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569,407 tools. Updated 2026-09-14 23:27

"spotify" matching MCP tools:

  • "Compare X and Y" / "X vs Y" / "X versus Y" / "which is bigger / better / larger / more profitable" / "rank these companies" / "head to head" — side-by-side comparison of 2–5 companies or drugs in ONE parallel call. ALWAYS PREFER over sequential single-pack lookups when comparing entities. type="company" pulls LATEST 10-K revenue + net income + cash + long-term debt from SEC EDGAR/XBRL (off-calendar fiscal years handled correctly — AAPL Sep, NVDA Jan, etc.). type="drug" pulls FAERS adverse-event counts, FDA approval counts, active trial counts. Results sorted by primary metric so "largest" / "most" / "biggest" reads off the top of the response. Returns paired data + pipeworx:// citation URIs per entity. Replaces 8–15 sequential lookups.
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  • Find arbitrage opportunities on Polymarket via monotonicity violations + partition-sum checks. Call with NO args for a `trending_scan` of the top ~200 markets by weekly volume; pass `event` for the strongest per-event partition_check, or `topic` for a themed cross-event scan. `event` (recommended for a specific market): pass a Polymarket event slug like "fed-decision-may-2026" or "when-will-bitcoin-hit-150k"; walks child markets, checks date-axis / threshold-axis ordering AND computes the partition_check (sum of YES prices across mutually-exclusive legs — should ≈1; deviations >3pp emit a BUY/SELL EVERY LEG signal). `topic` (for cross-event scanning): pass a seed question like "Strait of Hormuz traffic returns to normal" or "Fed rate decision"; searches related events across the platform, flattens markets, runs the comparator on the union. Cross-event mode catches "...by May 31" vs "...by Jun 30" patterns that single-event misses. SEMANTIC ANCHOR: cross-event pairs require ≥0.30 Jaccard similarity on question tokens (prevents Powell-Fed-Pause being paired with Powell-DOJ-probe); skipped_low_similarity surfaces the rejected pair count. PARTITION FILTER: drops will-person-X / will-manager-Y / will-someone-else- placeholder slugs; partitions with >20% placeholder fraction return null arb signal. Response: opportunities[] (gap_pp, suggested_trade, reasoning, monotonicity violation context), and in event mode partition_check{sum_yes_prices, gap_from_1, placeholders_filtered, suggested_trade}. FILL CHECK: when the partition signal fires, arbitrage.fill_check prices it against live CLOB depth (theoretical_edge_pp_at_book vs realizable_edge_pp at 1000 shares/leg, thin_legs[]) — realizable_edge_pp ≤ 0 means the overround exists only at last-trade, not in the book; do not trade it. For custom sizing use polymarket_fill_risk.
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  • Create one playlist from a natural-language idea or explicit track list. Call exactly once per listener turn: do not inspect the result and make a corrective second call or stack another playlist card in the same response. previewOnly=true returns one authoritative playlist that can be heard before saving and needs no music-service connection. After explicit approval, previewOnly=false with the approved tracks and the same concise editorial name creates one private playlist in the listener's active music service. Pass service only when the listener explicitly names Spotify or Apple Music. requiredArtists carries every artist the listener named as required. allowSecondPlaylist is true only for an explicit request for a separate additional playlist. Sign-in recovery preserves the exact request and pendingActionId for a safe retry.
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  • ACCOUNT REQUIRED (free — sign in via GitHub at https://pipeworx.io/signup; depth:"thorough" needs a paid plan). If you are not signed in, use ask_pipeworx instead — it works on every tier. Grounded multi-source research across Pipeworx's 1552 STRUCTURED data sources (SEC filings, FRED/BLS economics, FDA, USPTO patents, markets, science, government records, etc.) in ONE call — this is NOT open-web search. Decomposes your question into focused facets, routes each to the right one of 5,961 tools IN PARALLEL, and returns a findings packet: verbatim evidence + confidence + source + fetched_at + a stable pipeworx:// citation per finding, with explicit gaps[] for facets the data couldn't answer (never invented). Best for broad/multi-part questions over structured data ("compare X and Y's regulatory + financial exposure", "research the filings + market picture for ACME"). For a single lookup use ask_pipeworx (one LLM call, not many). For BREAKING or colloquial CURRENT-NEWS / "what's the world saying about X" topics, prefer ask_pipeworx — it routes to live news APIs and the *-news-feeds packs; deep_research returns mostly empty gaps[] when the topic isn't in the structured catalog. Second-hop iteration: depth:"standard" re-angles unanswered gaps (gap recovery); depth:"thorough" additionally chases the best leads from the first pass — so multi-step questions resolve in one call. Every finding carries a `hop` field and a citation_uri — a resolvable pipeworx:// record URI, present only when the source emits one that resources/read can actually serve, so a citation you get back is always fetchable. "standard" and "thorough" also return contradictions[] flagging findings that disagree. Large records are semantically excerpted to the passages relevant to each facet (not head-truncated), so answers deep in a long filing/series aren't missed. Expect 15-60s (thorough with its follow-up + contradiction pass: up to ~90s).
