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650,770 tools. Updated 2026-10-14 18:04

"Guide to Executing and Reading Terminal Commands" matching MCP tools:

  • Use only after works_public_eligibility returns eligible. Download that immutable public GitHub snapshot, run the selected pinned static contract without executing repository commands, and return a signed receipt. Return the report field verbatim and stop.
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  • Returns all WSF ferry terminals with their numeric IDs, names, abbreviations, and coordinates. Call this first to resolve human-readable terminal names (e.g. "Bainbridge Island", "Seattle", "Kingston") to the numeric terminal IDs required by the schedule and space tools. The terminal list is small (20 terminals) and rarely changes.
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  • Create new guides Create one or more new guides based on provided queries. Each guide targets exactly ONE engine and ONE analysis mode, chosen with the optional `source` field (default `google`). How to request each guide type: 1. Google SERP guide (1 credit per guide): omit `source`, or pass `source: "google"`. Example payload: {"queries": ["best crm"], "lang": "en-us"} 1bis. Google AI Overview guide (1 credit per guide). Two modes, like AI engines: `source: "google_ai_overview"` builds the guide from the TEXT of Google's AI answers (AI Overview, completed with AI Mode answers) ; `source: "google_ai_overview_citations"` builds it from the content of the web SOURCES those answers cite (recommended for GEO). Same language/country parameters as a Google SERP guide, 1 credit per guide in both modes. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "google_ai_overview_citations"} 2. LLM ANSWER guide (4 credits per guide): pass the engine name alone, e.g. `source: "chatgpt"`. The guide is built from the answer text the AI generates for the query. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt"} 3. LLM CITATIONS guide (4 credits per guide) [RECOMMENDED AI mode]: pass the engine name with the `_citations` suffix, e.g. `source: "chatgpt_citations"`. The guide is built from the content of the web pages the AI cites in its answer. Example payload: {"queries": ["best crm"], "lang": "en-us", "source": "chatgpt_citations"} Which AI mode to pick? For GEO (getting a page visible in AI answers), prefer `<engine>_citations`: AI engines send traffic by CITING pages as sources, so the winning move is to look like the pages they cite. The answer-text mode (`<engine>` alone) is mostly useful to analyze how the AI phrases its own answer. When in doubt, pick `<engine>_citations`. The same two modes exist for every AI engine (chatgpt, perplexity, claude, gemini, grok, mistral, deepseek). To optimize the same page for several engines or modes (e.g. Google AND ChatGPT answers AND ChatGPT sources), create one guide per source value on the same query. IMPORTANT, HOW TO READ THE RESPONSE OF THIS ENDPOINT, WHICH SPENDS CREDITS. Queries listed in `guidesFailed` are PROVEN not to have produced a guide and their credit was given back (unless the account has unlimited credits, where nothing was reserved): re-sending them is free and correct. Queries listed in `guidesUnknown` have an UNDECIDABLE outcome and their credit is deliberately KEPT, because the guide was most likely written: DO NOT re-send them, you would pay for the same guide twice. Look them up in `GET /api/v1/guides` after a few minutes instead, and contact support if nothing shows up. Finally, a `200` is NOT a promise that every query produced a guide: compare `guides.length` with the number of queries you sent, never read `success` alone, and never re-send a query just because it is missing from `guides`.
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  • [PAID $0.01 USDC per call — optional third-party check] Preflight a proposed command or tool call through HumanMirror Safe Preflight (humanmirror.fr, x402-verified seller) before executing it. Returns the independent risk verdict (risk level, findings, required guards) from their circuit engine. Use for genuinely risky external tool calls where a second opinion matters. Benign commands settle $0.01 USDC on Base and return the verdict; commands they judge over-limit are blocked and refunded (no charge). This is an OPTIONAL external check — AgentWorld's own spend-authority, solvency and circuit-breaker layers remain primary and free.
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  • [PAID $0.01 USDC per call — optional third-party check] Preflight a proposed command or tool call through HumanMirror Safe Preflight (humanmirror.fr, x402-verified seller) before executing it. Returns the independent risk verdict (risk level, findings, required guards) from their circuit engine. Use for genuinely risky external tool calls where a second opinion matters. Benign commands settle $0.01 USDC on Base and return the verdict; commands they judge over-limit are blocked and refunded (no charge). This is an OPTIONAL external check — AgentWorld's own spend-authority, solvency and circuit-breaker layers remain primary and free.
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  • Returns real-time drive-up and reservable vehicle space available at WSF terminals for upcoming sailings. Use for "will I make the ferry?" or "how full is the next sailing?" questions. Optionally filter to a specific terminal by ID (use wsdot_get_ferry_terminals for the ID). driveUpSpaceCount is the key field — zero means the drive-up lane is full. Destinations are arrivingTerminalIds, not the itineraryLabel string: a sailing can serve several terminals, and those IDs are what wsdot_get_ferry_schedule accepts. Results are paged by terminal (default 5, max 20): offset/limit select whole terminals and totalCount counts matching terminals, not sailings — every sailing of a returned terminal is included, so page size varies with how many departures each terminal carries.
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Matching MCP Servers

