"B&R Automation" matching MCP tools:

• automation_test

  Perspective AI

  Runs a single end-to-end execution of an existing automation against a mock conversation, returning success/failure plus the channel target and duration. Mirrors a real production firing. Behavior: - Sends REAL messages by default: posts the configured webhook, sends the configured email, posts the Slack message, or writes the HubSpot record. Use override_email (email channels) or override_webhook (webhook channels) to redirect delivery to a safe test target. - Each call fires another real delivery. - Errors when the perspective or automation is not found, or you do not have access. Webhook URLs (configured or override) are validated. - Mock conversation defaults: trust score 85, status complete, "Test Participant" / test@example.com. Override participant_name, summary, and tags via test_data. - Returns success: true also when the automation's condition skips delivery (e.g., tag/trust filter doesn't match the mock). The error field is populated only on real delivery failures. When to use this tool: - Verifying a freshly-created automation actually delivers before relying on it (override_email / override_webhook direct the test to a safe target instead of real recipients). - Reproducing a delivery failure surfaced in automation_list (last_error). When NOT to use this tool: - Listing what's configured — use automation_list. - Changing config — use automation_update. - Removing the automation — use automation_delete.

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• automation_update

  Perspective AI

  Updates fields on an existing automation. Pass a partial updates object with only the fields you want to change; omitted fields are preserved. Toggling enabled or changing schedule/channel/condition takes effect on the next scheduled run. Behavior: - Saves the change to the same automation record. Scheduled automations with an active workflow are restarted on update so the next run picks up the latest config. - Errors when the perspective or automation is not found, or you do not have access. - Webhook URLs in updates are validated. For HubSpot, the workspace's HubSpot connection is re-checked — errors with "Could not resolve HubSpot portal ID — please reconnect HubSpot" if disconnected. - For scheduled automations: changes to channel, condition, execution mode, instruction, or message template apply starting from the next run, not the one currently in flight. When to use this tool: - Toggling enabled on or off (also pauses/resumes scheduled sends). - Changing schedule, channel, condition, instruction, or message_template on a live automation. When NOT to use this tool: - Removing the automation entirely — use automation_delete. - Verifying a config change actually delivers — follow up with automation_test. - Listing what's configured — use automation_list.

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• find_compatible_with

  eurorack

  Return modules that have a typed compatibility relationship with the given module. Both edge directions are returned and tagged via the per-match `direction` field — so a single call answers both "what is X a R for?" and "what is a R for X?". `relationship` is OPTIONAL. Omit it to get EVERY edge touching the module across all relationship kinds — the bare "what pairs with / relates to X?" question — with each match self-describing via its own `relationship`. Pass a relationship to restrict to that one kind. Prefer the relationship-less call when you don't already know which kind exists; reach for the typed form only when the question names a specific role ("what clocks X?"). Use this for two question shapes: 1. Patch-time compatibility — "what could I use as a clock source for X?" (returns matches with direction='inbound'), or "what does X clock?" (direction='outbound'). 2. Catalog comparison — "what's an alternative to X?" (symmetric), "what does X replace?" (outbound) / "what replaces X?" (inbound), "is there an expander for X?" (inbound). The vocabulary describes the edge as stored (from = role-bearer, to = target): Patch-time: - clock-source-for — A clocks B - cv-source-for — A produces CV that B consumes - modulator-for — A is a modulator suitable for B (LFO, S&H, random) - audio-source-for — A is an audio source for B (typically a VCO into a VCF) - quantizer-for — A quantizes for B - trigger-source-for — A produces triggers that B consumes - envelope-target-for — A is something B's envelope output is designed to drive Catalog: - replaces — A is the newer successor to B (Morphagene replaces Phonogene) - alternative-to — symmetric: A and B occupy similar design space with different character - expander-for — A is an expander module for the host module B Direction tag on each match: - outbound: queried module is the FROM side (role-bearer). Match is what the queried module does as R. - inbound: queried module is the TO side. Match is the R-for the queried module. - symmetric: only for alternative-to. Args: - module_id (string, required): "<manufacturer-slug>/<module-slug>" - relationship (string, optional): one of the values above. Omit for all edges. - limit (number): default 50, max 200 Returns: { "module": { id, name }, "relationship": <relationship> | null, // null when none was passed (all-edges query) "matches": [{ id, name, manufacturer, notes, source_id, direction, relationship }] } If the module is unknown, returns an error. If no relationships have been recorded in either direction, returns matches=[]. The `notes` field describes the edge in the canonical A→B direction; combined with `direction` the caller can read it correctly either way.

