"Prop Amp (Proportional Amplifier) Information" matching MCP tools:

• scan_propsA

  flash-props-apiA

  Flatten every active player prop across all of today's games for a sport into a single list. Read-only. No side effects. Requires an API key; rate-limited and row-capped per your tier (Free 25 rows, Builder 100, Pro 3,000, Enterprise 5,000). Returns: { sport, stat, count, rows: Array<{ player, stat, line, overOdds, underOdds, bookCount, gameState?, flashProjection?, eventId, sport, homeTeam, awayTeam, startTime, source, fetchedAt }>, snapshotId, snapshotConsistency }. Each row is a player prop merged with its event context; use homeTeam/awayTeam for matchup context. overOdds/underOdds are American-format integers; null when odds unavailable. Use scan_props when you need a broad cross-game market view. Returns count=0 with an empty rows array (not an error) when no props are posted for the day yet. When not to use: use get_game_props when you already have an eventId; use find_player_props for one player.

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• get_player_propsA

  Lumify Sports IntelligenceA

  Get player-prop lines and live progress for an NFL, NCAAF, NBA, NCAAB, NHL, MLB, or soccer event. Joins persisted player-prop mains to this-event player box counts and grades over/under/push (1:1 slugs, combo sums including rush+rec and pass+rush yards, weighted total bases, anytime TD, double-double/triple-double, hockey points). Sport × market catalog: https://lumify.ai/docs/player-props. GET /odds / get_odds stay on moneyline/spread/total. Returns available:false with no charge if no prop mains have been ingested. Other sports return HTTP 400.

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• generate_shot_background_imageA

  Squall StudioA

  Generate an empty background plate for one short shot. Both reference inputs steer what the plate itself looks like — layout, prop identity, materials and lighting — and are unrelated to upload_shot_continuity_reference, which guides clip generation instead. Use reference_image_asset_ids for images already in this project (find them with get_asset_library) and reference_images_base64 to send bytes you produced locally, for example a frame lifted from an earlier scene so a prop matches what is already on screen. Uploaded bytes are used for this one generation and are not kept as project assets. The location's own reference images are always included on top of both. Spends credits. Returns a job id — poll it with get_job.

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• op_amp_gainA

  calc.engineerA

  Calculate voltage gain and output for operational amplifier circuits in inverting, non-inverting, and differential configurations. For inverting: Av = -Rf/Ri with input impedance equal to Ri. For non-inverting: Av = 1 + Rf/Rg with very high input impedance. For differential: Av = Rf/Ri applied to (V1 - V2). Reports gain in linear and dB, output voltage when input is provided, input impedance, and phase inversion status. Ideal op-amp assumptions (infinite open-loop gain, zero input bias current). Chain from ohms_law for power budgeting or resistor_color_code for component selection.

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• update_locationA

  Squall StudioA

  Overwrite fields on one location. Read it first (get_project_locations or get_location), then send ONLY the fields you changed — omitted fields are left untouched. IMPORTANT: a location is usually shared by several scenes across episodes, so this edit changes every scene that uses it. Check where it is used first; if the change is meant for one scene only, it needs a NEW location rather than an edit to this one. Editing name, short_description, visual_prompt, user_prompt, visual_style, aspect_ratio or spatial_layout marks the location stale, because its existing generated image no longer matches the description — regenerate the image if you want them back in sync. Editing mood, location_type, recurring or appears_in_episodes does not affect the image and leaves the stale flag alone. spatial_layout is the set bible: the named zones of the set and the fixed zone and height of each prop. Scenes must draw their spatial_geometry zones from it instead of inventing labels, so correcting it here fixes prop placement for every scene at once. Keep descriptions consistent with the owning character's status and the project's tone. This writes immediately and cannot be undone.

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  Destructive

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• find_player_propsA

  flash-props-apiA

  Every active prop for one player across today's board for a sport; same rows as scan_props, filtered by name (exact normalized match preferred, case-insensitive contains match as a fallback; see matchType in the response) instead of stat. Use this when you know the player but not which game/event they're in.