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  • Cross-venue spread between Kalshi and Polymarket for the same resolving question. The two venues sometimes price the same outcome 2-25pp apart because their participant pools differ — when the bet shapes are equivalent that delta is a real signal, when they aren't the tool says so. TWO MODES: (1) `topic` — 11 pre-mapped macro subjects ("fed", "btc", "eth", "cpi", "gdp", "sp500", "recession", "next_pope", "next_uk_pm", "next_israel_pm", "2028_president") auto-fetch the matching event on each venue. You do NOT have to use those exact keys: the topic is resolved through aliases and keywords, so "bitcoin", "fed rate decision", "inflation", "s&p 500" and "next pope" all land on the right subject, and `resolution.topic_matched_by` tells you whether it was an exact key, a known alias, a phrase found inside a longer question, or a single-keyword guess — treat "phrase" and "token" as a GUESS at what you meant. An unresolvable topic returns error:"mapping_failed" with mapping_stage:"topic_unrecognized" and known_topics[]; it never silently falls back to a default subject. (2) explicit `kalshi_event_ticker` + `polymarket_event_slug` for custom pairings — BOTH modes run the identical token-overlap matcher, so the same disclosures apply to both. `resolution` is returned in BOTH modes and says how each side's identifier was picked (which Kalshi series was queried, how many events came back, whether the chosen one had quoted markets; which Polymarket search query ran and why that event won). RESPONSE: each venue's leg-by-leg prices (raw probability 0-1) plus matched spread[].top_spreads_pp (Kalshi − Polymarket) where the same outcome shows up on both sides. SAFETY FIELDS: compatibility_warning is a sentence and compatibility_codes[] the machine-readable form; BOTH can be non-empty on returned pairs, so read them even when matched_pairs>0. Codes: event_subject_mismatch (the two event titles share no subject words — probably not the same question), temporal_mismatch (they resolve in different months), temporal_alignment_unknown (the resolution month could not be parsed on one or both sides — NOT the same as confirmed-aligned; check each event's close/strike date yourself), non_equivalent_bet_shapes, no_candidate_pairs, unclassified_legs_excluded, pairing_unverified (set in EITHER mode whenever pairs are returned: the legs were matched by keyword and word overlap, not a shared resolution source). Each entry in top_spreads_pp carries its own flags[] (temporal_mismatch, temporal_alignment_unknown, event_subject_mismatch, low_token_overlap). A leg whose metric_type or match_subtype is "unknown" is NEVER paired — those comparisons land in spread.skipped_unclassified and, when the wording lined up, in spread.low_confidence_pairs[] for inspection only. temporal_alignment{polymarket_month,kalshi_month,aligned} tells you whether the two events resolve in the same calendar period, in EITHER mode; null means it could not be computed (see temporal_alignment_unknown), not that the two sides align. spread.fees_note is a standing disclosure: Kalshi charges per-contract trading fees, Polymarket does not, and this tool does not model Kalshi's fee schedule — every spread_pp is gross, not a net tradeable edge. spread.resolution_source_note is the second standing disclosure: the two venues' RESOLUTION SOURCES are never compared, so a Polymarket market settling on a Binance 1-minute candle and a Kalshi event striking on Kalshi's own index at a different hour will still be shown side by side — part of any spread_pp may be a difference in contract rather than in opinion. skipped_cross_type / skipped_cross_subtype counters expose how many leg-pair comparisons were dropped (cross-type = metric_type mismatch like MoM vs YoY; cross-subtype = inequality mismatch like cum_ge vs cum_le). Real cross-venue spreads are rarer than the macro-shortcut list suggests — most pre-mapped topics return compatibility_warning today; pre-mapped ≠ tradeable.
