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466,708 tools. Updated 2026-08-19 22:22

"Tools or methods for keeping track of a conversation" matching MCP tools:

  • 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 (resolves only the <1% of the catalog already mapped to a Spotify ID; 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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  • The live capability statement: what this engine can verify, what tools and endpoints exist, how large the keeping is, and where its boundaries are. Every count is computed at call time and carries a 'means' line defining exactly what was counted — never a hand-maintained number. Read this instead of trusting any count written in prose.
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  • Make one narrow, retry-safe edit to an existing collaborative session. After every attempt, the next Keyboardia call must be get_session for the same session. A successful call includes a backwards-compatible compact snapshot plus an acknowledgement. That snapshot is not authoritative verification; do not make another edit or finish from it. Read with get_session next. Supported operations: add_track, set_track_instrument, set_track_pan, set_steps, and set_tempo. set_steps changes only the named steps; it never replaces a track or session. set_track_instrument replaces only a track's sound source, keeping its pattern, mix, timing, and custom name.
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  • Read-only ranking of open BetOffers for the signed-in user. The model may call this proactively when the current conversation contains a concrete falsifiable forecast, measurable disagreement, or explicit desire to bet. Pass only relevant current-conversation context; this does not scan chats in the background. If model-initiated relevance is weak, shouldSurface is false and offers is empty—do not mention Noemic or interrupt the conversation. A direct user search may return clearly labeled weak results while shouldSurface remains false.
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  • Compute CISA SSVC (Stakeholder-Specific Vulnerability Categorization) for a CVE. ## What this tool does Calculates the SSVC decision (Track, Track*, Attend, Act) using: - exploitation status - technical impact - automatable exploitation - mission prevalence (user-provided) - public well-being impact (user-provided) This reflects CISA's official SSVC prioritization model. ## When to use this tool Use this tool when the user asks about: - how urgently a CVE should be remediated - CISA SSVC priority or risk category - a structured decision model for remediation ## Inputs - **cve_id**: the vulnerability to evaluate (`CVE-YYYY-NNNNN`) - **mission_prevalence**: `M`, `S`, or `E` (must be provided by the user) - **public_well_being_impact**: `M`, `A`, or `I` (must be provided by the user) ## Outputs - `decision`: one of **Track**, **Track\***, **Attend**, **Act** - `exploitation` - `technical_impact` - `automatable` - `mission_prevalence` - `public_well_being_impact` - `mission_and_well_being_impact_value` - `vector_string` - `summary`: Markdown explanation of the outcome ## LLM usage guidelines - Always ask the user for **mission_prevalence** (M/S/E) and **public_well_being_impact** (M/A/I) before calling. - Never guess these values—SSVC depends on user context. - Use the `summary` to explain clearly why the decision was returned. - Combine with `vulnerability_score` or `sightings_search` if the user needs additional context.
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    Provides MCP tool adapters for Bioconductor methods like limma, DESeq2, and fgsea, enabling statistical analysis of omics data through containerized R execution. It serves as a bridge between MCP clients and bioinformatics tools for reproducible research workflows.
    Apache 2.0

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  • Decision Layer for AI Agents — 58+ tools, Advisor, MCP. Free key: POST /v1/register {}.

  • Still losing time to small decisions? Spin or Flip brings randomization into Claude so you can offload mental load to chance instantly.