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• market_analyzeA

  x402 Crypto Market StructureA

  Is macro with you or against you? Get the current regime (bull/bear/risk_on/risk_off/choppy), directional signal and confidence, and macro context (DXY, VIX, fear/greed) before entering a position. Data-only, no LLM latency. coverage disclosed per token. REST equivalent: POST /analyze/market (0.25 USDC). Args: token: Token symbol (BTC, ETH, SOL, XRP, ADA, DOGE, AVAX, LINK, BNB, ATOM, DOT, ARB, SUI, OP, LTC, AMP, ZEC) context: Optional historical context window ('7d' or '30d'). Adds percentile rankings.

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• betting_build_parlayA

  v12-dfsC

  Build Parlay Deterministic parlay analysis for BOTH leg shapes. Body: {legs:[...], ticket_odds?}. PROP legs {name, prop, threshold} keep the legacy correlation-aware EV. GAME-side legs (ML / run line / total / team total / F5, selected by the `market` field) — the slips users actually paste — are priced from the CURRENT de-vigged market at that exact market/ line (canonical team resolution), falling back to the market-anchored run model for totals; per-leg fair prob + edge vs the slip's price, combined payout / breakeven / fair prob / EV under a documented independence assumption. Legs sharing a game are flagged correlated=true and get a correlation_warning INSTEAD of a combined edge. ticket_odds (the slip's printed combined price) is verified vs the leg product — >2% off flags ticket_odds_mismatch (the slip was misread; do not trust the numbers). NEVER estimate a parlay in prose — this endpoint is the math. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json **422**: Validation Error Content-Type: application/json **Example Response:** ```json { "detail": [ { "loc": [], "msg": "Message", "type": "Error Type", "ctx": {} } ] } ```

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• value_lp_tokenA

  hogswap-mcpA

  Value a liquidity-provider position. Give the LP token's asset id (free, no key) and optionally `amount` in LP BASE units — what the wallet holds — for its USD value and the redeemable amount of each underlying. Also identifies the issuing pool/DEX (and STAMM tier). Per-unit figures are per WHOLE LP token. Values are a proportional-share redemption at analytics prices: no slippage, no exit fee, NOT a market quote — fields are null rather than guessed when supply or a price is missing, so check before reporting a number.

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• trace_xgr_value_flowA

  XGR MCP GatewayB

  Read-only native-XGR value-flow analysis starting from one transaction. Use model="possible" for conservative attribution ranges or model="proportional" for haircut attribution. Native XGR has no per-coin identity, so results are provenance models rather than proof that a specific coin moved. maxTransfers and maxHops accept a number or "all"; "all" is still bounded by Explorer server safety caps and reports truncation explicitly.

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• historical_colour_queryA

  Colour MemoryA

  Ask a question about how historical colour authorities actually reasoned, and get evidence with provenance rather than a summary. Covers seven validated source builds -- Jennings (paint recipes, 1902), Bradley (rotating-disc apparatus, 1895), Vanderpoel (quantified object analyses, 1902), Beaumont (woven colour relationships), Hay (harmonic proportional powers, 1838), Guichard (measured spatial extents, 1880) and Hokusai (subject-conditioned colour application, 1848). Each answer names its source, its locator and what that kind of evidence CANNOT support. Use it for questions like 'how do I paint a leaf', 'what did Bradley's disc proportions measure', 'what's the difference between making a colour and applying it', or to check a claim someone has attributed to one of these authors. Crucially, these sources' numbers are NOT interchangeable: a recipe part, a disc share, an object percentage, a proportional power and a measured extent answer different questions, and the response says so explicitly rather than averaging them.

