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522,293 tools. Updated 2026-09-06 12:44
"Linear" matching MCP tools:
- Linear Regression: Linear RegressionConnectorNo auth
- Calculate loading metres (LDM) for European road freight — how much trailer length a pallet load occupies. 1 LDM = 1 linear metre of a 2.4m-wide trailer; a standard artic is 13.6 LDM. Provide a pallet preset OR custom length_mm + width_mm — omitting both errors with a usage hint. Behavior: deterministic; stackable=true with stack_height 2 or 3 divides the floor footprint accordingly; fits reports whether the load fits the chosen vehicle's LENGTH (give weight_kg to also see total_weight_kg against the vehicle's max payload); utilisation_percent is of the vehicle's length. Rate-limited (anonymous use: 25 requests/day per IP): a 429 error body carries retry_after_seconds and a Retry-After header — back off and retry, or call get_subscribe_link for higher limits. Returns: ldm, vehicle (name, length_m, max_payload_kg), utilisation_percent, pallet_spaces (used/available), total_weight_kg, fits and warnings under result, plus confidence, _source and citation (the FreightUtils v1 response envelope). Related: vehicle_lookup (the trailer specs behind the vehicle presets), pallet_fitting_calculator (boxes onto one pallet), consignment_calculator (mixed lines including LDM).ConnectorNo auth
- Get a product's full, LLM-verified design system so you can match its exact look. Use this for "design like <product>" (e.g. site="Linear", "Stripe", "Figma"). Returns (default): color_scheme; colors with named roles (background, text, primary, secondary, accent, link, button_bg, button_text); fonts + font_roles; type_scale; spacing; primary/secondary button; framework + personality. All hex normalized. Deep-decoded products additionally include measured button hover/focus states, a shadow elevation scale (card/overlay/subtle), motion durations + easings, the measured spacing scale, the brand's own CSS custom properties (css_vars), and Icon DNA (icons: style outline/filled/duotone/3d, grid, stroke_weight, corner) — all measured from the live page, not guessed. Match them exactly; pass the domain to generate_asset(style_from=...) to strike icons in this exact style. Your own private BYODS design systems (call list_my_design_systems) resolve first. format: leave empty for the raw token dict. Pass "all" to also get paste-ready DESIGN.md / Tailwind v4 / CSS variables / W3C tokens JSON, or a single format name ("tailwind", "css", "design_md", "tokens", "astryx") to get just that text. "astryx" returns a ready Meta-Astryx defineTheme TypeScript file (measured hover/press states + [light,dark] tuples baked in) — save it and run `npx astryx theme build` for production CSS.ConnectorNo auth
- Return a canonical definition for a primitive Eurorack / synthesis concept and its relations to other concepts in the corpus. Use this for VOCABULARY questions, not module questions — when the user is asking what a term means or how two terms relate, not which modules implement it. Typical shapes: - "Is four-quadrant mult the same as through-zero AM?" → lookup_concept("four-quadrant mult") - "What's the difference between a gate and a trigger?" → lookup_concept("gate") - "Modular signal level vs line level — when does it matter?" → lookup_concept("modular signal level") - "Are clock dividers just pulse counters?" → lookup_concept("clock divider") - "Are polyphonic patch cables TRRRRRS?" → lookup_concept("polyphonic cable") Lookup is case-insensitive across three axes, tried in order: the canonical id ("through-zero-fm"), the canonical label ("Through-Zero FM (TZFM)"), and any registered alias ("tzfm", "through zero fm"). Spaces and hyphens are matched literally; the lookup does NOT normalize whitespace beyond lowercasing. If the term doesn't match anything, the response includes up to 5 substring-matched suggestions. Args: - name (string, required, min length 2): the term to look up. Examples: "AM", "ring mod", "four-quadrant mult", "TZFM", "clock divider", "gate", "trigger". Returns: { "concept": { "id": "amplitude-modulation", "label": "Amplitude Modulation (AM)", "description": "A multiplication of two signals: the carrier...", "aliases": ["am", "amplitude modulation", "amplitude mod"], "related_concepts": [ { "related_concept_id": "ring-modulation", "related_concept_label": "Ring Modulation (RM)", "relation_kind": "commonly_confused_with", "note": "AM with a unipolar modulator preserves the carrier..." }, ... ], "source_id": null, "citation_url": "https://learningmodular.com/glossary/...", "citation_quote": "Amplitude modulation is when..." } | null, "_meta": { "query": "<the name argument verbatim>", "matched_via": "id" | "label" | "alias" | "none", "concept_suggestions": [ { "id": "...", "label": "...", "matched_via": "alias", "matched_text": "..." } ], "feedback_hint": "...?" } } Relation kinds: - "related_to" — see-also link (default; symmetric in spirit). - "subtype_of" — X is a specific case of Y (RM ⊂ AM, TZFM ⊂ linear FM). - "inverse_of" — X is the opposite of Y (clock-divider ↔ clock-multiplier). - "commonly_confused_with" — they're distinct, but people conflate them (gate vs trigger, AM vs RM, modular level vs line level). When to cite: every concept carries either source_id or citation_url + citation_quote. Surface the citation when the answer affects a decision (e.g. "the corpus cites learningmodular.com — TRS cables are physically the same connector whether carrying balanced mono or unbalanced stereo; only the destination determines the role"). When the result is null and concept_suggestions are provided, present 2–3 closest matches to the user. If none look right, the corpus genuinely doesn't carry that concept — call report_gap with kind="missing_field" and tool_name="lookup_concept" naming the term and its expected definition.ConnectorNo auth