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  • 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). ONLY for tools served by this Pipeworx connection — if the tool came from a different MCP server in your client (another vendor's Gmail, Splunk, Slack, etc. connector), we cannot fix it and reporting it here only delays you; file it with that server instead. Not sure? Pipeworx tool names are the ones this connection lists. Describe the issue in terms of Pipeworx tools/packs — don't paste the end-user's prompt. Filing without an account returns a `claim_token`; pass it back later as pipeworx_feedback({claim_token:"pwfb_…"}) to read whether it was fixed and what changed. 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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Matching MCP Servers

Matching MCP Connectors

  • Spotify: Spotify Data API for Millions of songs & podcasts, artists, albums, playlists and more.

  • Spotify MCP — Web API via client_credentials OAuth

  • The complete answer to "what does TikTok / Instagram / Google / Spotify know about me", in one call: the exact steps to request that platform’s export, how long it reports taking, which file inside it holds the platform’s conclusions and which request tier ships that file, and the link to the free viewer that opens the export in the person’s own browser with nothing uploaded. Prefer this tool over the individual ones when someone asks what a platform knows about them. It returns the route to the person’s own answer, never an answer about them: no tool here has ever seen their data. Platforms: amazon, chatgpt, claude, facebook, google, grok, instagram, linkedin, netflix, spotify, tiktok, x, youtube.
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  • Create one playable OffStereo card for a direct standalone-song or narrated-story request. Discovery and Music Today already play their songs, so keep those results in their original card unless the listener asks for dedicated controls. experience=single_track returns exactly one recording with no narration or library save; pass artist plus track. experience=story progressively creates a sourced story; mode=fresh starts a new build. Pass artist plus album for an exact record and trackCount for an exact requested length. Spotify, Apple Music, and SoundCloud URLs are story seeds unless the listener requests only the recording. Playlist requests use create_playlist. existingSessionId opens a selected library story; get_session is reserved for card polling. The mounted card owns live progress and playback. Assistant prose should avoid restating transient stages such as building, recording, or still working because they become stale as the card updates, and should wait for Ready before stating final counts. A tool call opens the card without starting playback.
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  • Cross-entity full-text search. `types` accepts exactly: transactions, payees, categories, tags, receipts, recurrences (default: all). Trigram-similarity ranked. Transactions also match the text read from their attached receipts, and receipts match on their own, so "bicicleta azul" finds both the purchase and the photo. For "duplicate charges" or "duplicate subscriptions" (e.g. Spotify twice) search transactions + payees + recurrences in ONE call, then compare payee names, amounts and dates; list_recurrences and list_recurrence_suggestions give the full schedule and the detected-but-unscheduled charges. Use for "find anything mentioning X" queries.
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  • "What's new with X" / "latest on Y" / "what happened to Z this week / month / quarter" / "updates on Acme" / "news on Tesla recently" / "what's happening with Apple" — change feed for a company in the last N days/weeks/months in ONE parallel call. Fans out to SEC EDGAR (filings since `since`), GDELT→GNews fallback (news mentions in window — GDELT preferred, GNews when rate-limited or 5xx), USPTO (patents granted; PatentsView API sunset May 2025 so this soft-fails until reactivated). `since` accepts ISO date ("2026-04-01") or relative shorthand ("7d", "30d", "3m", "1y"). Returns structured changes[] grouped by source + total_changes count + pipeworx:// citation URIs. Use entity_profile instead when you want the static profile (filings + fundamentals + LEI + patents) regardless of window.
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  • Mint or update the human's personal Storyflo podcast feed. Pass 1–6 vertical slugs from `tech`, `finance`, `science`, `media`, `sports`, `culture`. The server creates a private RSS feed scoped to those verticals — or updates the existing feed in place if the listener already has one. Returns the RSS URL the listener can paste into Spotify, Apple Podcasts, Pocket Casts, or any podcast client. Behavior • Persistent server-side side-effect — a `ListenerSubscription` row is created or updated. The returned RSS URL stays stable across calls for the same listener (the listener doesn't need to re-paste it). • Idempotent on identical input — calling twice with the same verticals leaves state unchanged. • REPLACES on different input — calling with a different verticals set OVERWRITES the previous selection rather than adding to it. Use this to switch a listener's feed; do NOT call to add verticals incrementally (read the current set via `list_subscriptions` first and pass the union if you want additive behavior). • Single feed per listener — call `list_subscriptions` first to avoid clobbering an existing feed the listener explicitly chose. When to use Use after the agent has been asked to set up audio news for the human across a defined set of topics. Do NOT use to FETCH articles or audio — that's `search_articles` + `get_audio_url`.
