"Construct 3" matching MCP tools:

• law_citations_format_oscola

  UK Business Tools - Ledgerhall

  USE THIS TOOL AFTER citations_resolve to produce the correctly formatted OSCOLA citation string. Pass the parsed fields returned by citations_resolve directly into this tool. Formats per OSCOLA 4th edition rules for each citation type. Refuses (status: upstream_validation) if confidence is 0.0 — TNA confirmed the document does not exist — or if a neutral citation has no resolved_url (ambiguous court code, e.g. bare EWHC without a division). In either case, do NOT manufacture a citation; surface the failure and ask the user for the source URL or better identifying details. DO NOT construct the input fields yourself. The structured input must come from citations_resolve — guessing fields is the primary citation-fabrication route and this tool is the guard against it. Authoritative OSCOLA formatting for UK legal citations (no network call).

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• research_niche

  KDP Niche Research

  Get detailed KDP niche intelligence for a specific keyword. Returns demand score, competition score, Amazon BSR range, estimated monthly revenue, review threshold, average book pricing, and data freshness for the given Kindle publishing niche. Pricing tiers (x402 USDC on Base network): - $0.03 per query for cached/pre-seeded keywords - $0.10 per query for live on-demand research (new keywords) Use the free `list_niches` tool first to see available keywords. Payment options: 1. Set the KDP_X_PAYMENT environment variable on the server for auto-pay. 2. Pass a valid x402 payment header via the x_payment argument. 3. If neither is set, the tool returns structured 402 payment instructions that an x402-capable agent can use to construct and retry payment. Args: keyword: The KDP niche keyword to research (e.g. "romance novels", "keto cookbook") x_payment: Optional base64-encoded x402 payment header. Takes precedence over the KDP_X_PAYMENT environment variable.

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• compute_swale

  civilquants

  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).

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• citations_format_oscola

  UK Legal Research

  USE THIS TOOL AFTER citations_resolve to produce the correctly formatted OSCOLA citation string. Pass the parsed fields returned by citations_resolve directly into this tool. Formats per OSCOLA 4th edition rules for each citation type. Refuses (status: upstream_validation) if confidence is 0.0 — TNA confirmed the document does not exist — or if a neutral citation has no resolved_url (ambiguous court code, e.g. bare EWHC without a division). In either case, do NOT manufacture a citation; surface the failure and ask the user for the source URL or better identifying details. DO NOT construct the input fields yourself. The structured input must come from citations_resolve — guessing fields is the primary citation-fabrication route and this tool is the guard against it. Authoritative OSCOLA formatting for UK legal citations (no network call).

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• list_deployments

  Control Plane

  A workload's deployments — its per-location rollout status. This is the PRIMARY readiness check after create_workload/update_workload: poll it (without `location`) until ready, then report the canonical endpoint as the public URL — never construct a URL by hand. Without `location`: every location with readiness, endpoints, and the canonical URL. With `location`: that single deployment in full detail — version chain, per-container readiness/restarts/messages, full JSON. For cron workloads, per-execution run history lives in status.jobExecutions of that per-location detail. Pair with get_workload_events and get_workload_logs to diagnose failures.

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• queryPointInTimeMetrics

  Cortex

  Execute point-in-time queries for one or more engineering metrics. Returns current metric values for specified time periods, with support for batch queries and optional period-over-period comparisons. Time range (startTime/endTime) cannot exceed 6 months (180 days). PREREQUISITES - Follow this workflow: 1. Discover all available metrics ONCE: Call listMetricDefinitions (view='basic') - cache this response 2. Get metric query metadata ONCE per metric: Call listMetricDefinitions (view='full', key=METRIC_KEY) - supportedAggregations: Valid aggregation methods - orderByAttribute: Attribute path for sorting by metric values - groupByOptions[].key: Valid groupBy keys (use exact values, do NOT guess) - filterOptions[].key: Valid filter keys (use exact values, do NOT guess) Cache the full view response for each metric. Reuse the metadata from cached responses for subsequent queries on the same metric. 3. Construct query: Use the query metadata from the full view responses in step 2 to build valid point-in-time requests IMPORTANT: Cache only results from listMetricDefinitions. Do NOT cache point-in-time query results - always execute fresh queries for current data. Only refresh cached listMetricDefinitions responses if no longer in your context window or explicitly requested. Do NOT guess attribute names - always use exact values from listMetricDefinitions responses. Response includes: - Lightweight metadata: Column definitions optimized for programmatic use - Row data: Actual metric values and dimensional data - No heavy schemas: Source definitions excluded (get from listMetricDefinitions instead) Error responses: - 400: Invalid metric names, date range, validation errors, or unsupported metric combinations - 403: Feature not enabled (contact help@cortex.io)

