"Tide" matching MCP tools:

• pipeworx_feedback

  Noaa Tides

  Tell the Pipeworx team something is broken, missing, or needs to exist. Use when a tool returns wrong/stale data (bug), when a tool you wish existed isn't in the catalog (feature/data_gap), or when something worked surprisingly well (praise). Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. The team reads digests daily and signal directly affects roadmap. Rate-limited to 5 per identifier per day. Free; doesn't count against your tool-call quota.

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• pipeworx_trending

  Tides

  What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window (24h, 7d, or 30d). Useful for: (1) discovering what data sources are hot for current events, (2) confirming a popular tool is the canonical choice before asking your own question, (3) seeing whether your use case aligns with what most agents need. Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.

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• bart_stations

  BART Real-Time Transit

  List all BART stations with abbreviation codes and locations. Use this to look up station codes needed by other tools.

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• entity_profile

  Tides

  Get everything about a US public company in one call. Use when a user asks "tell me about X", "research Acme", "brief me on Tesla", or you'd otherwise call 10+ pack tools across SEC EDGAR, XBRL, USPTO, news, GLEIF. Returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC — Run 6 fix landed real FY2025 numbers, not stale FY2022); patents (USPTO PatentsView API was sunset May 2025; pack soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first).

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• check_api_key_status

  Nefesh — Real-Time Human State Awareness for AI

  Check the status of a pending API key request. Use the exact same email the user provided to request_api_key. Poll this every 10 seconds. Once the user clicks the verification link in their inbox, status changes from 'pending' to 'ready' and the response includes the API key. Store it immediately — returned once only. Expires after 15 minutes.

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• get_human_state

  Nefesh — Real-Time Human State Awareness for AI

  Get current unified human state for a session. Call this before generating important responses. Returns: - state: calm | relaxed | focused | stressed | acute_stress - stress_score: 0-100 (lower = calmer) - confidence: 0.0-1.0 (based on signal quality and device type) - suggested_action: maintain_engagement | simplify_and_focus | de-escalate_and_shorten | pause_and_ground - action_reason: human-readable explanation of why this action was suggested - adaptation_effectiveness (on 2nd+ call): shows whether your previous suggested_action actually reduced stress — contains previous_action, stress_delta, and effective boolean. Use this to self-improve. Use suggested_action to adapt your response: calm/relaxed = full complexity, focused = shorter and structured, stressed = max 2 sentences, acute_stress = one grounding sentence only. Requires a prior ingest call to have data. Not a medical device.

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• nausika_tides

  Nausika

  Tide predictions or station discovery at a coordinate (latitude, longitude). Default: predictions from the nearest NOAA station; outside US waters falls back to a global modeled-tide source. Set stations_only=true to discover stations (capped by limit). Tune the window with begin_date (YYYYMMDD) + range_hours, the reference with datum, and output units (metric/english). Example: latitude=37.77, longitude=-122.42. Chain nausika_geocode for place→coordinates; pair with nausika_marine_forecast.

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• generate_llms_txt

  Tides

  Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

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• request_api_key

  Nefesh — Real-Time Human State Awareness for AI

  Request a free Nefesh API key. No existing API key needed for this call. IMPORTANT: You MUST ask the user for their real email address before calling this tool. Do NOT invent, guess, or generate an email address. The user will receive a verification link they must click to activate the key. Without clicking that link, no API key will be issued. Disposable or temporary email services are blocked. Example prompt to the user: "What is your email address? You will receive a verification link to activate your free API key." Flow: call this with the user's real email, then poll check_api_key_status every 10 seconds until status is 'ready'. Free tier: 1,000 calls/month, all signal types, 10 req/min. No credit card.

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• scan_competitor_ai_presence

  Noaa Tides

  Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Returns ranked list with score, confidence, signal density per entity.

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• ai_visibility_check

  Tides

  Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.

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• remember

  Noaa Tides

  Save data the agent will need to reuse later — across this conversation or across sessions. Use when you discover something worth carrying forward (a resolved ticker, a target address, a user preference, a research subject) so you don't have to look it up again. Stored as a key-value pair scoped by your identifier. Authenticated users get persistent memory; anonymous sessions retain memory for 24 hours. Pair with recall to retrieve later, forget to delete.

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• time-and-a-half-calculator

  Microapp

  Compute the time-and-a-half overtime rate (hourly × 1.5) and gross pay for a week with regular and overtime hours. Follows the US FLSA convention: hours past 40 are paid at 1.5× the base rate.

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• get_session_history

  Nefesh — Real-Time Human State Awareness for AI

  Get state history for a session over time. Returns timestamped datapoints with stress_score, state, and heart_rate for each observation. Includes an overall trend: rising | falling | stable. Use minutes parameter to control the lookback window (default: 5, max: 60). Useful for detecting stress patterns during a conversation. Not a medical device.