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• read_account_info

  Arcadia Finance

  Get full overview of an Arcadia account: health factor, collateral value, debt, deposited assets, liquidation price, and automation status. Health factor = 1 - (used_margin / liquidation_value): 1 = no debt (safest), >0 = healthy, 0 = liquidation threshold, <0 = past liquidation. Higher is safer. On all supported chains returns an `automation` object showing which asset managers are enabled (rebalancer, compounder, yield_claimer, merkl_operator, gas_relayer, cow_swapper). Automation detection spans every asset-manager version deployed on the selected chain, so registrations made on older versions are still reported as active; the returned value is the user-facing dex_protocol (e.g. 'slipstream') with no version suffix. LP positions in assets[] include a dex_protocol field (slipstream, slipstream_v2, slipstream_v3, staked_slipstream, staked_slipstream_v2, staked_slipstream_v3, uniV3, uniV4) — use this as the dex_protocol param for write_asset_manager.* tools. Slipstream V2 is Base-only. V3 is available on Base and Optimism. Unichain supports only Slipstream V1, uniV3, and uniV4. The automation object uses internal AM key names (slipstreamV1, slipstreamV2, slipstreamV3, uniV3, uniV4): map slipstreamV1 → 'slipstream'/'staked_slipstream', slipstreamV2 → 'slipstream_v2'/'staked_slipstream_v2', slipstreamV3 → 'slipstream_v3'/'staked_slipstream_v3', uniV3 → 'uniV3', uniV4 → 'uniV4'. Numeric fields without a _usd suffix are in the account's numeraire token raw units (divide by 10^decimals: 6 for USDC, 18 for WETH, 8 for cbBTC). Fields ending in _usd are in USD with 18 decimals (divide by 1e18). health_factor is unitless. Asset amounts are raw token units. To list all accounts for a wallet, use read_wallet_accounts.

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• automation_create

  Perspective AI

  Creates an automation on a perspective. Triggers: per_interview (fires on every completed conversation) or scheduled (daily/weekly digest). Channels: webhook, email, slack, hubspot. Execution modes: direct (fast, deterministic) or agent (LLM-powered). Behavior: - Each call creates a new automation — even if name/config matches an existing one. - Once enabled, the automation starts firing on real events: per_interview sends on every completed conversation going forward; scheduled sends a real message on the configured cadence (daily/weekly). - Webhook URLs are validated. For HubSpot, the workspace's HubSpot connection is required — errors with "Could not resolve HubSpot portal ID — please reconnect HubSpot" if not connected. - Errors when the perspective is not found or you do not have access. When to use this tool: - The user wants ongoing notifications on every completed conversation (per_interview). - Building a daily/weekly digest delivered to Slack, email, HubSpot, or a webhook (scheduled). When NOT to use this tool: - Trying a one-off send before going live — create the automation, then use automation_test (use override_email / override_webhook to avoid hitting real recipients). - Editing or toggling an existing automation — use automation_update. - Connecting Slack or HubSpot — use integration_manage first; the provider must be connected before slack/hubspot channels work. Example — per-conversation Slack notify: ``` { "perspective_id": "...", "automation": { "name": "Notify Slack", "trigger": { "type": "per_interview" }, "execution_mode": "agent", "channel": { "type": "composio", "delivery_config": { "provider": "slackbot", "tool_slug": "SLACKBOT_SEND_MESSAGE", "params": { "channel": "#research" }, "resource_id": "...", "resource_name": "..." } } } } ``` Typical flow: 1. integration_manage (operation: "list"/"connect") → ensure Slack / HubSpot is connected (only needed for those channels) 2. automation_create → create the automation 3. automation_test (with overrides) → verify delivery before relying on it

