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594,087 tools. Updated 2026-09-20 21:39

"A server for finding laboratory equipment dimensions and specifications" matching MCP tools:

  • List all API specifications in the active project. Set scope to 'org' to list the published APIs across every project in the organization instead — each entry carries the projectId and specId to pass to set_context. Use this to browse specs or find a spec id; for one spec by id use get_spec. Requires project context for scope 'project'.
    ConnectorAPI key
  • Look up road-freight vehicle and trailer specifications — 17 types: EU articulated trailers (standard/mega curtainsider, box, reefer, double-deck, flatbed, low-loader), US 53ft/48ft dry vans, rigid trucks (7.5-26 t) and vans (Luton, Transit, Sprinter). Each record carries internal dimensions, payload and gross weights, euro/UK pallet capacity, axle configuration and features. Provide slug (e.g. "standard-curtainsider") for one record; omit it to list all 17; category (articulated | rigid | van) and region (EU | US) filter the list. Behavior: read-only; an unknown slug errors with the valid list; per-record provenance (sources, audited_at, decision_rationale) is included. 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: the vehicle record (or filtered list) under result, plus confidence, _source and citation (the FreightUtils v1 response envelope). Limitations: typical specs, provenance pending independent verification (the envelope's provenance_status says so) — real equipment varies by operator and build; legal payload is set by the vehicle's plated weights. Related: ldm_calculator (whether a pallet load fits), pallet_fitting_calculator, consignment_calculator.
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  • Discover sheet names and used dimensions before reading or editing a WorkPaper. Returns metadata only; use read_range or read_cell for values.
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  • Get full specifications, equipment, all images, and pricing per term for a specific vehicle. Use a vehicle_id from search_vehicles results. IMPORTANT: Always show `detail_url` as a clickable link — it points to the FINN configurator where the user picks term and km. To produce a direct checkout link for a specific term + km combination (and optionally a one-time Fahrzeugbereitstellung), call `get_subscription_pricing` and use the `checkout_url` it returns. Never construct checkout URLs yourself. The `vehicle_id` field is an internal API identifier — never display it to users.
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  • No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.
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  • Set the multi-dimension analysis (form.report.dimensionAnalysis) of a form, replacing the dimension list without touching overallAnalysis (title / radar settings you omit are kept). Dimension codes are stable: pass dimensions[].code to keep or set one, or omit it and a dimension with the same name keeps its existing code. In the knowledge_quiz scene each dimension needs fieldCodes (question codes); in the scored_quiz scene a formula is optional — dimensions that questions score into via choices[i].dimensionScores sum those automatically, so only give a formula to dimensions no question scores directly. A dimension still referenced by a question's dimensionScores or by report.formula (the overall formula) cannot be removed. Pass an empty dimensions array to clear the multi-dimension analysis. Call get_form first to read the question and dimension codes. Not supported for random_knowledge_quiz forms.
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    Destructive
    API key

Matching MCP Servers

  • F
    license
    Not graded
    quality
    D
    maintenance
    An AI agent system that monitors manufacturing equipment health using the Model Context Protocol (MCP). Enables answering natural language questions about equipment status, maintenance, and anomalies through MCP tools.
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  • A
    license
    B
    quality
    B
    maintenance
    An MCP server for controlling lab instruments (oscilloscopes, signal generators, etc.) via standardized interfaces like USBTMC, RS-232, and LAN.
    100
    MIT

Matching MCP Connectors

  • Permit-verified ADU rentals, pre-approved plans and cited ADU rules for LA, San Diego, SF and NYC.

  • AI agents hire a human to observe, log or film on site. Typed results, feasibility before payment.

