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470,179 tools. Updated 2026-08-23 06:04

"Information or content related to the show Taskmaster or the term Task Master" matching MCP tools:

  • Read-only availability and pricing lookup for domain names. No purchase or order is created by this tool; it only returns information. Preferred input: `domains`, 1 to 200 fully-qualified names (e.g. ['acme.com', 'acme.io']); results cover exactly those domains, with no suggestions or expansion. Fallback input: `query`, free text (one or more names, comma- or space-separated); names given without a TLD are expanded to popular TLDs (com/io/ai/co/net). Each result includes whether the domain is available, whether it is a premium name, the registration price and the renewal price. Both prices are totals for one full registration term of that ending, not per-year rates: one year on most endings, but two years on .ai, whose registry mandates a two-year term. Do not divide or multiply a returned price by a number of years. Available non-premium results also carry a `checkout_url` the user can open in a browser to register the domain on justdomain.ai if they choose to. Premium names cannot be registered through Just Domain yet and carry no `checkout_url`.
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  • Search Okun Koneosa's shop policies and terms. Covers delivery terms, privacy policy, terms of service, the consumer right of withdrawal / returns, and company information. Use this instead of guessing when the customer asks about delivery times, shipping costs, returns, warranty or how their data is handled. Args: query: Finnish keyword, e.g. "palautus", "toimitusaika", "takuu", "toimituskulut". Leave empty to list all sections. limit: Maximum sections to return (1-20, default 5). Returns: JSON with: - sections: each with page, page_title, heading, content and url - total: how many sections matched - query: the term that was searched Notes: - Content is split by heading, so you get the relevant paragraph rather than a whole page. Always cite the `url` so the customer can read the full terms. - These are the shop's own terms. They do not override Finnish consumer law.
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  • Look up the 99 Names of Allah (Asma ul Husna). Returns Arabic, transliteration, English and Bengali. Give a number for one name, a search term to match by meaning or transliteration, or neither to get all 99.
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  • Get full specifications, equipment, all images, and pricing per term for a specific vehicle. Use a vehicle_id from search_vehicles results. IMPORTANT: Always show `detail_url` as a clickable link — it points to the FINN configurator where the user picks term and km. To produce a direct checkout link for a specific term + km combination (and optionally a one-time Fahrzeugbereitstellung), call `get_subscription_pricing` and use the `checkout_url` it returns. Never construct checkout URLs yourself. The `vehicle_id` field is an internal API identifier — never display it to users.
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  • Fuzzy text search across route names, descriptions, and category labels. Resolves natural-language queries like "electricity retail sales by state" or "natural gas imports" to matching route paths. Multi-term queries are also matched term by term, so combining a commodity, a metric, and a sector — "electricity price residential", "coal generation industrial sector" — reaches the route carrying that data even when no single entry reads like the whole phrase. STEO series names are indexed so queries like "ethanol net imports" or "crude oil production forecast" also resolve, and so are facet values, so a fuel type or sector term like "wind" or "anthracite coal" resolves to the route that exposes it, with filter_hint carrying the filter to pass on. Results include isLeaf so you know whether to browse further or query directly. Results with score > 0.72 are weak matches — try a more specific query or use eia_browse_routes to explore the taxonomy. The first call after server start waits 24-30s while the index warms, and at most 45s; every later call returns in milliseconds. Check indexComplete before reading anything into a short or empty result set.
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  • Report what this session controls: the master account/subaccount, whether it can trade or is read-only, and the exact on-chain authorization scope (which messages, which subaccount, and that it CANNOT withdraw/transfer). Call this first.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.
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    MIT
  • F
    license
    Not graded
    quality
    B
    maintenance
    MCP server that provides OpenRouter model pricing data, enabling price lookups, trending/cheapest lists, and model searches without an API key.

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

  • the-committee MCP — wraps StupidAPIs (requires X-API-Key)