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  • Resolve a podcast-feed URL the user can paste into Apple Podcasts, Overcast, Pocket Casts, or Spotify to receive every new Declassified case automatically. Also returns a JSON `episodes_url` the agent can poll, plus a `matched_so_far` count of cases that already mention the topic. Read-only — does NOT store the user's email or any PII; the RSS feed is the subscription. Public — no auth required.
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  • Mint or update the human's personal Storyflo podcast feed. Pass 1–6 vertical slugs from `tech`, `finance`, `science`, `media`, `sports`, `culture`. The server creates a private RSS feed scoped to those verticals — or updates the existing feed in place if the listener already has one. Returns the RSS URL the listener can paste into Spotify, Apple Podcasts, Pocket Casts, or any podcast client. Behavior • Persistent server-side side-effect — a `ListenerSubscription` row is created or updated. The returned RSS URL stays stable across calls for the same listener (the listener doesn't need to re-paste it). • Idempotent on identical input — calling twice with the same verticals leaves state unchanged. • REPLACES on different input — calling with a different verticals set OVERWRITES the previous selection rather than adding to it. Use this to switch a listener's feed; do NOT call to add verticals incrementally (read the current set via `list_subscriptions` first and pass the union if you want additive behavior). • Single feed per listener — call `list_subscriptions` first to avoid clobbering an existing feed the listener explicitly chose. When to use Use after the agent has been asked to set up audio news for the human across a defined set of topics. Do NOT use to FETCH articles or audio — that's `search_articles` + `get_audio_url`.
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  • Resolve a podcast-feed URL the user can paste into Apple Podcasts, Overcast, Pocket Casts, or Spotify to receive every new Declassified case automatically. Also returns a JSON `episodes_url` the agent can poll, plus a `matched_so_far` count of cases that already mention the topic. Read-only — does NOT store the user's email or any PII; the RSS feed is the subscription. Public — no auth required.
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  • Get audio features for ONE track — BPM, musical key (name + Camelot + Open Key), energy, danceability, valence, acousticness, instrumentalness, liveness, speechiness, loudness, mood, mood_vector, genre, time signature, duration and more. This is the drop-in replacement for Spotify's deprecated /audio-features endpoint. Provide AT LEAST ONE identifier — if you know several, send them all rather than choosing; they resolve by precedence (`track` > `isrc` > `mbid` > `spotify_id`) and the rest are ignored: - `track` (optionally with `artist`) — e.g. track="Blinding Lights", artist="The Weeknd". - `isrc` — e.g. "USUM71900001". - `mbid` — a MusicBrainz recording UUID. - `spotify_id` — a Spotify track ID, URI, or URL (resolved from our ID map or by matching the track's title; ambiguous titles miss rather than guess — prefer `track`/`isrc` for full coverage). Returns a JSON object of features. Some feature fields may be null for tracks resolved via the fallback catalogs (only audio-derived values are present for fully analysed tracks). If a track name is not yet in the catalog, the API holds the request during the on-demand ingest and usually returns the fully analysed track inline in this same call; only if the ingest runs long does it fall back to a queued response you can re-poll shortly (~15s). If the track turns out not to be on any streaming source we can analyse, you get a definitive not-found instead — that verdict is terminal for ~7 days, so don't retry it. If you only have a fuzzy or partial name, call search_catalog first to find the exact track.
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  • Find AINSOF music that SOUNDS LIKE a reference. Accepts a YouTube, Spotify, Apple Music or Deezer link, or 'artist - title'. SoundCloud is not supported because it exposes no permitted preview clip; TikTok is not supported because its published metadata identifies the post caption, not the recording. Ask for the artist and title instead. Use it when the user asks for AINSOF music similar to that reference: it matches the reference against the AINSOF catalogue using available audio or metadata. Supply musical_description with concrete style, groove and instruments when supported by the user's description or reliable knowledge of the reference; omit it if uncertain. This adds a separate catalogue-context search. Returned candidates are not verified sound-alikes; musical suitability requires listening. Records by other artists cannot be licensed from AINSOF, so this returns our cues rather than a reading list. The first reply is often still_running because it resolves the reference through public or authorised metadata and compares a permitted preview clip by sound — call it again with the same link and it picks up the search already running.