  • Set the multi-dimension analysis (form.report.dimensionAnalysis) of a form, replacing the dimension list without touching overallAnalysis (title / radar settings you omit are kept). Dimension codes are stable: pass dimensions[].code to keep or set one, or omit it and a dimension with the same name keeps its existing code. In the knowledge_quiz scene each dimension needs fieldCodes (question codes); in the scored_quiz scene a formula is optional — dimensions that questions score into via choices[i].dimensionScores sum those automatically, so only give a formula to dimensions no question scores directly. A dimension still referenced by a question's dimensionScores or by report.formula (the overall formula) cannot be removed. Pass an empty dimensions array to clear the multi-dimension analysis. Call get_form first to read the question and dimension codes. Not supported for random_knowledge_quiz forms.
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    Destructive
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  • Use this when exact dates or equipment fit matter, for questions like 'is X available', 'find a site for the long weekend', or 'which parks have space for a 32 ft RV'. It reads observed campsite availability across Canadian park reservation systems (BC Parks today) from public reservation data. Filters the official sites cannot: exact equipment fit, electrical, waterfront, shade, pets, privacy — across every park at once. Returns only sites observed open for EVERY requested night, with an absolute Parks Open page URL to cite, a booking link into the official reservation flow (we never book for the user), and observed_at for freshness; verify availability on the official site. Not for: fees, rules, facilities (use parksopen_park_info), weather (parksopen_check_weather), closures (parksopen_check_alerts), or dates beyond the provider's booking window.
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  • Unified search across your entire Costory workspace — dimension values, events, alerts, dashboards (with their conditionsCel), dashboard templates, reports, virtual dimensions, and budgets. PRIMARY tool for discovering CEL field names: each dimensions result includes `dimension` (the exact CEL/groupBy name, e.g. cos_sub_account_id), `label`, and `topMatches`. Use type: ["dimensions"] to focus on dimensions only. An empty query (query: "") with type: ["dimensions"] returns every dimension with its top values — use this when you need the full field catalog before building filterCel. With a keyword, results are filtered to matching values (e.g. query: "prod" finds production values across dimensions). Use this when a user mentions a product, team, project, or service name and you need to discover where it appears in the cost data before querying. Returns matching dimension values, related events, alerts, dashboards, dashboardTemplates, reports, virtualDimensions, budgets. Virtual dimension hits include id, name, bqName (immutable query field — set at create, never changes), status, and description. Each dashboard result carries a "conditionsCel" string — the dashboard's CEL filter (empty when none) — so before calling update_dashboard you can decide whether to set "extendDashboardConditions: true" on your new widget. Budget results include id (parent budget id for URLs) and name/year; call get with the budget id to obtain the budgetVersionId needed for query. IMPORTANT: Use short, concise search terms — e.g. if the user says 'my kubernetes dashboard', just search for 'kubernetes', not the full phrase. Optional "type" array restricts results to specific entity buckets (dashboards, reports, alerts, budgets, dimensions, virtual_dimensions, events). FOLLOW-UP: After calling search, use get to fetch full details for dashboards, budgets, reports, virtual dimensions, and cost alerts by ID. For dimension values, use "query" to query data grouped by or filtered on the matched dimensions. When the user wants to add to a dashboard, use the id from the dashboards bucket as input to update_dashboard. EXAMPLES: • "List all CEL dimensions" → { query: "", type: ["dimensions"] } • "Find account-related dimensions" → { query: "account", type: ["dimensions"] } • "Show me kubernetes costs" → { query: "kubernetes" } • "Find the data team dashboard" → { query: "data team" }
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  • Get ISO shipping-container specifications, with optional load-fit maths. Covers 10 types: 20ft/40ft standard, 40ft and 45ft high-cube, 20ft/40ft reefer, 20ft/40ft open-top and 20ft/40ft flat-rack. Provide type as a slug (e.g. "20ft-standard", "40ft-high-cube") for one container's record; omit it to list all 10. Add item dimensions (item_length_cm/width_cm/height_cm, optional item_weight_kg and item_quantity) to also compute how many such items fit. Behavior: read-only reference data with per-record provenance (sources, audited_at, decision_rationale); an unknown type errors with the valid slug list. Fit calculations are geometric best-effort — they do not model load distribution, securing or mixed cargo. 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: the container record — internal/external/door dimensions (cm), capacity_cbm, tare_weight_kg, max_gross_kg, max_payload_kg and euro/GMA pallet counts — under result, plus confidence, _source and citation (the FreightUtils v1 response envelope). Limitations: manufacturer-typical specs, provenance pending independent verification (the envelope's provenance_status says so) — actual equipment varies by lessor and line; confirm against the carrier's equipment guide. Related: validate (checks a container NUMBER's ISO 6346 check digit — not specs), cbm_calculator / consignment_calculator (the cargo volume to fill it), uld_lookup (the air-freight equivalent).