  • Report what this session controls: the master account/subaccount, whether it can trade or is read-only, and the exact on-chain authorization scope (which messages, which subaccount, and that it CANNOT withdraw/transfer). Call this first.
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  • Retrieve the full content of a specific Costory documentation page by its public docs URL or page path. Use this after search_documentation returns results. Response starts with `Url: https://docs.costory.io/...`. When citing this page in chat, use that exact `Url:` as the markdown href — do not convert to a relative app path. EXAMPLE: "Show me the full page about cost explorer" → { page: "https://docs.costory.io/features/cost-explorer" }
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  • Retrieve proteins annotated with a functional term or descriptive text in a single species. You can query for tissues, compartments, diseases, processes, pathways, and domains. IMPORTANT: For cross-species comparisons, run this tool separately for each species. Select relevant model organisms to search or ask user to provide the selection. The results reflect annotation depth within each category; use caution when interpreting. If no results are found, try simplifying the query. For tissue queries, follow BRENDA tissue nomenclature and omit the word "tissue" (e.g. use "skin" instead of "skin tissue"). Output fields: - category: Source database of the matched functional term (e.g. GO, KEGG, Reactome, Pfam, InterPro). - term: Exact identifier for the functional term. - description: The free text description of the term. - proteinCount: Number of proteins annotated with that term - preferredNames: Full protein-name list when `detail_for_term` is set - stringIds: STRING protein identifiers when returned - preferredNames_omitted: True when a row omits the protein-name list - stringIds_omitted: True when STRING identifiers are omitted
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  • Search scientific literature and read full-text content from peer-reviewed papers. Use `dois` (preferred) or `titles` with targeted `term` queries to extract full-text passages from specific papers. Each call returns up to 5 relevant excerpts (~500 chars each) — vary search terms across calls to read through a paper section by section. **IMPORTANT — keep `limit` small.** Use `limit: 10-50` with `offset` for pagination. Large limits with full citations and excerpts produce very large payloads that consume significant LLM context. **Calling with no parameters browses the corpus** (210M+ papers, relevance-sorted). This is allowed for broad exploration but rarely what you want — pass `term`, `dois`, `titles`, or other filters for targeted results. **What This Tool Returns:** - Paper metadata: title, authors (first 3), abstract, DOI, journal, year, volume, issue, page - `fulltextExcerpts`: up to 5 passages (~500 chars) from the paper matching your query (OA only) - `access`: resolved access link with source, type (open/institutional/purchase), content type, and pricing - `citations`: Smart Citation statements — actual quoted text from citing papers, classified as supporting/contrasting/mentioning/unclassified (unclassified = statement present but classifier hasn't assigned a type) - `tally`: citation metrics (total, supporting, contrasting, mentioning, citing publications) - `editorialNotices`: editorial notices (retraction, correction, concern, erratum), each with status, noticeDoi, date - `isOa`, `oaStatus`, `license`: open access information **Fetching Paper Metadata (no search term needed):** Pass `dois` or `titles` WITHOUT a `term` to retrieve metadata for specific papers. Example: `dois: ["10.1038/s41586-020-2012-7"]` **Full-Text Excerpts:** For OA papers, `fulltextExcerpts` contains passages matching your query. If empty, the full text is not indexed or terms didn't match — use the `access` field for the best link to the PDF or full text. **Smart Citations ARE Full-Text Evidence:** - `snippet`: exact sentence/paragraph from the citing paper's full text - `type`: classification (supporting, contrasting, mentioning, unclassified) - `section`: paper section (Introduction, Methods, Results, Discussion) - `sourceDoi`: paper containing this snippet; `targetDoi`: paper being cited **Search Capabilities:** - Boolean operators: AND, OR, NOT - Phrase search: "exact phrase" - Proximity: "term1 term2"~5 - Field filters: title, abstract, author, journal, year, affiliation - Citation filters: supporting_from/to, contrasting_from/to, mentioning_from/to - Editorial filters: has_retraction, has_concern, has_correction, has_erratum **Parameters:** - `term`: cross-field search query (optional when `dois`/`titles` provided) - `dois`: array of DOIs to filter to specific papers - `titles`: array of titles to filter (use when DOIs unavailable) - `limit`: max results (default: 10, max: 1000) - `offset`: pagination offset - Plus 20+ filter parameters (see schema) **Response Format:** ```json { "hits": [{ "doi": "10.1234/example", "title": "Paper Title", "authors": [{"authorName": "Jane Smith"}], "abstract": "Full abstract text...", "year": 2023, "journal": "Nature", "tally": {"supporting": 32, "contrasting": 8, "mentioning": 5}, "fulltextExcerpts": ["Relevant passage..."], "access": {"url": "https://...", "accessType": "open", "contentType": "pdf"}, "citations": [{"snippet": "These findings...", "type": "supporting", "section": "Results"}], "editorialNotices": [{"status": "retracted", "noticeDoi": "10.1234/notice", "date": "2021"}] }] } ```
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  • Find similar or competitor websites based on classification. Takes a URL, classifies it (or uses cached classification), and returns other websites from the same category and subcategory. Useful for competitive analysis and discovering related content. Rate limited to 1 request per minute per domain. Args: url: The website URL to find similar sites for. limit: Maximum number of similar sites to return (1-50, default 10). Returns: Dictionary with: - url: The input URL (normalized) - classification: The URL's category and subcategory - similar_sites: List of similar URLs from the same category - total_in_category: Total sites in this category/subcategory - cached: Whether the classification was from cache