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• historical_colour_queryA

  Colour MemoryA

  Ask a question about how historical colour authorities actually reasoned, and get evidence with provenance rather than a summary. Covers seven validated source builds -- Jennings (paint recipes, 1902), Bradley (rotating-disc apparatus, 1895), Vanderpoel (quantified object analyses, 1902), Beaumont (woven colour relationships), Hay (harmonic proportional powers, 1838), Guichard (measured spatial extents, 1880) and Hokusai (subject-conditioned colour application, 1848). Each answer names its source, its locator and what that kind of evidence CANNOT support. Use it for questions like 'how do I paint a leaf', 'what did Bradley's disc proportions measure', 'what's the difference between making a colour and applying it', or to check a claim someone has attributed to one of these authors. Crucially, these sources' numbers are NOT interchangeable: a recipe part, a disc share, an object percentage, a proportional power and a measured extent answer different questions, and the response says so explicitly rather than averaging them.

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• historical_colour_queryA

  Colour MemoryA

  Ask a question about how historical colour authorities actually reasoned, and get evidence with provenance rather than a summary. Covers seven validated source builds -- Jennings (paint recipes, 1902), Bradley (rotating-disc apparatus, 1895), Vanderpoel (quantified object analyses, 1902), Beaumont (woven colour relationships), Hay (harmonic proportional powers, 1838), Guichard (measured spatial extents, 1880) and Hokusai (subject-conditioned colour application, 1848). Each answer names its source, its locator and what that kind of evidence CANNOT support. Use it for questions like 'how do I paint a leaf', 'what did Bradley's disc proportions measure', 'what's the difference between making a colour and applying it', or to check a claim someone has attributed to one of these authors. Crucially, these sources' numbers are NOT interchangeable: a recipe part, a disc share, an object percentage, a proportional power and a measured extent answer different questions, and the response says so explicitly rather than averaging them.

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• propfirms_getA

  luxalgo-mcp-serverA

  One prop firm's full dossier by slug: general profile (platforms, markets, payments, Trustpilot, restricted countries), every challenge with its rules, live offers with promo codes and affiliate links, and the written overview (about, rules, payout policy, FAQ). Find slugs with propfirms_search. Uncaptured (null) fields are omitted; challenges reference applicable offers via offerIds into the firm-level offers list. For simulated pass odds on this firm's challenges (reference archetypes, same engine as luxalgo.com/prop-firms), use propfirms_pass_rates.

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• list_cost_tagsA

  PlutusA

  List the virtual cost-allocation tag_keys defined for this account (e.g. "team", "product"), each with the cost_entries grain it's locked to and how many rules map dimension values to a tag_value. Use a tag_key with query_costs (breakdown_by: "tag") to see spend broken down by it. redistribute_bucket, when non-null, names a bucket (often "Untagged") whose spend is dissolved into the other tag_values in proportion to their own attributed spend in the same period — so that bucket will not appear in a query_costs breakdown for this tag_key, and the other values include a proportional share of it. It reappears only in periods where there was no other spend to redistribute against.

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• gripforge_attachA

  GripForgeC

  Attach a prop (sword, shield, gun, staff/scythe…) onto a rigged character. Finds the hand bone across naming schemes, scales the prop to the character, seats the grip, closes the fist, and returns a bind + ready-to-paste Three.js / Unity / Godot snippets. Pass Library ids (character_id / prop_id) or https URLs. attach_id reuses an existing armed bind GLB as the character. prop_id_2 attaches a second held item (off-hand) onto the first result. The bind (+ armed GLB when export_glb) is saved in Library — not a second credit. To write files into an open repo, use the npm MCP package gripforge_library_pull.

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• gripforge_generateA

  GripForgeC

  CREATE any mesh asset and save it to Library — the canonical generation door. kind decides the pipeline: character/enemy/boss are auto-rigged (pass concept_item or file_url for image-to-3D; otherwise text-to-3D), weapon and prop are direct text-to-model (no rig, no concept step). The workspace Style DNA is applied to the prompt. If the look may already exist, call gripforge_style_kit FIRST. Costs 10 credits. Returns a persistent job_id immediately; poll gripforge_generation_read for progress and the Library/Studio result. Closing this call does not cancel it.