- Paid tier only. Calling this without an authenticated CivilQuants account returns TIER_INSUFFICIENT — sign up at https://civilquants.com/pricing or use the free-tier alternative compute_manhole. Linear extra-over measurement of hard material encountered during drainage trench excavation. Discriminates between natural rock (CESMM4 E.6 / NRM2 5.6.1 / MMHW 500.6.1 / SMM7 R12.6.1) and artificial hard material — buried concrete / masonry / obstructions (CESMM4 E.7 / NRM2 5.6.2 / MMHW 500.6.2 / SMM7 R12.6.2). The platform's first dual-quantity WorkItem: carries both length_m and volume_m3 so CESMM4/NRM2 (m³) and MMHW/SMM7 (m) each render with their correct unit per the standards' rules. Eight variant presets cover both hard-material types × four depth bands. SMM7 R12 deems trench excavation (including hard material) included in the pipe-run rate — the SMM7 handler emits a zero-priceable annotated line for tender transparency (third use of the deemed-included extra-over annotation pattern). Closes the drainage_ancillaries L2 leaf at 4/4 members. Sibling assemblies: connection_to_existing (S32), ditch (S33), pipework_testing (S33). Example params: length_m=10 m (0.5–500), max_depth_m=1.5 m (0.3–10), trench_width_m=0.7 m (0.3–3). Example call: {"params": {"length_m": 10, "max_depth_m": 1.5, "trench_width_m": 0.7}, "standard": "MMHW"}. Omitted parameters use sensible engineering defaults. Pass deliverables=["xlsx","dxf","pdf"] (any subset) to also receive one-shot download URLs in the same call: Excel BoQ (both tiers, watermarked free) plus the dimensioned DXF (CAD) and PDF drawing sheets (paid tier).ConnectorNo auth
Matching MCP Servers
- AlicenseBqualityAmaintenanceA Model Context Protocol server that enables AI assistants to interact with Linear project management systems, allowing users to retrieve, create, and update issues, projects, and teams through natural language.1984,856146MIT
- AlicenseBqualityCmaintenanceEnables managing Linear issues, projects, and teams through Cline. Supports CRUD operations, bulk actions, and rich text descriptions.22288134MIT
Matching MCP Connectors
Search, read and create Linear issues, projects, teams and cycles.
Linear MCP — wraps the Linear GraphQL API (OAuth)
- Use this when you need the exact interest rate that grows a principal to a target amount over a set number of years. type="compound" (default) uses the closed-form nth-root formula for the given compounding frequency; type="simple" uses linear growth. Requires target greater than principal and all values positive. Returns the annual rate as a percent plus the interest earned and the growth multiple; compoundingPerYear is null for simple interest. Deterministic: same input, same output. Example: principal=1000, target=2000, years=10, compoundingPerYear=12 -> ratePercent=6.9515, growthMultiple=2. Prefer this over trial-and-error.ConnectorNo auth
- Forecast future periods with a linear trend and honest fit quality. PREMIUM (license). For quick planning, not statistical modeling. Typical input {"values": [100, 120, 138, 161], "periods_ahead": 3} returns {"trend_per_period": 20.2, "r_squared": 0.998, "forecast": [180.9, 201.1, 221.3], "caveat": "..."}. Use when a series is roughly linear and fit quality matters as much as the projection. Not for seasonal or cyclical data, and not for measuring growth already observed (growth_rates). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "need at least 4 historical values"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.ConnectorNo auth
- Forecast a DCPI market's near-term trajectory (next 1-8 quarters). Projects excess_power_score and constraint_score forward with confidence bands that WIDEN with horizon, from DC Hub's daily DCPI snapshot history — the only source that can, because it owns the time-series. Use to answer "is this market trending toward BUILD or AVOID?" or "will Dallas power stay tight over the next 6 months?". Params: market_slug (required, metro slug e.g. dallas, phoenix, northern-virginia — valid slugs come from rank_markets / get_market_dcpi_rank); horizon_quarters (optional 1-8, default 4; 2 = ~6 months out). Returns {market_slug, method, basis{history_points, history_span_days, slope_per_day, trend}, horizon_quarters, projection[{quarter_out, excess_power_score, excess_power_band, constraint_score, constraint_band}], caveat, snapshot_record}. HONEST: linear trend extrapolation, NOT a guarantee — bands widen with horizon and short history; needs >=3 daily snapshots or it declines. Do NOT use for a single point-in-time verdict (use get_market_dcpi_rank) or to rank many markets (use rank_markets).ConnectorNo auth