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• smithsonian_get_object

  smithsonian-mcp-server

  Fetch the full catalog record for a Smithsonian object by its record_id (from smithsonian_search results). Returns all available metadata: title, dates, materials, dimensions, provenance, exhibition history, credit line, accession identifiers, and a media summary. Call smithsonian_get_media for full image URLs. Use record_id values from smithsonian_search — do not manually construct IDs.

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• aetherwave_reframe_image

  AetherWave Studio

  Reframes an image to a new aspect ratio by intelligently outpainting the edges. Pass a public `imageUrl` and the target `aspectRatio` ('16:9', '9:16', '1:1', '4:3', '3:4', etc.). Three speed tiers: 'turbo' (5 cr, fast), 'balanced' (10 cr, default), 'quality' (14 cr, slowest, best edges). Returns the reframed image URL.

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• get_case

  operant-mcp

  Return the full case for a given pair_id (axes 1/2/4) or id (axis 3): malign and benign task prompts, expected decisions, grounding rationale, and bypass patterns. Axis 3 cases are single (unmatched) and use an 'id' field instead of 'pair_id'. Use list_cases to browse available ids.

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• get_project_context

  main

  Captures the user's project architecture to inform i18n implementation strategy. ## When to Use **Called during i18n_checklist Step 1.** The checklist tool will tell you when to call this. If you're implementing i18n: 1. Call i18n_checklist(step_number=1, done=false) FIRST 2. The checklist will instruct you to call THIS tool 3. Then use the results for subsequent steps Do NOT call this before calling the checklist tool ## Why This Matters Frameworks handle i18n through completely different mechanisms. The same outcome (locale-aware routing) requires different code for Next.js vs TanStack Start vs React Router. Without accurate detection, you'll implement patterns that don't work. ## How to Use 1. Examine the user's project files (package.json, directories, config files) 2. Identify framework markers and version 3. Construct a detectionResults object matching the schema 4. Call this tool with your findings 5. Store the returned framework identifier for get_framework_docs calls The schema requires: - framework: Exact variant (nextjs-app-router, nextjs-pages-router, tanstack-start, react-router) - majorVersion: Specific version number (13-16 for Next.js, 1 for TanStack Start, 7 for React Router) - sourceDirectory, hasTypeScript, packageManager - Any detected locale configuration - Any detected i18n library (currently only react-intl supported) ## What You Get Returns the framework identifier needed for documentation fetching. The 'framework' field in the response is the exact string you'll use with get_framework_docs.

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• get_attributes_for_model

  OpenDataModels MCP server

  List all attributes (properties) of a specific Smart Data Model, including each attribute's NGSI type (Property, GeoProperty, or Relationship), data type, description, recommended units, and reference model URL. Use this after get_data_model when the user wants to understand what fields a model has, what values they accept, or how to construct a valid NGSI-LD payload. Example: get_attributes_for_model({"model_name": "WeatherObserved"})

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• get_vehicle_details

  FINN Auto - Car Subscription

  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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• cwe_lookup

  ContrastAPI

  Look up MITRE CWE (Common Weakness Enumeration) catalog record from research view 1000. Default response is SLIM (first 3 mitigations, first 3 examples; extended_description is null) — pass include='full' for the verbose record (full mitigations + examples lists, populated extended_description). Returns description, abstract type (Pillar/Class/Base/Variant/Compound), status (Stable/Draft/Incomplete/Deprecated), exploit likelihood, recommended mitigations, observed example CVEs, parent_cwe (walk up the hierarchy), child_cwes (drill down to more specific weaknesses), and cve_count (LOWER BOUND — counts only CVEs whose primary CWE matches; CVEs with multiple CWEs may not be counted). Use after cve_lookup or kev_detail to understand the underlying weakness category; chain with cve_search(cwe_id=...) to enumerate all matching CVEs. Returns 404 when the CWE is not in research view 1000. Free: 30/hr, Pro: 500/hr. Returns {cwe_id, name, description, extended_description (null on slim, populated on include='full'), abstract_type, status, likelihood, mitigations (first 3 by default), total_mitigations, examples (first 3 by default), total_examples, parent_cwe, child_cwes, cve_count, updated_at, verdict, next_calls}.

