Skip to main content
Glama
457,771 tools. Updated 2026-08-14 15:09

"Arm" matching MCP tools:

  • List filament spools with optional filters and sorting. Accounts often have hundreds of spools, so ALWAYS pair sort_by with a limit. Use sort_by=last_used + limit=10 for "most used / most popular spool" questions. Use sort_by=created + limit=N for recently added. Use sort_by=left for emptiest/fullest. Filters (material_type/brand/color) are case-insensitive substring matches. If the user names a specific spool by id or 4-character short id (e.g. "T2SO"), call get_filament instead — do NOT list and grep. Amount-remaining fields: report weight from leftGrams/totalGrams (grams) and percentLeft (%), NOT the raw total/left which are internal filament LENGTH in mm. density (g/cm³) is the value used for the gram conversion; densityIsEstimated=true means the spool has no material profile so a default density was assumed.
    Connector
  • Check whether molds fit together on a rotational-molding machine arm. Every answer comes from the deterministic RotoSpider geometric layout engine: rotation-envelope and dead-height checks, pairwise mold-to-mold clearance, offset-arm riser selection, and ring arrangements for 3+ identical molds. It never returns a physically invalid layout. Args: molds: List of mold objects. Use one explicit unit convention: Box/frame mold: {"length_mm": L, "width_mm": W, "height_mm": H}. Cylinder/tank mold: {"diameter_mm": D, "height_mm": H}. Exact L, slope, triangle, frustum, or complex mold: measured length_mm+width_mm+height_mm plus the complete geometry_asset_id+geometry_asset_revision returned by the geometry WebAPI or another trusted publisher. Decimal-inch aliases are length_in, width_in, height_in, and diameter_in. Each value is converted once to canonical micrometres; do not give both aliases for the same value. Optional per mold: "name", "weight_kg", "quantity" (default 1). machine: Public-sample straight-arm preset. Available models are listed in the tool description. Leave empty AND give no explicit geometry to scan all presets ("which machine can take these molds?"). arm_type: 'straight' (dual spiders) or 'offset' (single-spider offset/L arm). Empty = both. spider_diameter_mm: Custom machine - spider (mounting plate) diameter. Giving this plus envelope_diameter_mm switches to custom-machine mode instead of presets. envelope_diameter_mm: Custom machine - rotation envelope diameter (for offset arms: the vertical envelope diameter). dead_height_mm: Custom straight arm - unusable center height between the upper and lower spider surfaces. offset_spider_y_mm: Custom offset arm - spider Y offset from the spider center to the sphere center (required for custom offset). offset_horz_diameter_mm: Custom offset arm - horizontal usable envelope diameter after side trim (defaults to envelope). riser_heights_mm: Custom offset arm - available riser heights; the solver picks the best (or none). *_in: Decimal-inch aliases for the matching custom-arm and clearance *_mm arguments. max_load_weight_kg: Optional arm weight capacity; the solver loads molds only up to this total weight. clearance_target_mm: Target mold-to-mold clearance (default 300). clearance_min_mm: Minimum acceptable clearance (default 150). allow_overhang_within_envelope: Allow every mold shape to extend past the spider edge while its complete active shape remains inside the rotation envelope. Defaults to false. include_layout: Include request-relative mold placements. Use with response_api v1/v2/v3 to select the placement heading dialect. display_unit: 'mm' (default) or 'in'. Canonical result fields remain millimetres; 'in' adds a display projection rounded to 0.00001 in. response_api: Public placement dialect. Defaults to rotospider.layout-check.v1; request rotospider.layout-check.v2 for exact four-heading orient keys when layouts are included. Returns a summary sentence plus per-arm results: feasible, placed vs requested counts (per mold type when available), selected riser height, spider utilization, center-of-gravity offset, achieved clearance, and the engine's reason when molds do not fit.
    Connector
  • Assemble checkout-ready cart(s) in ONE call for a multi-product (and optionally multi-store) request. Creates a cart per store, adds all items, and sets the shipping address — then returns the cart(s) with delivery options to choose. Use this when the buyer lists several products at once (optionally across stores) and/or gives their address up front, instead of calling create_cart/add_to_cart/set_shipping_address separately. Does NOT select delivery, check out, or pay — the buyer picks delivery (select_shipping_option) and approves checkout/payment per store afterward. Out-of-stock items are reported; pass customer.email to auto-arm a back-in-stock alert for them.
    Connector
  • List MULTIPLE printers with optional filters. For details on a single known printer, call get_printer instead — do not list-then-filter. For farm-wide counts ("how many printers are doing X"), call get_farm_overview instead — do not paginate this. Use status=["online"] to only see reachable printers, status=["printing"] for ones actively printing, status=["was_printing_when_offline"] for printers that dropped mid-print, status=["idle"] for available printers ready to accept a job, status=["awaiting_bed_clear"] for printers whose last print finished but the bed has not been cleared yet (NOT print_pending, which means a queued staggered start).
    Connector
  • ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1455 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,529 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).
    Connector
  • "Is it true that…" / "fact check" / "verify the claim that…" / "did X really…" / "was Y actually…" / "confirm or refute" / "true or false" — natural-language claim verification against authoritative sources. Use whenever the agent needs to check whether something a user said is factually correct. Company-financial claims (revenue, net income, cash for public US companies) verify via the structured SEC EDGAR + XBRL fast path with exact percent-delta math; ANY OTHER factual claim (macro statistics, rates, prices, drug data, records) automatically falls through to the grounded pipeline — routed to the right live source, answered with verbatim evidence, then judged. Returns a verdict (confirmed / approximately_correct / refuted / inconclusive / unsupported / could_not_verify), the grounded or structured actual value with pipeworx:// citation, and reasoning. IMPORTANT for callers: could_not_verify means the check did not happen (our LLM or source failed) and carries verification_error{stage,detail} — it is NOT evidence for or against the claim, and must not be shown as one. unsupported means we looked and cover no source for it. Replaces 4–6 sequential calls (NL parsing → entity resolution → data lookup → comparison).
    Connector

