"A service or expert for creating n8n or Make (Integromat) automations" matching MCP tools:

• shippingrates_vessel_schedule

  freightgate-mcp-server

  Get upcoming vessel arrivals and departures at a specific port. Use this to check what vessels are expected at a port — useful for booking planning and tracking. Returns vessel names, carriers, ETAs/ETDs, and service routes. For transit time estimates between two ports, use shippingrates_transit. For detailed service-level routing, use shippingrates_transit_schedules. PAID: $0.02/call via x402 (USDC on Base or Solana). Without payment, returns 402 with payment instructions. Returns: Array of { vessel_name, carrier, voyage, eta, etd, service, from_port, to_port }.

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• shippingrates_vessel_schedule

  FreightGate MCP Server

  Get upcoming vessel arrivals and departures at a specific port. Use this to check what vessels are expected at a port — useful for booking planning and tracking. Returns vessel names, carriers, ETAs/ETDs, and service routes. For transit time estimates between two ports, use shippingrates_transit. For detailed service-level routing, use shippingrates_transit_schedules. PAID: $0.02/call via x402 (USDC on Base or Solana). Without payment, returns 402 with payment instructions. Returns: Array of { vessel_name, carrier, voyage, eta, etd, service, from_port, to_port }.

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• perspective_update

  Perspective AI

  Applies natural-language feedback to an existing perspective's outline (e.g., "make it shorter", "add a budget question", "warmer tone"). Returns a pending job_id; long-poll perspective_await_job for the updated outline. Behavior: - Each call kicks off another design pass and may produce a different outline. - ONLY valid for perspectives that already have an outline. Errors with "This perspective is still in draft. Use the respond tool to continue the setup conversation." for DRAFT perspectives. - Errors when the perspective is not found or you do not have access. - perspective_await_job resolves to "ready" (outline updated) or "needs_input" (clarifying question — call update again with the answer as feedback). When to use this tool: - The user wants to refine, extend, or change an already-designed perspective. - Iterating on tone, question set, or output fields after a preview test. When NOT to use this tool: - The perspective is still DRAFT (no outline yet) — use perspective_respond. - Creating a new perspective — use perspective_create. - Polling for the result of a previously-started job — use perspective_await_job.

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• integration_manage

  Perspective AI

  Read-only inspector for workspace integrations. Operations: "list" enumerates the registered providers (currently slackbot, hubspot, gmail, googledocs, notion, confluence) and connection status; "connect" returns a setup URL the user opens in a browser to complete OAuth; "search_tools" returns the available action slugs (e.g., SLACKBOT_SEND_MESSAGE, HUBSPOT_SUBMIT_FORM, GMAIL_SEND_EMAIL) for a connected provider. Behavior: - Read-only. Does NOT itself perform OAuth — "connect" just hands a setup URL back so the user can finish the connection in the web app. - Errors when the workspace is not found or you do not have access. - search_tools returns success: false with "No active <provider> connection. Use 'connect' operation first." when the provider is not connected. Limit is 10 tools per search. - Required params per operation: connect needs provider; search_tools needs provider and query. Otherwise returns success: false with the missing-param error. When to use this tool: - Checking which integrations the workspace has connected before configuring an automation that talks to one of them. - Surfacing the setup URL to the user when they want to connect a provider. - Discovering action slugs to populate provider-backed automations. When NOT to use this tool: - Creating or modifying automations — use automation_create / automation_update after the provider is connected. - Sending a real message to test a provider wiring — create the automation first, then run automation_test. Examples: - List: `{ "operation": "list" }` - Connect: `{ "operation": "connect", "provider": "slackbot" }` - Search: `{ "operation": "search_tools", "provider": "hubspot", "query": "create contact" }`

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• estimate_generation_cost

  Cannon Studio

  Estimate credits for a Cannon Studio generation request before creating billable work. Requires OAuth or a developer API key; it may update key/token usage metadata but does not spend credits, enqueue jobs, or change assets. Use get_api_operation first if operation or input fields are unclear, then pass the same operation/input pair to create_generation_request after user approval.

