"Using AI to control and access data from Home Assistant and smart home devices" matching MCP tools:

• check_compatibility

  product-intelligence

  Check if a smart home device fits a user's existing setup using SmartHomeExplorer's proprietary Compatibility Engine. Evaluates across 7 ecosystems (Google Home, Alexa, HomeKit, SmartThings, Matter, Hubitat, Home Assistant), 8 wireless protocols, hub requirements, and subscription cost stacking. Returns a compatibility score (0-100) and verdict (great-fit / works / caution / poor-fit). This cross-ecosystem analysis is unique to SmartHomeExplorer — no other public service evaluates device-to-device compatibility across platforms. Methodology at smarthomeexplorer.com/she-score-methodology.

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• compare_products

  product-intelligence

  Side-by-side comparison of 2-4 smart home products using SmartHomeExplorer's editorially curated data. Compares SHE Consensus Score (from 12 expert sources), ecosystem support levels, subscription costs, and key differentiators. Returns a data-backed winner determination with source-linked review page URLs. Methodology at smarthomeexplorer.com/she-score-methodology.

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• analyze_company

  Nordic Financial MCP

  AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'

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• axint.templates.list

  Axint

  List all 26 bundled reference templates in the Axint SDK. Returns a JSON array of { id, name, description } objects — one per template. Templates cover messaging, productivity, health, finance, commerce, media, navigation, smart-home, and entity/query patterns. No input... Use: use to discover valid template ids before templates.get. Effects: read-only template metadata; writes no files and uses no network.

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• analyze_record

  Senzing

  Get the Senzing JSON analyzer script to validate mapped data files client-side. REQUIRED: `workspace_dir` (writable directory, e.g. ~/sz-workspace) — the call WILL FAIL without it. The analyzer validates records against the Entity Specification, examines feature distribution, attribute coverage, and data quality. Returns a Python script (no dependencies) with instructions. No source data is sent to the server. Typical workspace_dir values: Linux `/tmp` or `~/sz-workspace`; macOS `~/sz-workspace`; sandboxed envs: explicit path under home (do NOT assume /tmp exists).

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• dossier_cors

  drwho.me

  Core dossier check: Send a CORS preflight OPTIONS request to https://<domain>/ and return the access-control-* response headers. Use to verify CORS policy for a specific origin-method pair, or to check whether a domain allows cross-origin requests; provide origin and method to simulate a precise preflight, or omit to use defaults (origin: https://domainposture.com, method: GET). Single OPTIONS request via fetch, 5 s timeout. Returns a CheckResult: on success, {status:"ok", headers:{access-control-allow-origin,...}}; on failure, {status:"error", reason}.

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• list_covered_events

  Crosswire

  Free discovery of everything check_resolution_risk can audit: the covered canonical World Cup events, their per-outcome pair ids (…#home / #draw / #away), the Polymarket conditionIds and Kalshi tickers with outcome labels for each pair, match dates, the frozen ruleset_sha pinning the identity graph, the coverage kickoff cutoff, and snapshot freshness. Use a returned pair_id (or a pair's two market ids) as input to check_resolution_risk.

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• calculate_home_affordability

  AVnester — Indian Real Estate Intelligence

  Estimate the monthly home-loan EMI / monthly payment in India — a home-loan calculator. Deterministic math; not advice or a loan-approval claim. Two modes: pass propertyValue (80% LTV assumed) OR loanAmount for a specific loan (e.g. "₹50 lakh loan"). Use for "what would my EMI be" / "monthly payment on …". The response `assumptionNote` states the basis in plain words. Always surface the disclaimer field.

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• list_store_categories

  agentView

  Lists all published agentView store categories (e.g. Gastronomie, Wartezimmer, Empfang, Smart Home) with localized titles, descriptions and template counts. Use this to narrow a subsequent search_store_templates call when the user asks for 'templates for a waiting room' or similar. No authentication required. Returns count, language and a categories array where each entry has slug, title, description, templateCount, heroIconKey and detailPath.

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• request_solar

  Utilify

  Capture a Texas homeowner's interest in rooftop solar and route to a licensed installer — use when the user owns (or is buying) a Texas home and mentions solar panels, solar quotes, solar savings, or reducing their bill through solar. Use when the user says 'I just bought a house in Austin and want solar quotes', 'how much could solar save on my Houston electric bill', or 'connect me with a solar installer for my new home'. Returns a lead ID and confirms next steps; Utilify routes the lead to installer partners (SunPower, Sunrun, Palmetto, and independent TX installers). Caveats: (1) only call when the user has explicitly opted in and confirmed homeownership — this is not for renters, and Utilify may earn a referral fee. (2) Texas-only — for non-TX addresses, decline and explain. (3) Don't double-call for the same address in one conversation; one lead per opt-in. If the user has only expressed mild curiosity ('I'm thinking about solar someday'), answer the question first and only call this tool once they confirm 'yes, connect me'.