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  • Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Each result includes the collection's raw cover `image` — the URL the publisher set, or null if they set none (the app may still show an auto-generated cover when null). This is the stored value, not the computed display image. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.
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  • Browse published Bible verse collections. Search by keyword, filter by language, sort by popularity. Each result includes the collection's raw cover `image` — the URL the publisher set, or null if they set none (the app may still show an auto-generated cover when null). This is the stored value, not the computed display image. Args: search: Search term to filter by name, description, or publisher name. language: Language code prefix (e.g. "en", "de", "ja", "zh"). ordering: Sort order: -downloads (default), -created, name. limit: Number of results (1-100, default 20). offset: Starting position for pagination.
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  • Publish a task to make it visible to operators. Works for both settlementMode='escrow' and 'direct' tasks. The task must be in Draft or Funded status. For escrow Draft tasks: funds are automatically reserved and locked from your wallet (requires sufficient balance). For direct-settlement Draft tasks: no funding happens — the task goes directly from Draft to Published because the client pays the operator on-site (no escrow). This is the intended shortcut for direct-settlement. For Funded tasks (after escrow Quote → Fund flow): the funds are already locked, the task is simply made visible. After publishing, operators can accept the task. Requires authentication. Next: wait for task.accepted via get_task_events or webhook.
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  • Choose whether this board is a freeform whiteboard ('draw', the default) or a kanban task board ('todo'). Mode is switchable WHENEVER the board is empty of real content: drawings (text/strokes/images) and tasks. Empty or seeded columns DON'T count (switching to 'draw' clears them), so a cleared board can be switched again, and you can flip draw<->todo freely until the first stroke/text/image or task lands. Setting 'todo' auto-seeds three starter columns (To do / In progress / Done). Returns `{ mode, columns }`. Use the task/column tools (`create_task`, `create_column`, …) once the board is in 'todo' mode.
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  • Fetch a webpage and extract specific information using AI. Use this when you need structured data from a page (e.g. pricing, specs, contact info) rather than the raw content. Costs 5 credits. If the page has no usable text (empty or JavaScript-rendered body), the model is NOT called: content comes back empty and usage.low_content is true, rather than a fabricated answer. Gate on usage.low_content (or usage.content_chars) to detect pages you cannot ground on. Returns: content (the extracted text), url, credits_used, credits_remaining, usage (input_tokens, output_tokens, content_chars, low_content). Args: url: The URL to extract from prompt: What information to extract (e.g. "list all pricing tiers with features" or "extract the author name and publication date")
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  • Get the full details of a single Todoist task / to-do item by its id, including content, description, project id, section id, priority, due date/datetime, labels, web URL, and creation time. Use after todoist_list_tasks to inspect one task.
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  • Keywords observed in Amazon's own autocomplete suggestions for a seed term, per marketplace: the current suggestion list(s) for the seed's prefix (each term with its position 1-10 within that list) plus related observed vocabulary starting with the seed, with the marketplaces each term was observed in. Use for listing/backend keyword language, 'what do buyers type for X', or seeding niche/product research with real buyer phrases. No volume figures and no organic-ranking data — observed suggestion vocabulary only. Amazon marketplaces only.
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  • Cancel a task you posted. Only legal before bidding/assignment closes it out. Args: access_token: AgentAuth bearer token (requires ``market.post``). task_id: UUID of the task to cancel. Returns: The cancelled task on success. ``{"error_code": "not_found", ...}`` if the task doesn't exist, ``{"error_code": "authorization_failed", ...}`` if you're not the poster, or ``{"error_code": "invalid_input", ...}`` if the task is already past the cancellable stage.
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  • Bid on an open task. Args: access_token: AgentAuth bearer token (requires ``market.bid``). task_id: UUID of the task to bid on. proposed_cost_units: Your price, as an **integer** amount_units. Never a float or Decimal — money is integer units end to end. estimated_duration_seconds: How long you expect the work to take. proposed_approach: Free-text summary of how you'll do the work. terms: Optional JSONB — anything else worth stating up front. confidence_score: Your self-assessed confidence, 0.0-1.0. Returns: The created bid (status ``"pending"``). The task moves to ``"bidding"`` on its first bid. Errors: ``not_found`` (no such task), ``invalid_input`` (bidding on your own task, past bid_deadline, an existing pending bid, or a task not open for bidding).
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