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    Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.
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    An MCP server for tracking and managing AI command usage history using a PostgreSQL database. It enables users to log, search, and view statistics for various AI-related commands and their execution contexts.
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Matching MCP Connectors

  • Search factual investing-book metadata and browse BrinkerAdvisor reading paths.

  • Live geopolitical and markets intelligence wire: 35k+ wire items, event threads, 55k+ articles.

  • Search the free Signal8 Academy (signal8.ai/learn) — plain-English guides that explain dilution (ATMs, warrants, convertibles, baby shelf, cash runway), how to read SEC filings (8-K items, Form 4 codes, 13D/13G, 424B5, S-1/S-3), market structure (halts, short interest, float, reverse splits, STOCK Act disclosures) and how to use Signal8. Returns matching guides with title, description, track, section, reading time, lastVerified date, the public url and the signal8:// resource uri — no bodies; call get_learn_guide for the full Markdown. Keyword match: every query word must appear somewhere in the guide; title hits rank highest. An empty query lists every guide (optionally one track) in reading order. Use this to ground an explanation of a concept the user asked about, or to cite a guide alongside data from the dilution / filing tools. Works without an API key. An empty result means no guide matched the words given — try fewer or broader words (e.g. "warrant" rather than "warrant inducement repricing") — not that the topic is unimportant.
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  • Runs a two-stage discounted cash flow on numbers you provide and returns the fair value per share, the margin of safety against the price you gave, and how much of the value sits in the terminal stage. Cash flow grows at your growth rate for the stage-one years, then forever at your terminal rate, with the terminal value from the Gordon Growth Model discounted back over the stage-one years. Use when the user wants to value a company under their own assumptions, test how sensitive a valuation is to the discount or growth rate, or check the arithmetic of a DCF they are building. Do not use it to look up what a company is worth on Zyberno's own assumptions, which is get_stock_valuation and uses a different, fade-based model; the two will not agree and are not meant to. This computes your assumptions, it does not endorse them. The output is arithmetic, and a two-stage DCF is highly sensitive to the discount and terminal rates, so treat a single result as one point rather than an answer.
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  • New messages, findings and reviews in the rooms you belong to, since your cursor. Reading NEVER advances the cursor — the same window replays until you ack, so crashing between reading and acting costs nothing. Returns an ack_cursor to hand to ack.
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  • Mamanida's editorial buying guides for one storefront, in that storefront's own language. Called without `guide` it lists the published guides (metadata only: title, deck, meta description, pillar, topics, dates and the canonical Mamanida URL), optionally filtered by `topic`. Called with `guide` (the guide slug from the listing) it returns that one localized edition plus its structured body: paragraphs, headings, lists, comparison tables, callouts, links to other guides and category calls-to-action. A `category_cta` gives a `category_slug` you can pass straight to search_products, which is the intended guide → category → product path. Retailer and affiliate URLs are never returned.
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  • Returns CANDIDATE FOUNDATIONAL PAPERS for a research topic — cheap retrieval only, no synthesis. Ranks papers by a blend of citation count (0.6 weight, captures importance) and semantic similarity to your topic (0.4 weight). Use this to bootstrap a literature survey or get a fast sense of the landscape. For a synthesized orientation report (key concepts, open problems, reading order), use the /field-guide skill which calls this tool internally. Does not require a Pro API key — no LLM calls are made.
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  • Import an open-source load test (JMeter .jmx, k6 .js, or Locust .py) into an existing script, converting it to Loadster commands. An import may create script assets, datasets, and a scenario; replace=true also replaces the script's existing commands and variables. Returns action items to review. For OpenAPI/Swagger or Postman, read the spec yourself and build commands with create_script instead.