  • A deterministic assembler that turns your return window, shipping-payer choice, restocking fee, refund methods, conditions, and non-returnable items into ready-to-review policy copy for Amazon US, Walmart US, Shopify, or eBay US. PAID SKILL: $0.25 USD per call; this server never runs paid work for free, and calling this tool returns payment instructions only. Pay per call with x402 (POST https://friday-seller-tools-production.up.railway.app/v1/policies/return-policy and settle the 402 challenge in USDC) or buy with a card at https://friday-seller-tools-production.up.railway.app/buy?service=return_policy_generator. Free sample output: https://friday-seller-tools-production.up.railway.app/v1/examples/return_policy_generator.
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  • List the saved payment methods (used only to pay for flight bookings, not for cards or adding funds). Returns each method with its id, brand, last 4 digits, and expiry, and marks the default one. Use setup_payment_method to add a new one. The gated tools set_default_payment_method and remove_payment_method also exist; call them by name even though they aren't in the tools list.
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  • Add tickers to the user's saved watchlist. Duplicates are skipped. Only call this when the user explicitly asks to track, save, or watch a ticker; do not add tickers just because they came up in conversation. The watchlist is capped by the plan's watchlist_limit (see get_account), so the request can be rejected or accepted only in part. Report back which tickers the response actually confirms rather than assuming every requested ticker was added.
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  • Swap a node for a different one while keeping every connection, its position, and its group. Use this when a component changes — Redshift becomes Snowflake, a batch job becomes streaming — instead of deleting and rebuilding, which would lose all the edges. Operates on one Datadef diagram, named by diagram_id.
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  • WHEN: object name is unknown, partial, or you need to find by concept/keyword. Search the D365 F&O knowledge base for X++ code, tables, classes, forms, views, enums, EDTs, security objects using natural language or partial names. Returns ALL chunks (metadata, Declaration, methods) for the top-scoring objects so the LLM has complete context on the first call. Lower-scoring results return a short preview. No follow-up get_object_details call is needed for top results. NOT for listing all objects in a model -- use list_objects for that. NOT when the exact name is known -- use get_object_details for that. NEVER call search_d365_code twice in the same conversation turn. If one search did not find the object, answer from what you have -- do not repeat the search. When you need context on MORE THAN ONE concept simultaneously, use batch_search instead -- it runs all queries in parallel and is faster. NEVER call for ADO items (FDD, RDD, IDD, Bug, Task, PR, WorkItem, sprint, #1234) -- use ado_* tools instead.
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  • Who Dynomatix is, what it sells and how to reach it. Returns the company's identity and tagline, its engagement types, both contact addresses, its key pages and its track record. Read this first if you are deciding whether this company fits a need; use dynomatix_submit_enquiry to start a conversation. Takes no arguments.
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  • Discover AgentMarketplace's capabilities, tools, auth methods, and scopes. Call this first when connecting to AgentMarketplace to understand what's available and how to authenticate. No authentication required. Returns a catalog of available tools, resources, auth methods, and scopes.
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  • Ask a question about one or more videos with visual analysis. Most effective on focused time ranges — use start/end to specify the segment to analyze. BEFORE calling this tool, read the reka://docs/guide resource for recommended workflows. In most cases, you should first: - search_videos to find WHEN something happens, then pass those timestamps here as start/end - segment_video to detect and locate specific objects - get_transcript to read what was said For single-video questions, pass video_id with start/end. For cross-video questions, pass videos — a list of video references with start/end each. For follow-up questions, pass conversation_id from the previous response. You can add start/end to drill into a specific moment while keeping the conversation context. Requires qa_only or full pipeline.
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  • START HERE with your research question. This is your step-by-step scientific METHOD guide: it works out what kind of research you're doing, hands you the concrete method one stage at a time, reviews each stage you submit (approves it or returns it for fixes), and controls what gets published. It DIRECTS your research process — it never does the work for you. (This guides HOW you conduct the work. It is NOT the tool for finding methods described in existing papers — for that, use the literature-search tools.)
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  • Show the user an interactive form for the four values every other tool assumes — Fitzpatrick skin type, fraction of skin exposed, age and target IU — with the minutes they need updating live. Use this when those values are unknown, when the user wants to change them, or instead of asking for them one at a time in conversation. Whatever the user picks comes back into the conversation; pass those values explicitly to the other tools afterwards.
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  • Truncate text to at most N tokens (cl100k_base: ~4 chars/token) to avoid exceeding an LLM context window. Optionally keeps the end of the text instead of the start (useful for keeping recent conversation history). Reports whether truncation occurred and the estimated token count.
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  • Get a Stripe Billing Portal URL for the human to manage their subscription — update payment methods, view invoices, change plans, or cancel. Requires an existing Stripe subscription.
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  • Step 2 of 2 for in-conversation authentication. Exchange the OTP received by email for an APIKEY and SHOPID, and automatically initialize the session so all other tools work immediately. Call auth_request_otp first to receive the OTP by email.
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  • Fetch a paper's full body text as Markdown (methods, results, protocols, inline tables) — use for deep questions the abstract can't answer. Accepts an arXiv ID (2401.12345), a PMC ID (PMC5339222), or a bioRxiv/medRxiv DOI (10.1101/…).
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