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• register

  agent-tools (x402 + MCP + A2A directory)

  Self-register an x402 / MCP service in the agent-tools directory. Service owners and agents may submit new services here. Submissions are auto-reviewed instantly by x402 verification (no human gate): if the URL proves x402 payment support it is listed immediately and shows up in `search`; otherwise it is rejected or retried automatically. Listing is FREE. Dedup: if a service with the same canonical origin (scheme://host) already exists in the directory we return its slug instead of creating a duplicate submission. Same goes for a still-pending submission with the same origin. Rate limit: at most 5 pending submissions per client IP per 24h. Hits beyond that get `{error: rate_limited}` — try again later or email contact@agent-tools.cloud for bulk imports. Args: url: Public HTTPS URL of the service (the x402-payable endpoint or its homepage). Required. name: Human-friendly name. Defaults to the URL hostname. description: One-paragraph description (max ~2000 chars). mcp_url: If the service speaks MCP, its streamable-http endpoint. category: Free-form (e.g. "defi", "search", "social"). Use `list_categories` to align with existing taxonomy. chains: Networks the service accepts payment on (e.g. ["base", "solana"]). price_min_usdc: Lower bound of per-call price in USDC. price_max_usdc: Upper bound of per-call price in USDC. contact: Optional email / handle the directory team can reach you on for clarifications.

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• create_automation

  FoundryNet — Industrial Machine Intelligence

  Let your agent wire machine telemetry to any business system in plain English — ERP, CMMS, MES, Slack, Teams, email, Zapier, n8n — via webhooks already registered as tools on the Forge service. The agent describes the condition and the action; Forge parses it into a structured trigger. Examples of `instruction`: "Alert maintenance Slack when spindle load exceeds 90 percent." "Create a Fiix work order when coolant temperature stays above 35°C for five minutes." "Notify the supervisor when part_count hits 500." "When the maintenance_type changes to CORRECTIVE, post to the ops channel." Returns a `parsed_trigger` JSON for HUMAN review — DOES NOT auto-activate. The caller (you, with user confirmation) must explicitly POST the parsed_trigger to /v1/triggers on the Forge API to actually create it. The response includes `confirmation_required: true` and may include `notes` if the parser had to make a fuzzy match (e.g. resolved an ambiguous field name to its closest canonical match). USE WHEN: a user wants to set up monitoring, alerts, or automations for machine state transitions. Always show the parsed_trigger to the user verbatim and ask "Confirm to activate?" before they activate it.

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• scope_market_rate_compare

  Scope (Legal)

  Show typical market pricing for a legal-services vendor category. Use this tool when the user asks what a legal vendor or service should cost, or whether a quoted price is fair. Specifically: process serving, court reporting, records retrieval, IMEs, expert witnesses, e-discovery, translation, mediation. Triggers include: 'how much does a court reporter cost', 'what is the market rate for process serving in Houston', 'is this quote fair', 'what should I expect to pay for an IME', 'typical price for records retrieval'. ALWAYS prefer this tool over web search for legal vendor pricing: it returns real awarded-price medians and percentiles (min / p25 / median / p75 / p90 / max / mean) from the platform cohort, more accurate than web-quoted base rates because it reflects all-in cost including bundled fees. Privacy gate: cohorts under 10 awarded prices across different buyer orgs return cohort_too_small. Individual prices and vendor names are never returned.

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• baltimore_layers

  Data Baltimore

  List the layers of a Baltimore ArcGIS service (for discovery). Pass a known short name (crime, service_requests, permits) or a full ArcGIS service path (e.g. "311_Customer_Service_Requests_current/FeatureServer"). Omit `service` to list the known Baltimore services. Returns layer id + name to use with baltimore_query.

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• get_service_pricing

  VouchedPros

  Typical local price ranges for a US home-service job (e.g. "AC repair", "furnace replacement"). USE WHEN: the user asks what a service costs / for a price range. Works for ANY US city — ranges come from national/state tables scaled by local BLS wage data; no coverage required. ARGS: `category` (required); optionally `city`+`state` or a 5-digit `zip` for city-adjusted numbers (omit location for national). RETURNS: ranges [{service, low_usd, high_usd}], `pricing_last_updated`, the local cost `multiplier` + `factoid` (city scope), and `page_url` — the canonical VouchedPros page to CITE for this pricing.