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  • Opens the run's event stream, collects up to max_events, and returns as soon as the run reaches a terminal event or wait_seconds elapses — whichever comes first. This is how you watch a build without polling. Example: {"run_id": "…", "from_seq": 0, "max_events": 50, "wait_seconds": 5}. Returns {events: [{seq, type, at, stage, message, rows, bytes, failure_code}], next_from_seq, run_status, terminal}. Call it again with from_seq set to next_from_seq to continue. wait_seconds is capped at 20 and max_events at 100; terminal true means the run is finished and there is nothing more to wait for.
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  • Return the user's personalization guide — how they want a person researched before you write to them. Call this only when you are going to personalize a message; follow the returned guide. When none is set, returns a note and you should fall back to the default research rules in the outreach craft skill.
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  • Use this when the task needs a shell command or an existing ReMCP terminal session: start, read, wait, interact, stop, or list sessions. Choose exactly one operation; parameters are validated against that operation’s closed schema. Starting or interacting with commands can change local or external state, and force termination can lose unsaved process work; reading, waiting, and listing do not mutate the session. Use manage_system for OS-wide process inventory or killing an arbitrary PID.
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  • Read the full text of a cooking guide from recipes-daily.com, as markdown. Call this when search_recipes lists a guide that answers the question — how or why something works in the kitchen, how to store or substitute an ingredient, how to use a piece of equipment — and answer from what it says rather than from memory, citing its URL. Pass the guide URL exactly as search_recipes returned it. For recipes, use show_recipes instead: a recipe is a page the person cooks from, not text to retell.
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  • Cancel a run from any non-terminal state before collecting (a collecting run's outputs are delivered and charged: 409). The cancel request is recorded immediately and returns run_id and cancel_requested true; the platform kills the machine and terminalizes the run as state killed on its next orchestration tick (about 60 s). Poll mcg_get_run to observe the terminal state.
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  • Get the guide to authoring a wireframe mockup — the markup dialect, the wireframe component set, what the drawn style discards, and a complete valid example. Call this BEFORE composing your first mockup in a conversation: markup written from general Tailwind and HTML habits is refused, and the guide is what an author needs to write a mockup that is accepted first time.
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  • Preview or save the allowlisted discovery report for one device. Send terminal and saidas (step id to pasted output), initially with conferir:true. Preview returns normalized dados, additional passos and pronto without writing. Omit conferir to save when complete. Only allowlisted facts are saved, never raw commands. First report wins within one hour; identical retries do not rewrite. The discovery never creates a legacy measurement, sends a reading, installs software or creates a schedule. With Accept: text/plain the receipt is only `ok`.
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  • Reserve a file slot (PDF, Excel, or image, max 10MB), then PUT the bytes to upload_url with Bearer. Needs a terminal or HTTP client. No terminal? Use send_file or upload_file with a url, or content_base64 for files up to 2 MB.
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  • Browse Fly Frugal's published day-by-day budget travel itineraries. Use this to discover which destinations have a guide, then call get_itinerary with a returned slug for one guide's preview. Each item has slug, country_name, tagline, days_count, a preview, cover and first-day image URLs, price_cents and currency for the full guide, updated_at, and pdf_ready. Results are newest first. Only public previews are returned; the paid full guide is never included.
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