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  • Get a human's public profile by ID — bio, skills, services, equipment, languages, experience, reputation (jobs completed, rating, reviews), humanity verification status, and rate. Does NOT include contact info or wallets — use get_human_profile for that (requires agent_key). The id can be found in search_humans results.
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  • Return static specifications for a single vessel, identified by exactly one of: MMSI (9 digits), IMO (7 digits), or Datalastic UUID. Includes physical dimensions (length, breadth, draught), tonnage and cargo capacity (gross tonnage, deadweight, TEU, liquid gas), speed characteristics, year built, flag country, callsign and home port. This is reference data, NOT live position — use get_vessel for the current position, or find_vessels to search the registry by attributes.
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  • Search 873 exercises by name with muscle/equipment/level filters. Rows are lean (name, ext_id, equipment, level, muscles) — enough to pick one; get_exercise returns instructions and media. Paginates: pass next_cursor back as `cursor`.
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  • POST-ACTION Wallet Secret Guardian ($0.02). Scans for BIP-39 seed phrases (12 or 24 consecutive wordlist words), raw hex or WIF-format private keys, Ethereum/Bitcoin wallet addresses, and API keys/bearer tokens appearing near wallet/custody/signing terminology. Any finding results in NO_COMMIT — wallet secrets have no safe threshold, unlike other DCL evaluators. Returns a `sanitized_output` with all matches redacted (null if nothing was found) and a masked `redacted_sample` per finding — the real value is never returned or stored server-side.
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  • Server-side checklist for a DRAFT training program. Call it with the same WorkoutDocument you intend to import BEFORE presenting the draft to the user: it verifies day references resolve, every exercise is identifiable, rep ranges make sense, and — in 'coached' mode — that each exercise has a starting weight (or calibration note), matches the user's equipment and respects session length / weekly days. Pass program_mode='preserve' when the document is the user's OWN program brought in from a file. The same structural errors are refused, but a missing weight is accepted as a fact about their program, and an equipment or schedule mismatch comes back as a warning to show them rather than a violation to fix. Use the same mode you will pass to import_document. Returns {ok, mode, violations, warnings, unresolved, notes}. `unresolved` lists fields the file never stated — ask about those; never fill them in. Saves nothing, and creates nothing: reviewing somebody's file is not the start of a coaching relationship.
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  • Get remediation advice for a single finding as GitHub-flavored markdown. When AI Assist is enabled and within budget this is a suggestion written for this exact finding; otherwise it falls back to the static guidance-library text and says so in 'source'. Unlike the other reads this one can spend AI budget, which is why it is a separate tool. Use this for advice on one finding; for the whole library use list_security_guidance. Requires project context.
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  • Get the user's coaching profile: name, primary goal (e.g. build muscle / lose fat), experience level, target training days per week, equipment preference (e.g. full gym / home), height and weight (with units), timezone, and member-since date. Use this to CONTEXTUALIZE advice to the user's background and constraints — tailor volume, exercise selection, and progression to their experience level and available equipment. Excludes account/billing internals and contact info. For current-week training activity use get_training_snapshot; for subscription/connection status use check_connection.
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  • List PubMed-cited papers in HERB's reference index — the literature backing herb/ingredient-target and -disease associations. Each row is tagged evidence_tier human_clinical (its "Experiment type" includes "Clinical Experiment") or laboratory (cell/animal studies only). Filter by drug type or experiment type, or leave both blank to page through all ~2,000 references.
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  • Retract support for a finding you authored, with a reason. Original content remains visible and labeled withdrawn. Identical retries are safe; this does not claim the finding is disproven.
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  • Semantic search across all extracted datasheets. Finds components matching natural language queries about specifications, features, or capabilities. Best for broad spec-based discovery across all parts (e.g. 'low-noise LDO with PSRR above 70dB'). Only searches datasheets that have been previously extracted — not all parts that exist. For finding specific parts by number, use search_parts instead.
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  • Compare mapped human-evidence strength and limitations for two to five supplements for the same goal. This is an evidence comparison, not a product ranking or purchase recommendation, and contains no affiliate links. Use only for public, non-personal evidence questions. Do not call this tool for requests involving personal or sensitive health information, including medical records, medication lists, diagnoses, symptoms, laboratory results, or treatment planning. Tell the user not to submit that information and direct them to a qualified healthcare professional.
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