- 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. The result already carries the rendered palette and its PNG, PDF, ASE, JSON and CSS downloads -- show them to the customer. Never present the archive anchors a colour was derived from as the colours you are recommending. If you go on to choose a final palette OF YOUR OWN from this evidence, call palette_finalize once with those exact colours so the customer can see and download what you actually recommended.ConnectorNo auth
- "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.ConnectorNo auth
- "Tell me about X" / "research Acme" / "brief me on Tesla" / "what does Apple do" / "company profile for Microsoft" / "give me the rundown on NVDA" / "everything you know about $TICKER" — full cross-source profile of a US public company in ONE parallel call. ALWAYS PREFER over chaining single-pack SEC/XBRL/news lookups when the user asks for a holistic view. Fans out across SEC EDGAR, XBRL, USPTO patents, federal contracts (USAspending), FDA-licensed biologics (Purple Book), H-1B hiring (DOL LCA), news and GLEIF, and returns: cik + company_name (+ resolved_from/resolved_to when `value` was a name); recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC); patents (USPTO PatentsView API sunset May 2025 — soft-fails until reactivated); federal_contracts (USAspending awards where the company is the recipient); fda_products (FDA-licensed biologics — vaccines, cell/gene therapies — from the Purple Book; a company with only small-molecule/generic drugs will show none here, that is expected, not a failure); hiring (H-1B sponsorship volume + salary range from DOL LCA filings); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. `sources_used` / `sources_failed` say which of these actually returned data for THIS company — an empty section is a real "no data", not a bug. Pass a ticker ("AAPL"), zero-padded CIK ("0000320193"), OR a company name ("Moderna") — names now resolve via SEC EDGAR's company-name match; a private company (no CIK/ticker) returns resolved:false with an explicit `notes` line, not a bare failure. `type` accepts "company" or "ticker" interchangeably — both take the same `value` shapes above.ConnectorNo auth
- Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.ConnectorNo auth
- Realizable-vs-theoretical edge check against live CLOB order-book depth. REQUIRES one of `market` (single-market mode) or `event` (basket/partition mode). SINGLE-MARKET: pass a market slug/URL + side (buy_yes|sell_yes|buy_no|sell_no, default buy_yes) + size_usd (default 1000 — max spend on buys, target proceeds on sells); walks the ladder and returns top_of_book, vwap_fill_price, slippage_pp, shares_filled, max_fillable_usd, and a verdict (clean|degraded|cannot_fill). BASKET: pass an event slug/URL + side (sell_yes = capture overround by selling every leg, buy_yes = capture underround; default auto from partition sum) + size_usd interpreted as settlement notional S (shares per leg; each share pays $1); returns theoretical_sum vs realizable_sum (top-of-book vs VWAP across all legs), capture_ratio, profit_usd at executed size, per-leg fill detail, thin_legs[], max_clean_notional_usd, and forced_directional_risk naming the legs most likely to strand you unhedged. USE THIS before acting on any polymarket_arbitrage SELL/BUY-EVERY-LEG signal or any polymarket_edges trade above ~$500 — theoretical overround on thin books is not capturable, and partial basket fills convert an arb into an unhedged directional position (the dominant loss mode in real arb-bot P&L).ConnectorNo auth
- Paid tier only. Calling this without an authenticated CivilQuants account returns TIER_INSUFFICIENT — sign up at https://civilquants.com/pricing or use the free-tier alternative compute_attenuation_tank. Vegetated, geotextile-reinforced or rip-rap-lined linear drainage swale per CIRIA C753. Trapezoidal prismatic channel with three lining strategies covering the UK design palette from low-velocity amenity grass channels (1V:3H, 1-3% gradient) to high-velocity rip-rap-lined stretches. Optional check-dams (stone or concrete) for steeper sections. Renders cleanly across all four standards using existing earthworks / geosynthetics / concrete handlers — no PC items, all contractor-full supply route. Example params: bed_width=0.5 m (0.2–3), left_side_slope_h_per_v=3 (1.5–6), right_side_slope_h_per_v=3 (1.5–6). Example call: {"params": {"bed_width": 0.5, "left_side_slope_h_per_v": 3, "right_side_slope_h_per_v": 3}, "standard": "MMHW"}. Omitted parameters use sensible engineering defaults. Pass deliverables=["xlsx","dxf","pdf"] (any subset) to also receive one-shot download URLs in the same call: Excel BoQ (both tiers, watermarked free) plus the dimensioned DXF (CAD) and PDF drawing sheets (paid tier).ConnectorNo auth