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• free2aitools_explain

  Free2AITools

  Explain why a specific entity received its FNI ranking score by showing the 5-factor breakdown: Semantic (S), Authority (A), Popularity (P), Recency (R), Quality (Q). FNI = 0.35*S + 0.25*A + 0.15*P + 0.15*R + 0.10*Q. Read-only. Use this after search or rank to understand why an entity scored high or low; use free2aitools_compare instead for side-by-side differences between multiple entities.

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• automation_delete

  Perspective AI

  Permanently deletes an automation. Pauses any scheduled sends first, then removes the automation. Behavior: - DESTRUCTIVE and irreversible — the automation cannot be recovered. No undo. - Errors when the perspective or automation is not found, or you do not have access. Deleting an already-deleted automation errors as well. - If pausing the scheduled sender fails, the deletion is aborted and you'll get success: false with "Failed to stop running workflow. Please try again." — the automation stays intact in that case. When to use this tool: - The user explicitly asked to remove an automation and confirmed. - Cleaning up a misconfigured automation that automation_test repeatedly fails on. When NOT to use this tool: - The user just wants to pause it temporarily — use automation_update with { enabled: false } instead. - You're not sure which automation_id is correct — confirm via automation_list first.

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• check_bulk

  DepScope

  Fast pre-flight filter for a batch of (ecosystem, package) pairs. DB-only, <100ms for 100 items. USE WHEN: about to emit `npm install a b c …` or `pip install a b c …` — catches hallucinated names, stdlib, typos, and known-bad in ONE call. NOT a dep-tree audit (use scan_project for that). RETURNS: per-item {status: exists|stdlib|malicious|typosquat_suspect|historical_incident|unknown}.

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• find_drivers

  Autario Data Analytics Platform

  KILLER ANALYSIS: given a target KPI + multiple candidate indicators, rank which candidates best predict the target by correlation strength. Perfect for "what moves my KPI?" questions. Returns ranked list with r, p-value, R² for each candidate. Maximum 30 candidates per call.

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• stir_attestation_explainer

  Sipflow

  [cost: free (pure CPU, no network) | read-only] Static explainer for STIR/SHAKEN: maps attestation levels (A / B / C per RFC 8588) to plain-English requirements + common scenarios, and SIP codes commonly emitted by signing/verification (428 / 436 / 437 / 438 / 608) to their RFC anchors and operator causes. Provide either `attestation` (A/B/C) or `code` (e.g. 438). Pair with: `validate_stir_shaken_identity` when the user has the JWS segments and wants the cryptographic verdict; `search_sip_docs({ sourceType: 'stir-shaken', ... })` for ATIS / CTIA / RFC depth.

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• get_product_recommendation

  Custom Blinds Shop

  Translate a customer's primary concern into a product recommendation. primary_concern must be one of: blockout, heat, glare, moisture, privacy, security, automation. Optionally narrow by room (bedroom, lounge, etc.), location, budget, and aesthetic. Returns a recommended product_id with rationale — pass it to get_price or configure_product next. Security concern routes to brochure MCP (Garden Route customers only).

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• list_services

  Escola de Rádio TV & Web (ER+)

  Lista serviços oferecidos pela ER+ ALÉM dos cursos regulares: 'demo' (gravação de demo profissional com Ruy, R$ 350), 'mentoria' (mentoria 1:1 com Ruy, R$ 250/h), 'b2b' (treinamentos corporativos pra empresas). Use quando aluno perguntar sobre demo, mentoria, treinamento empresarial. Pra cursos regulares, use list_courses.

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• optimize_home_loan_tax_regime

  AVnester — Indian Real Estate Intelligence

  Compare a home-loan borrower's income tax under the OLD vs NEW regime (FY2026-27) and recommend which regime saves more income tax. Pure deterministic slab math — not tax advice. Use when the user asks "old or new tax regime", "home-loan tax benefit", or "section 80C / 24(b) deduction". Models §24(b) interest + §80C principal (+ joint-loan doubling); the response lists benefits it does NOT model (capital gains, HRA, etc.). Always surface the disclaimer field.