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• discover_tools

  Tides

  Find tools by describing the data or task. Use when you need to browse, search, look up, or discover what tools exist for: SEC filings, financials, revenue, profit, FDA drugs, adverse events, FRED economic data, Census demographics, BLS jobs/unemployment/inflation, ATTOM real estate, ClinicalTrials, USPTO patents, weather, news, crypto, stocks. Returns the top-N most relevant tools with names, descriptions, and full input schemas (with curated examples) — each result is ready to call directly, no second schema lookup needed. Call this FIRST when you have many tools available and want to see the option set (not just one answer).

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• resolve_entity

  Tides

  Resolve a user-spoken name to the canonical/official identifiers other tools require as input. Use FIRST when you have a name but need an ID. SUPPORTED TYPES: "company" (returns ticker + 10-digit CIK + company_name from SEC EDGAR + pipeworx://edgar/company/{cik} citation URI; accepts ticker, CIK, or company name as input — auto-disambiguated), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/{rxcui} citation; accepts brand or generic name). Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.

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• resolve_entity

  Noaa Tides

  Resolve a user-spoken name to the canonical/official identifiers other tools require as input. Use FIRST when you have a name but need an ID. SUPPORTED TYPES: "company" (returns ticker + 10-digit CIK + company_name from SEC EDGAR + pipeworx://edgar/company/{cik} citation URI; accepts ticker, CIK, or company name as input — auto-disambiguated), "drug" (returns RxCUI + ingredient + brand from RxNorm + pipeworx://rxnorm/{rxcui} citation; accepts brand or generic name). Each call cascades through several lookup endpoints internally — using resolve_entity replaces 2-3 manual lookups.

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• entity_profile

  Noaa Tides

  Get everything about a US public company in one call. Use when a user asks "tell me about X", "research Acme", "brief me on Tesla", or you'd otherwise call 10+ pack tools across SEC EDGAR, XBRL, USPTO, news, GLEIF. Returns: cik + company_name; recent_filings (up to 5 with pipeworx://edgar/company/{cik}/filings/{accession} URIs); fundamentals (LATEST 10-K Revenues + NetIncomeLoss + Cash, sorted period_end DESC — Run 6 fix landed real FY2025 numbers, not stale FY2022); patents (USPTO PatentsView API was sunset May 2025; pack soft-fails until reactivated); recent news mentions via GDELT→GNews fallback; LEI via GLEIF. Pass ticker "AAPL" or zero-padded CIK "0000320193" — names not supported (use resolve_entity first).

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• polymarket_edges

  Noaa Tides

  Scan top Polymarket markets and return opportunities where Pipeworx data disagrees with market price. Built for "what should I bet on today" — agents discover opportunities without paging hundreds of markets. FIVE MODEL FAMILIES grouped into three response segments under by_segment: (1) MODEL_DRIVEN — crypto_price (lognormal barrier from 90d FRED log-returns) and news_momentum (GDELT 7d/21d article-volume ratio, soft signal w/ halved Kelly). (2) STRUCTURAL_ARBITRAGE — partition_overround on mutually-exclusive events; per-leg favorite-longshot bias correction with per-sport α (tennis 1.02, soccer 1.10, MMA 1.15, default 1.0); placeholder-slug filter drops will-person-X / will-team-Y / will-manager-Z / will-someone-else- backstops; partitions with >20% placeholder fraction skipped entirely. (3) CONCENTRATED_LONGSHOT — basket trade when one leg ≥85% AND ≥2 longshots ≤5% AND portfolio return ≥50:1; rare-by-design. EVERY OPPORTUNITY carries edge_pp_net (after slippage), kelly_fraction + kelly_fraction_half (capped at 0.25), market.liquidity, market.spread_pp, market.volume. TRADEABLE-EDGE KNOBS: min_liquidity / max_spread_pp drop opportunities where edge isn't realizable; min_partition_leg_kelly filters partitions by best per-leg Kelly. Cached 1h at the KV level keyed on all knobs. fed_rate bets are scanned but EXCLUDED from ranking (1m-T vs EFFR signal is unreliable at meeting-month horizons without paid OIS/SOFR-futures data); see fed_rate_context for raw spread.

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• scan_competitor_ai_presence

  Tides

  Compare AI visibility across multiple entities side-by-side. Probes each entity (your brand + N competitors) with ai_visibility_check, ranks by score, surfaces which is most/least recognized. Useful for competitive AI-marketing audits: "does Claude know about us as well as our competitors?". Returns ranked list with score, confidence, signal density per entity.

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