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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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• scout.market_pulse

  Scout

  Public-data-backed market snapshot for any US zip code. Returns Census ACS demographics (population, median household income, median age, owner-occupancy %, median home value, median gross rent), Scout's indexed agent density for that zip, and listings activity if the zip is in our MLS-live coverage area. Call this when an AI user asks 'what's the market like in [zip/city]'. Free, no API key required.

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• add_ssh_key

  BorealHost

  Inject your SSH public key into a site's container for direct SSH access. The key is appended to /home/admin/.ssh/authorized_keys. Only available for VPS/dedicated plans. Requires: API key with write scope. Args: slug: Site identifier public_key: SSH public key string. Supported types: ssh-ed25519, ssh-rsa, ecdsa-sha2-nistp256/384/521 Returns: {"success": true, "message": "SSH key added", "ssh_command": "ssh admin@184.107.x.x"} Errors: VALIDATION_ERROR: Invalid or unsupported key format FORBIDDEN: Plan does not support SSH

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• list_live_deals

  AgentsPrice

  AgentsPrice public live-deals feed (electronics, gaming, home, fashion), cached about 10 minutes, containing only real sourced deals with live buy links. No API key required. Use for a quick read of what is genuinely on sale right now.

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• locator_digest

  DC Member API

  GET /locator/digest — Get locator digest Returns your weekly locator digest — the same data that powers the Friday locator email. Use this to surface trip/event activity around the people and cities a member already follows. The response is composed of four independent sections; pass `?sections=<csv>` to skip any you don't need. Each section is described in full below. - **`homeCity`** — Activity in the city you have set as your home chapter. Null if you have no home city, or if you don't belong to any chapter yet. - **`favoriteCities`** — Per-city digest for cities you have favorited (besides your home city). Each entry lists upcoming trips/events into that city + new ones added since last week. - **`favoritePeople`** — Recent activity from members you follow: their new trips, upcoming trips, recently purchased tickets, and events they've RSVPd to. - **`myTrips`** — For each of your own upcoming trips, the people you're likely to overlap with (chapter leads, local members, and other DCers visiting the same city in the same window). Pass a comma-separated subset to `?sections=...` to omit sections you don't use — useful for narrow integrations and faster responses.

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• request_solar

  Utilify

  Capture a Texas homeowner's interest in rooftop solar and route to a licensed installer — use when the user owns (or is buying) a Texas home and mentions solar panels, solar quotes, solar savings, or reducing their bill through solar. Use when the user says 'I just bought a house in Austin and want solar quotes', 'how much could solar save on my Houston electric bill', or 'connect me with a solar installer for my new home'. Returns a lead ID and confirms next steps; Utilify routes the lead to installer partners (SunPower, Sunrun, Palmetto, and independent TX installers). Caveats: (1) only call when the user has explicitly opted in and confirmed homeownership — this is not for renters, and Utilify may earn a referral fee. (2) Texas-only — for non-TX addresses, decline and explain. (3) Don't double-call for the same address in one conversation; one lead per opt-in. If the user has only expressed mild curiosity ('I'm thinking about solar someday'), answer the question first and only call this tool once they confirm 'yes, connect me'.

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• get_food_environment

  USDA Food Access

  Get county-level food access risk profiles using Census ACS data. Constructs food access risk profiles by combining vehicle access (B25044), poverty status (B17001), and SNAP participation (B22001). Limited vehicle access combined with high poverty indicates food desert risk. Useful for identifying areas with barriers to food access in grant applications. Args: state: Two-letter state abbreviation (e.g. 'WA', 'MS') or 2-digit FIPS code. county_fips: Three-digit county FIPS code (e.g. '033' for King County, WA). Omit to get all counties in the state.

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• ceevee_chat

  CareerProof MCP

  Send a message to CeeVee AI assistant for CV optimization guidance (2 credits). Requires a cv_version_id (use ceevee_upload_cv or ceevee_list_versions to get one). Returns AI response with optional edit suggestions, source citations, and a conversation_id. Omit conversation_id to start a new conversation; include it to continue a thread.

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• book_appliance_repair

  Sunrays — Local Service Booking

  Book an appliance repair technician for washing machines, dryers, refrigerators, dishwashers, ovens, or other major home appliances. Returns a confirmed booking. Call /quote first.

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• screen_land_market

  CRE Intelligence

  Screen a US county as a LAND-INVESTING market (raw-land flip / Podolsky style). Grades the county on the signals that matter for buying cheap rural land and reselling on terms: population growth, demographics, owner share, and affordability. IMPORTANT: This screens on FREE Census data only (growth + demographics + a home-value affordability proxy). It does NOT include actual land sale prices or comps — those require county records or a paid service, and must be verified per-parcel before buying. Use this to rank/shortlist markets, not to buy.

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