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• noaa_spaceweather_get_conditions

  noaa-spaceweather-mcp-server

  Current space-weather snapshot: NOAA R/S/G storm scales (today + 3-day forecast), latest Kp index with its G-scale equivalent and aurora-visibility latitude, and a plain-language status summary. The quickest way to answer "is anything happening right now?" — use before deciding whether to drill into solar wind (noaa_spaceweather_get_solar_wind), aurora (noaa_spaceweather_get_aurora_forecast), or alert details (noaa_spaceweather_get_alerts).

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• noaa_spaceweather_get_solar_activity

  noaa-spaceweather-mcp-server

  Solar flare and radiation storm picture: recent GOES X-ray flux with flare-class labels (A/B/C/M/X), 3-day flare-class probabilities (C/M/X), active solar regions with per-region flare probabilities, and GOES integral proton flux at ≥10 MeV with NOAA S-scale. For operators tracking HF radio blackout (R-scale, driven by X-ray) and radiation storm risk (S-scale, driven by protons). Active region data helps identify which region is driving current activity.

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• get_category_landscape

  StackSwap

  Full map of one GTM category — leaders, runner-ups, and skip/replace candidates. Returns every catalogued tool in the bucket with cost, AI-readiness, swap-registry status, and partner sign-up links. Use when the user wants to see the full landscape for a category (e.g. 'show me all CRMs', 'what outbound tools exist', 'map the analytics category') — strictly more comprehensive than `recommend_partner` (single best pick). Known buckets: crm, outbound, data, marketing-automation, analytics, meetings, support, scheduling, automation, seo, cdp, revenue-intelligence, chat, collaboration, phone, landing-pages, linkedin, ai-content, saas-mgmt, enablement, ai-tooling.

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• aetherwave_list_master_presets

  AetherWave Studio

  Returns every AI mastering preset AetherWave supports, with target LUFS, tags, descriptions, and difficulty level. Call this before master_audio when you don't know which preset fits the track. 12 presets total covering streaming, hip hop, EDM, pop, rock, lo-fi, R&B, acoustic, cinematic, podcast, gentle, and loud-and-punchy mastering styles. Each preset has a target LUFS value (e.g. -14 for streaming, -9 for loud) so you can match the user's distribution target.

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• calc_interest

  Math MCP Learning

  Calculate compound interest for investments. Formula: A = P(1 + r/n)^(nt) Where: - P = principal amount - r = annual interest rate (as decimal) - n = number of times interest compounds per year - t = time in years Examples: compound_interest(10000, 0.05, 5) # $10,000 at 5% for 5 years → $12,762.82 compound_interest(5000, 0.03, 10, 12) # $5,000 at 3% compounded monthly → $6,744.25

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• get_available_doc_gens

  Skala — Legal Platform for Startups

  Get the list of legal document templates available for generation on the platform (e.g. NDA, employment agreement, stock purchase agreement). For corporate services like 83(b) filing or registered agent, use get_available_corporate_services instead.

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• handoff_audit

  governance-platform

  Audit a handoff between two chain stages. Returns a context capsule with verified facts from the prior stage and checks structural compatibility of proposed data for the next stage. Use this between chain stages to ensure Agent B receives only verified data from Agent A, and that nothing was mutated in transit. Sibling tools: create_chain (define the pipeline), submit_chain_stage (advance through it), handoff_audit (verify between stages). The context capsule contains: - Verified fields and their values from the prior stage - Determinism hash proving the prior stage's results - Blueprint constraints the next stage must satisfy - Compatibility verdict if proposed_data is provided Args: api_key: GeodesicAI API key (starts with gai_) chain_id: Chain identifier from create_chain from_stage: Stage name that completed (Agent A) to_stage: Stage name about to start (Agent B) proposed_data: Optional data Agent B intends to submit — checked for compatibility

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