Matching MCP Servers

Matching MCP Connectors

  • Global business entity verification, sanctions screening (OFAC/UN/EU/UK HMT), UBO mapping, and jurisdiction risk scoring for AI agents. Pay per call in crypto (USDT/USDC/BTC/ETH). Built by ARM Consultancy LLC, UAE.

  • Rotomolding mold-on-arm layout feasibility: which molds fit on a machine arm/spider, and how.

  • ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1455 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,529 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).
    Connector
  • NightWatch Knowledge Graph lookup for a COMPANY/entity (equities & RWA universe: Samsung 'samsung-electronics', SK Hynix 'sk-hynix', 'tsmc', 'nvidia', 'asml', 'arm', ...). Returns SOURCED data only — every row carries a citation URL (the KG refuses uncited data): (1) numeric fundamentals (revenue, net income, market cap, business segments, dividend, market-share rankings), (2) typed relations (supplies / competes / customer_of / licenses — e.g. Samsung supplies NVIDIA HBM, competes with TSMC in foundry), and (3) a live HyperLiquid price block when the entity is tradable. Use this BEFORE reasoning about a company's fundamentals, competitors, supply chain, or a hedge on its equity perp. Input accepts a slug or a plain company name (fuzzy-matched).
    Connector
  • Rent a dedicated mobile port for 24 hours on a real 4G/5G carrier IP (Orange, France and Guadeloupe, AS16028), up to 5 GB included. The entry ticket: qualify the exit against your own target before committing to a week or a month. You rent the line, not a slice of a shared pool — one physical SIM, one client, one address for the full day. Carrier, ASN and uptime are probed every 10 minutes and returned with the key; if no mobile exit is verified live, you are not charged. — $10.00/call, paid per request via x402 (USDC).
    Connector
  • Run up to 100 record writes in ONE call (contact/company/deal/activity) - the fast path for imports/migrations. operations: [{object, method:create|update|delete, data|patch, id?}]. Returns a per-op result array (partial success). Every op still counts against your quota (batch saves round-trips, not quota).
    Connector
  • One-shot summary of farm-wide printer state. Use this (NOT list_printers) when the user asks "how many printers are printing/idle/awaiting bed clear/etc." or "what is the state of the farm". Returns a total and {count, printers:[{id,name}]} for each bucket: online, offline, not_connected, operational (idle), printing, paused, awaiting_bed_clear (a print finished but the bed has not been cleared yet — printer is online + operational + still has a job; this is NOT print_pending), in_maintenance, print_pending (a queued staggered/scheduled start), requires_attention (has unresolved error notifications), ai_running, ai_detected_low, ai_detected_high. Counts overlap intentionally: a printer can be in "online" + "printing" + "ai_running" at once.
    Connector
  • ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1455 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,529 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).
    Connector
  • ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1455 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,529 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).
    Connector
  • "What's the ticker for…" / "find the CIK for…" / "what's the LEI for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" / "who owns X" / "is X a subsidiary of Y" — resolve a user-spoken NAME to the canonical/official identifiers other tools require as input. Use FIRST whenever you have a name but need an ID. SUPPORTED TYPES: "company" (cross-source identity spine: 10-digit CIK + ticker + company_name from SEC EDGAR, legal-entity LEI from GLEIF with parent/ultimate-parent/children ownership when the LEI resolves, and security FIGI from OpenFIGI when a ticker is implied; every identifier is labelled with the source that established it, and an identifier that could NOT be resolved is stated explicitly under `unresolved` rather than omitted — accepts ticker, CIK, or company name as input), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/concept/{rxcui} citation; accepts brand or generic name). LEI/FIGI enrichment degrades gracefully — if GLEIF or OpenFIGI is unavailable, the EDGAR identifiers still return. Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.