- Retire an owned ticket from the working set, or restore one. Archiving is a different axis from status: the ticket keeps whatever status it had, so a done ticket stays done and a blocked one comes back still blocked — never use status 'cancelled' to mean 'archived'. An archived ticket disappears from ticket_list, the stats, the buckets, the attention queue, and outbound JIRA/Linear sync, but keeps its id and URL so citations stay valid, and it refuses edits until restored. Cascades to the active subtree; restore brings back exactly what was archived alongside it. Nothing is destroyed — this is not a delete, and no delete tool is exposed.ConnectorNo auth
- Read a token launch live from chain (free): terms, status, escrow balances, and a machine-readable liquidity release schedule. ``launch_id`` is the on-chain u64 launch identifier. Returns the raise window and progress, the per-wallet pledge cap (0 = uncapped), live escrow + launch-vault balances, and a ``release_schedule`` block (cliff-then-linear) an agent can plan future claim_ilo_tokens calls from without parsing prose. Pass ``caller_wallet`` to attach that wallet's own pledge summary too (the authoritative per-wallet view is get_my_pledge_status). Utility token fair launch: participating commits funds to a non-custodial escrow; it is not a purchase of an expectation of profit. Workflow: DISCOVER step -- read details, check the window and the per-wallet cap, then preview with pledge_to_ilo (plan mode) before committing anything.ConnectorNo auth
- Query this account's business-event timeline (GitHub releases/PRs, PagerDuty incidents, Jira issues, GitLab, Salesforce onboarding/churn, Stripe subscription created/canceled, Vercel production deploys, Linear issue creation, Sentry newly reported errors) — the same events overlaid on the Cost/Event Explorer charts. Always scope with start_date/end_date: there is no pagination and results are capped at 5000 rows (oldest-first), so an unscoped query over a long history may be silently truncated. Carries no cost figure. Mirrors GET /api/events.ConnectorNo auth
- Série histórica contínua (meses com e sem movimento) com saldo reconstruído, patrimônio e estatística elaborada (média/mediana/desvio/variação, tendência por regressão linear, médias móveis 3/6/12m, taxa de poupança). Suporta vida inteira (até 120 meses). Use from/to como YYYY-MM ou YYYY-MM-DD. Use esta ferramenta pro histórico mensal geral (saldo/patrimônio/receita/despesa); para série por categoria use category_history, para separar aporte de valorização em investimentos use wealth_evolution, e para um retrato único do momento atual (não série) use financial_snapshot.ConnectorOAuth
- Solves a linear or quadratic equation in one variable and returns every step: expanding parentheses, combining like terms, moving terms across the equals sign, and applying the quadratic formula with the discriminant stated. Reports identities and contradictions as such rather than as "no answer", gives roots as exact fractions with a decimal alongside, and labels complex roots explicitly instead of claiming no solution. Refuses rather than guesses on a missing or duplicated "=", a second variable, a function name, an unsupported exponent, or an inequality — every refusal says what to change. Covers only one-variable linear and quadratic equations: not systems, not inequalities, not degree three or higher. WHY DELEGATE THIS: Three places this algebra goes quietly wrong when reasoned about directly: the sign when distributing a negative across parentheses, which direction a term moves as it crosses the equals sign, and dropping one of the two ± roots of a quadratic or rounding a complex pair into a false "no solution". Exact fraction arithmetic gets all three right every time, and showing the work is the point — a student checking their own scratch paper needs the steps, not the answer. Owned by Equation Steps at https://equation-steps.gumballtools.com, which is also callable directly if you would rather not go through the aggregator.ConnectorNo auth
- Forecast a DCPI market's near-term trajectory (next 1-8 quarters). Projects excess_power_score and constraint_score forward with confidence bands that WIDEN with horizon, from DC Hub's daily DCPI snapshot history — the only source that can, because it owns the time-series. Use to answer "is this market trending toward BUILD or AVOID?" or "will Dallas power stay tight over the next 6 months?". Params: market_slug (required, metro slug e.g. dallas, phoenix, northern-virginia — valid slugs come from rank_markets / get_market_dcpi_rank); horizon_quarters (optional 1-8, default 4; 2 = ~6 months out). Returns {market_slug, method, basis{history_points, history_span_days, slope_per_day, trend}, horizon_quarters, projection[{quarter_out, excess_power_score, excess_power_band, constraint_score, constraint_band}], caveat, snapshot_record}. HONEST: linear trend extrapolation, NOT a guarantee — bands widen with horizon and short history; needs >=3 daily snapshots or it declines. Do NOT use for a single point-in-time verdict (use get_market_dcpi_rank) or to rank many markets (use rank_markets).ConnectorNo auth