transaction-level Metrc records, and license counts may differ from NY OCM totals. For dispensary-by-dispensary counts use get_market_stats instead.

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• get_metrc_market_landscapeA

  FindWeedNYA

  Statewide New York cannabis market aggregates, crawled from Metrc’s public Cannabis Market Landscape dashboard — the seed-to-sale system every licensee reports into. Use it for market-size and trend questions (how much does NY sell a month, which regions and product categories, how many licenses exist and how fast are they being issued, what share of lab tests pass). Returns a `summary` of the four headline numbers plus a `metrics` array: monthly retail sales, cumulative sales, units sold, transaction count, basket size, average price per unit, lab test volume and pass rate, retail sales by region and by product category, active licenses by type and by region, monthly new licenses and cumulative license growth. Narrow it with `section` or `metric`; `metricsAvailable` always lists everything in the snapshot. This is dashboard-level aggregate data, not transaction-level Metrc records, and license counts may differ from NY OCM totals. For dispensary-by-dispensary counts use get_market_stats instead.

  ConnectorNo auth

• send_to_printerA

  kernelcadA

  Use this when you need to upload a .gcode file (e.g. written by export with target: "model", format: "gcode") to a real network printer and, by default, start the print. protocol: 'octoprint' (POST /api/files/local with an X-Api-Key), 'moonraker' (Klipper's POST /server/files/upload), or 'bambu-lan' (Bambu Lab LAN-mode: FTPS implicit-TLS upload on port 990 as user 'bblp' with the printer's LAN access code, then an MQTT print-start command on port 8883 — requires access_code and, unless start_print is false, serial). bambu-lan uploads a .gcode.3mf print project (the printer prints 3MF projects, not bare G-code): the G-code goes in as Metadata/plate_1.gcode, inside the model 3MF from export format '3mf' when model_3mf_path is given (use options { arrange: 'plate', slicer: 'bambu' } so the printer shows the same named, coloured parts), else inside a minimal 3MF shell; the file name always ends in .3mf ('part.gcode' -> 'part.gcode.3mf'). Optional printer (a bundled profile id, the same ids as the export 3mf/gcode options.printer) is checked against protocol before anything is read or sent: an unknown id is refused with the list of valid ids, 'bambu-lan' needs a Bambu Lab profile and a Bambu Lab profile needs 'bambu-lan'. Pass { dry_run: true } to validate connectivity/authentication only, without uploading or starting a print. Never logs or echoes api_key/access_code.

  ConnectorNo auth

• colour_mixA

  Colour MemoryA

  Simulate perceptually modelled subtractive mixing of two colours in CIE Lab space (not RGB screen blending). Returns the resulting mixed hex value and its nearest archive match with cultural context. Uses CIE Lab subtractive model for perceptual accuracy. Example: mixing Prussian Blue and Yellow Ochre gives a muted green — the tool identifies which archive colour that green most closely matches.

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• get_page_performanceA

  rankparse-mcpA

  Google PageSpeed Insights report for a URL: Lighthouse performance/accessibility/SEO scores and Core Web Vitals (LCP, CLS, INP, FCP, TTFB), with lab and field (CrUX) data. Defaults to mobile; pass strategy=desktop for the desktop profile. Subject to a per-user daily cap (50/day) and a service-wide daily cap; successful responses are cached for 24h.

  ConnectorNo auth

• colour_mixA

  Colour MemoryA

  Simulate perceptually modelled subtractive mixing of two colours in CIE Lab space (not RGB screen blending). Returns the resulting mixed hex value and its nearest archive match with cultural context. Uses CIE Lab subtractive model for perceptual accuracy. Example: mixing Prussian Blue and Yellow Ochre gives a muted green — the tool identifies which archive colour that green most closely matches.

  ConnectorNo auth

• get_faqA

  CalmActivaA

  Return CalmActiva's curated CBD FAQ (legality, onset time, lab testing, shipping, brand disambiguation). Use for general CBD/brand questions before falling back to web search.

  ConnectorNo auth

• detect_discrepancyA

  MRC Data — China's Apparel Supply Chain InfrastructureA

  [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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• colour_mixA

  Colour MemoryA

  Simulate perceptually modelled subtractive mixing of two colours in CIE Lab space (not RGB screen blending). Returns the resulting mixed hex value and its nearest archive match with cultural context. Uses CIE Lab subtractive model for perceptual accuracy. Example: mixing Prussian Blue and Yellow Ochre gives a muted green — the tool identifies which archive colour that green most closely matches.

  ConnectorNo auth

• get_rewardsA

  agentcardA

  Show the user's tokenback: balance, lifetime earned, and recent activity. Tokenback pays tokens (1 token = 1¢ of credit value) on settled card spend. AI cards (create_card scope_preset: 'ai_labs') earn a boosted rate on AI-lab purchases, and companies can route a share of their earnings to their users as tokenback. Redeem with redeem_rewards.

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• get_biomarkersA

  Vitals VaultA

  Resolves known public biomarker slugs in request order for factual comparison and reports missing slugs without substitution. Private lab results are outside this tool’s data boundary.

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• quote_orderA

  TestWell Lab TestsA

  Price a set of tests/panels exactly as TestWell's checkout would: per-lab prices for the user's state (New York and New Jersey route to BioReference; Rhode Island is not served), the single $6 lab processing fee, the total, items that can't be ordered and why, and a prefilled cart URL. Use this before quoting any total to a user.

  ConnectorNo auth

• list_lab_markersA

  Wellness ProjectA

  Returns all LOINC-coded markers in the reference library: canonical name, LOINC code, panel, typical unit, and common aliases. Call this BEFORE log_lab_results to match user-provided marker names to canonical entries — same pattern as list_exercises for workouts. Prevents name drift and ensures trending works across lab visits.

  ConnectorOAuth

• compare_rcbA

  Trustbase Lab · Global Chemical Recycling IntelligenceA

  Purpose: quality benchmark - compare measured rCB sample parameters against a target native carbon black grade (e.g. N550) spec ranges; classify each parameter pass / light deviation / significant deviation. Guidelines: pass target_grade plus rcb_params (iodine_absorption, OAN, ash...); ideal for grading incoming rCB lots against a native anchor before substitution decisions. Limits: needs measured values as input - no lab data on file; thresholds follow the site's anchored-benchmark methodology, not customer specs. Ex: 'compare rCB sample vs N550'.

  ConnectorNo auth

• quote_ad_proof_packA

  Clip Studio MCPA

  Quote an Ad Lab Proof pack. Does not generate. Default 6 slides at 4:5: hook, in-the-life stills for the user’s niche, and a soft CTA. Pass hasScreenshot true when a product screenshot will be composited on the last slide.

  ConnectorOAuth