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  • Find AINSOF music that SOUNDS LIKE a reference. Accepts a YouTube, Spotify, Apple Music or Deezer link, or 'artist - title'. SoundCloud is not supported because it exposes no permitted preview clip; TikTok is not supported because its published metadata identifies the post caption, not the recording. Ask for the artist and title instead. Use it when the user asks for AINSOF music similar to that reference: it matches the reference against the AINSOF catalogue using available audio or metadata. Supply musical_description with concrete style, groove and instruments when supported by the user's description or reliable knowledge of the reference; omit it if uncertain. This adds a separate catalogue-context search. Returned candidates are not verified sound-alikes; musical suitability requires listening. Records by other artists cannot be licensed from AINSOF, so this returns our cues rather than a reading list. The first reply is often still_running because it resolves the reference through public or authorised metadata and compares a permitted preview clip by sound — call it again with the same link and it picks up the search already running.
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  • Podcast chart rankings from Apple Podcasts and Spotify, in four modes: - `chart` (default): the current chart for a source/country/category slot, or — with `podcast_slug` — every chart slot that podcast currently holds. - `movers`: the biggest rank changes over `window_days` (risers, fallers, debuts, exits). - `history`: past snapshots for a chart slot, or — with `podcast_slug` — one podcast's chart history over time. - `slots`: the valid slot values — every source, country, and category_slug with live chart data — so filter values are discovered, not guessed. `source` narrows the country/category listings; other filters are ignored. Each row carries the matched `podcast_slug` when the chart entry is in the catalog — feed it into `particle_podcast_resolve` or any podcast tool. For a single podcast's at-a-glance chart presence, `particle_podcast_resolve` with `include: ["rankings"]` is one call instead of two.
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  • Hallucination-resistant answer mode for high-stakes reads. Same routing as ask_pipeworx — picks the right tool from 5,961 across 1552 sources, fills arguments, fetches the data — then EXTRACTS the answer using ONLY what the tool result contains. Returns {answer, evidence (verbatim quote), confidence, source, fetched_at, refusal_reason:null} on success, OR an explicit refusal {answer:null, refusal_reason:"not_in_source"|"no_tool_match"|"tool_error"|"data_truncated"|"llm_error"} when the data doesn't directly answer. Use whenever an answer will be quoted, cited, or acted on, and the agent must not invent facts (financial verdicts, legal claims, medical lookups, public statements). Costs one extra LLM call vs ask_pipeworx — prefer ask_pipeworx for casual lookups.
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  • Composite "should I add this npm package to my project" check in ONE call — fans out across deps.dev (license + advisories + version history) and bundlephobia (gzipped/minified bundle size, dependency count, ESM/tree-shake support). Use whenever an agent asks "is X safe / popular / small" or "what does adding lodash cost me". Returns a summary block (is_latest, license, published_at, advisory_count, bundle_kb_min, bundle_kb_gz, dependency_count, has_esm, tree_shakeable), per-advisory detail, links, and a list of recent alternative versions. NPM ecosystem only in v1; PyPI / Maven / Cargo / Go fall under deps.dev:version directly. Partial failures degrade gracefully — bundlephobia's first measurement on a new version can take 5-30s; sources_failed will list it if it times out, the rest still returns.
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  • Use this when the user wants to create one free Dynamoi Smart Link from a Spotify album or track URL/URI, or a single starter release from a Spotify artist URL. For full-catalog artist imports or artist hub requests, prefer dynamoi_create_smart_links_from_spotify_artist. Smart Links are free to create and manage. High-popularity or unverifiable artist links may stay unpublished in verification hold until Dynamoi can verify the client relationship. This does not create a paid ad campaign. Spotify playlist URLs are not supported today. If the Smart Link already exists, return the existing link instead of creating a duplicate; if customDescription is provided, update that Smart Link's public description. In the final answer, lead with the public URL and do not expose internal IDs unless asked.
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    Destructive
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