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• compare_gear

  outdoorithm

  Compare 2-3 gear items side-by-side with specs, pros/cons, verdicts, and comparison summary. Supports lookup by unique_id with slug fallback. Use search_gear first if the user hasn't named specific products. Args: gear_ids: List of 2-3 gear item identifiers (unique_id or slug)

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• find_sections

  masnavi

  Search section TITLES (not beyt content) for a Persian phrase. Each match includes `first_citation` and `last_citation` — ready-to-use canonical citations (e.g. 'M2:2608'). To read a whole multi-section story, call get_range with the FIRST match's `first_citation` as start and the LAST match's `last_citation` as end. Do NOT construct a citation from `first_beyt_global` — that is a GLOBAL index (1..25635), not a daftar-local beyt number. Example: find_sections('ابلیس معاویه', daftar=2).

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• describe_endpoint

  Sugra API

  Describe one Sugra API endpoint by operation_id. Includes agent_hints (duration_class fast/slow/heavy, max_concurrency, bulk billing) so you can budget timeouts and parallelism before calling. POST endpoints with a JSON body also carry request_body_schema (the resolved JSON schema) - construct the `body` argument from it instead of guessing key names.

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• get_payment_requirements

  dns-of-money

  Get x402 PaymentRequirements for paying a pay: alias. Returns the 402 `accepts` block (scheme, network, payTo, asset, amount, invoiceId) an x402 agent needs to construct and submit the payment. currency='XRP' settles on the XRP Ledger (amount in drops); currency='USDC' settles USDC on Algorand via the GoPlausible facilitator (amount in atomic micro-USDC, feePayer in `extra`). The deterministic resolver chooses the rail; this tool never moves money. Example: get_payment_requirements('pay:acme.user', amount='1.5').

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• autocomplete_danish_word

  dannet

  Get autocomplete suggestions for Danish word prefixes. Useful for discovering Danish vocabulary or finding the correct spelling of words. Returns lemma forms (dictionary forms) of words. Args: prefix: The beginning of a Danish word (minimum 3 characters required) max_results: Maximum number of suggestions to return (default: 10) Returns: Comma-separated string of word completions in alphabetical order Note: Autocomplete requires at least 3 characters to prevent excessive results. Example: suggestions = autocomplete_danish_word("hyg", 5) # Returns: "hygge, hyggelig, hygiejne"

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• lz_broadcast_signed_tx

  Tenzro LayerZero V2 MCP

  Broadcast a pre-signed Ethereum transaction via eth_sendRawTransaction on the source chain RPC. Use this as the canonical broadcast path for calldata produced by lz_send_message (EndpointV2.send), lz_oft_send (OFT.send), lz_stargate_send (StargatePoolNative.sendToken), and lz_transfer_build (Value Transfer API steps). Returns the transaction hash on success. The caller must construct calldata, sign locally with msg.value = nativeFee from the corresponding quote tool, then submit the RLP-encoded signed tx hex here.

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• lion_payment_attempt_readiness_audit

  LION - Trend Intent MCP + Marketplace Visibility Audit

  Pre-spend payment-term trust check for x402 endpoints. Before your agent signs a Payment-Signature, call this with a target x402/MCP service URL: LION extracts the target live 402 payment terms (payTo, amount, asset, network, scheme), cross-checks them for drift across public discovery surfaces, and returns payment_attempt_blockers, buyer_policy_fit, canonical_purchase_recipe, funnel_stage, a transparent readiness score, and risk_flags so the agent can decide whether to sign. 0.05 USDC on Base eip155:8453. Unpaid tools/call returns JSON-RPC error -32402 with the x402 paymentRequirement; wallet-capable MCP clients (e.g. Coinbase Payments MCP, AWS AgentCore Payments) auto-construct the EIP-3009 signature. LION does NOT perform payment inside MCP. Checks payment-term consistency only - not a smart-contract security audit, no settlement guarantee, no fund movement.

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