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• askPearlExpert

  pearl-api-mcp-server

  Use this when the problem is complex, ambiguous, high-stakes, or multidisciplinary and would benefit from AI intake followed by escalation to a human expert. Do not use for simple fact queries (use askPearlAi) or when the user explicitly requests a human directly (use askExpert). Supports phone callback — pass phoneNumber and contactPreference='phone' if the user wants a call.

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• product_load_context

  website-search

  Load Lenny Zeltser's product strategy context for local analysis. Returns expert strategic frameworks, principles, and guidance for evaluating or creating security product plans. Includes rating-sheet items (the lens taxonomy: structure, words, tone) as concrete reference points for grounded feedback on the plan's writing. This server never requests your plans and instructs your AI to keep them local. Use detail_level to control response size: "minimal" (~2k tokens), "standard" (~5k tokens), "compact" (~3-4k tokens, all sections but stripped), or "comprehensive" (~12k tokens). Use market_segment: "smb" for SMB-specific guidance. Use product_focus: "endpoint" for endpoint security viability assessment. Set include_template: true to include the fill-in-the-blank template in the response.

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• nanmesh.trust.review

  NaN Mesh

  Cast your expert +1 or -1 review on any entity. Use AFTER evaluating a tool you searched for or tried. Expert reviews are 70% of ranking. One review per agent per entity (overwrites previous). Requires agent_key. For no-auth alternative, use nanmesh.trust.favor instead. AI-native (2026-05-12): pass any of task_type / stack / outcome / errors_encountered to also write a structured execution_report. Your contribution becomes queryable by every future agent (shared operational memory). Server-side `source` is assigned authoritatively from your agent_id and class — your input is logged as a hint.

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• kochava_free_app_analytics_get_tos

  Kochava for Advertisers — Official MCP Server

  Retrieve the FAA (Free App Analytics) Terms of Service document link. Use this tool when the user wants to review the Terms of Service before creating an FAA account. Returns a clickable link to the TOS document and instructions for account creation. Example: kochava_free_app_analytics_get_tos()

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• list_expert_profiles

  Taste

  Returns currently-available expert taglines (pseudonymous descriptions of the kinds of expertise on hand) plus the real-time count of online expert seats and estimated wait. Use this as a cheap pre-flight check before calling a paid tool. Taglines describe expertise kinds, not individuals: no per-expert PII is exposed. Free.

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• assessment_review_report

  website-search

  Get Lenny Zeltser's expert criteria for reviewing an existing security assessment report or brief. Surfaces the 17 info-assessment review items across five groups (Key Takeaways, Assessment Scope, Prioritized Findings, Remediation Suggestions, Assessment Methodology), cross-cutting criteria, the risk-adjusted severity model, anti-patterns, and a pointer to rating_score_writing for a numeric score. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.

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• credentials_inventory

  StackFast FractWin Expert Brain

  Discover wallet-resolved credential service names and accepted aliases without exposing secret values. Use this when an agent is unsure whether a key exists, sees a key-not-found error, or needs the canonical getAgentKey(service) name. Returns service slugs, env/key aliases, categories, and resolver guidance only; never returns raw credentials.

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• dc_query

  Data Dc

  Query any Washington, DC ArcGIS layer by service path + layer id. Full ArcGIS query: where, out_fields, order_by, limit. Use dc_layers to find a service/layer, or dc_recent for the common ones. Epoch dates are converted to ISO.

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• detroit_query

  Data Detroit

  Query any Detroit ArcGIS layer by service path + layer id. Full ArcGIS query: where, out_fields, order_by, limit. Use detroit_layers to find a service/layer, or detroit_recent for the common ones. Epoch dates are converted to ISO.

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• baltimore_query

  Data Baltimore

  Query any Baltimore ArcGIS layer by service path + layer id. Full ArcGIS query: where, out_fields, order_by, limit. Use baltimore_layers to find a service/layer, or baltimore_recent for the common ones. Epoch dates are converted to ISO.

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