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• ups_runtimeA

  calc.engineerA

  Estimates UPS (Uninterruptible Power Supply) backup runtime from battery specifications and connected load. Takes VA rating, watt rating, load in watts, and battery configuration (count, voltage, amp-hours) to compute effective stored energy after efficiency losses and runtime in minutes and hours. Detects overload conditions when load exceeds the UPS watt rating. Calculates power factor from VA/W ratings. Ideal for server rack planning, homelab power budgeting, network closet UPS selection, and graceful shutdown timer configuration.

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• propfirms_list_simulatableA

  luxalgo-mcp-serverA

  List the prop firms in the live LuxAlgo directory together with every simulatable challenge (challengeId, display name, account size, currency, price, and its rule-semantics provenance). Call this first to discover the firmId + challengeId pairs accepted by propfirms_challenge_rules, propfirms_simulate, propfirms_optimal_risk, propfirms_compare and propfirms_simulate_trades. Challenges whose loss-rule semantics cannot be established are listed under notSimulatable instead of being guessed. The listing is data, not endorsement: firms are alphabetical - no recommendation or ranking is implied, and none should be presented. DATA SOURCE & PROVENANCE: firm data comes live from LuxAlgo's public, keyless prop-firm directory API - the data behind luxalgo.com/prop-firms (origin overridable via the LUXALGO_APP_ORIGIN env var). Rule semantics are used verbatim where the directory serves structured rule columns; where it serves only free text, semantics are inferred ONLY when one reasonable reading exists, and every inferred field is disclosed in `inferredFields` (provenance 'directory+inferred') - relay those to the user next to any numbers. Challenges whose loss rules cannot be established are refused as not simulatable rather than guessed. Firms change rules; each firm's own page is always authoritative. NOTE: this lists only the firms and challenges whose rules the engine can encode honestly. The full directory — every visible firm with platforms, prices, payout terms, and live offers/promo codes — is served by propfirms_search, propfirms_search_challenges, and propfirms_search_offers.

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• infer_aircraft_specsA

  WindsockA

  Extract aircraft specs — AFTT, SMOH (engine 1, and engine 2 for twins), prop time, year, and interior/exterior quality (1–10), plus avionics mentioned — from observable page content: visible text and/or image URLs (a listing's own photos, or data: URLs). Uses the vision/LLM "autopilot inference" behind on-site valuation pre-fill. Anchor with registration or make_model_id to pull make/model + year from the FAA registry; set impute=true to fill gaps with the imputation model. Returns specs, per-field sources, and a ready-to-POST report_input for create_valuation_report. Requires Windsock PRO or Enterprise.

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• create_google_callout_extensionA

  Metadata MCP ConnectorA

  Add a short non-clickable selling-point snippet (callout) that appears beneath a Google Ads ad — short trust-builder phrases like "Free Shipping", "24/7 Support", "Money-Back Guarantee", or "No Setup Fees". Callouts reinforce value props without taking up headline space. ALSO KNOWN AS: callout, callout extension, selling point, trust badge, value prop, value proposition, tagline, ad badge KEYWORDS: callout, selling point, trust signal, value prop, badge, free shipping, money back, guarantee, support, no fees, google ads, extension WHEN TO USE: - "Add a 'Free Shipping' callout to our Google Ads library" - "Create a callout for 24/7 support" - "Register a new value-prop tag for the holiday campaigns" - "I want a 'Money-Back Guarantee' badge to show under our ads" WHEN NOT TO USE: - Want a clickable shortcut to a landing page → use create_google_sitelink_extension - Want a list of named items (e.g. "Brands: Nest, Nexus") → use create_google_structured_snippet_extension - Same callout for Microsoft Ads / Bing → use create_microsoft_callout_extension - Anything for Facebook / LinkedIn / Reddit — search-channel-only INPUTS: - callout_text: visible snippet (1-25 chars). EXAMPLE: create_google_callout_extension(callout_text="Free Shipping")

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