    Connector
  • Buy 5 GB of mobile proxy bandwidth on a real 4G/5G carrier IP address (Orange, France and Guadeloupe, AS16028), delivered as a proxy key valid for 30 days. Mobile addresses are shared by thousands of subscribers, making them the hardest class of IP to block without hitting legitimate users. Carrier, ASN and uptime verified live at purchase. Suited to agents running sustained collection against sites that already reject residential exits. — $30.00/call, paid per request via x402 (USDC).
    Connector
  • Arm an email watch on a site you already saved (FREE with a key) — DC Hub emails you when that site’s DCPI score, grid capacity, or nearby facilities move, so you don’t have to keep re-checking. On the free tier the alert is delivered to your human’s bound email (call bind_email first; notify_email is forced to that address). Pro can send to any address. The "monitor my shortlist for me" loop: call save_site first (it returns a saved_site_id), then set_site_alert on that id. Params: saved_site_id (required integer, from save_site or list_saved_sites), trigger_type ("dcpi_change" | "capacity_change" | "new_facility_nearby", default "dcpi_change"), threshold (number — the points/MW move that fires it, default 5), notify_email (required — the address the alert is sent to). Try: set_site_alert saved_site_id=12 trigger_type=dcpi_change threshold=5 notify_email=you@firm.com. Returns {ok, alert_id, message}. Do NOT use to watch a whole MARKET (use set_market_alert) or to save a new site (use save_site); this arms a monitor on ONE already-saved site.
    Connector
  • Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 5,529 across 1455 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.
    Connector
  • "What's the ticker for…" / "find the CIK for…" / "what's the LEI for…" / "what's the RxCUI for…" / "look up the ID for…" / "what is X's official identifier" / "who owns X" / "is X a subsidiary of Y" — resolve a user-spoken NAME to the canonical/official identifiers other tools require as input. Use FIRST whenever you have a name but need an ID. SUPPORTED TYPES: "company" (cross-source identity spine: 10-digit CIK + ticker + company_name from SEC EDGAR, legal-entity LEI from GLEIF with parent/ultimate-parent/children ownership when the LEI resolves, and security FIGI from OpenFIGI when a ticker is implied; every identifier is labelled with the source that established it, and an identifier that could NOT be resolved is stated explicitly under `unresolved` rather than omitted — accepts ticker, CIK, or company name as input), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/concept/{rxcui} citation; accepts brand or generic name). LEI/FIGI enrichment degrades gracefully — if GLEIF or OpenFIGI is unavailable, the EDGAR identifiers still return. Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.
    Connector
  • Fordert einen kostenlosen Telefon-Rückruf durch einen Claimondo-Berater an — der zweite Funnel-Arm neben claimondo_melde_schaden, für Kunden die lieber angerufen werden (oder wenn kein Slot passt / Daten fehlen). Legt einen Lead + Rückruf-Task in der Dispatch-Queue an; ein Berater meldet sich i. d. R. < 15 Min telefonisch. Erfrage Name + Telefonnummer + (optional) Schadenart/Anliegen/PLZ. Rufe dies NUR mit einwilligung_erteilt=true auf, NACHDEM der Nutzer der Datenverarbeitung + dem telefonischen Kontakt (Verarbeitung teils über einen KI-Dienst in den USA) ausdrücklich zugestimmt hat.
    Connector