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737,333 tools. Updated 2026-11-02 20:18

"A guide to file operations" matching MCP tools:

  • Enumerate and inspect the validated operations scene_apply accepts — call this BEFORE reaching for scene_script. The DSL is large (mesh editing, booleans, lathe/loft/sweep, curves, UV unwrap, modifiers, materials, lights, cameras, render settings, geometry nodes, batch and query ops), so most modelling does NOT need raw bpy. No args: every namespace with counts. guide=true (or op="guide" for older connector catalogs): full operating guide. namespace="mesh": that namespace's operations. Repeated details are object.radial_array or object.array_along_curve (no "pattern" namespace). Use world.update for the environment; validation is the separate scene_validate tool. search="boolean": ranked matches. op="mesh.bevel": the full JSON Schema with types, ranges and defaults. Schemas are introspected from the validator itself, so they are always exactly what scene_apply will accept. Full schemas are returned once in structuredContent; format="text" returns them in text instead. This tool is READ ONLY and free — it queues no job, spends no compute and changes nothing — so it is always safe to retry, including after a transport-level error.
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  • What to know before going to a venue, from UPFRONT's venue guide: the bag policy and what fans can bring, gates and entry, parking, getting there by transit or rideshare, and food and drink, including what the guide says about gluten-free, vegetarian or vegan, halal and kosher food. Matches questions like "what's the bag policy at MetLife?", "when do doors open at MSG?" or "where do I park for Lambeau?". venue: the venue's name ("MetLife Stadium", "MSG", "Lumen Field, Seattle"). topics: optional; only these parts, at more length: any of "bags", "entry", "parking", "transit", "food". Without it, every part. Covers the 36 stadiums, arenas and amphitheaters UPFRONT has a guide for; for any other venue the answer says so and lists the ones with guides. Each part is the guide's own words ("text", plus the guide's "faq" questions and answers). factsLastChecked is the date UPFRONT last checked the guide's facts; rules can change for a single event, and the venue's own event page has the final word. guideUrl is the guide on UPFRONT. dietary lists what the guide says per diet; dietaryNotMentioned lists diets the guide doesn't cover, which doesn't mean the venue has nothing for them.
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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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  • Get the current value of a figure a reference quotes with a date. Use this when a reference quotes a figure from an OptimToken guide ("measured on the 2026-10-25 OptimToken catalogue") and the answer needs the current value: the Compute Savings Plan or reservation discount, the gap between a flexible and a locked commitment, the ARM discount against Intel and AMD, the share of LLM models with a batch rate. It fetches the guide's figures file, rebuilt daily, and returns it as published. Args: guide: The guide slug, lowercase letters, digits and hyphens. Guides with figures today: ``"savings-plans-vs-reserved-instances"``, ``"arm-against-x86"``, ``"batch-api-economics"``. Returns ``{"document": {...}, "fetched_at": ..., "source": "live" | "cached", "note": ...}``, plus ``cache_age_seconds`` when cached (six-hour cache). ``document`` is the file unchanged: ``guide``, ``title``, ``url``, ``dataSource``, ``snapshotDate`` (the catalogue the figures come from), ``dateModified`` and ``figures``, where discounts are fractions (0.2743 is 27.4%) and each key names a median, a range or a count. An unknown slug returns ``{"error", "available_guides", "suggestions"}``. Any other failure (timeout, HTTP error, invalid JSON) returns ``{"error", "fallback"}``: the dated figure in the reference then stands, quoted with its date.
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  • <summary>Replace the user's writing style guide for one channel, the voice Sliq writes in there. A set guide overrides the communication style in memory, so when the user wants to sound different in a channel that has a guide, change the guide. It replaces text the user wrote or approved: keep everything they didn't ask to change, and tell them what you changed. To edit a guide, read it with get_writing_style_guide and pass back the whole new guide, without the notes that tool appends after it. The other channels keep their guides.</summary> <returns> <description>The writing style settings after the change.</description> </returns>
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  • Returns an official GuruWalk support guide for a specific traveler-support topic. GuruWalk is a platform for free walking tours and paid activities; these guides are GuruWalk's own source of truth on how bookings, cancellations, account settings and contacting guides actually work, including current policies and the exact URLs travelers should use. These guides apply only to bookings and accounts on guruwalk.com. Available topics: - account_settings: The traveler wants to manage their GuruWalk account: edit their details (name, surname, phone, city, password), change their email, stop receiving emails / unsubscribe, or delete their account; or they can't access their account. These are concrete steps you shouldn't improvise: consult this before answering. - contact_guru: The traveler wants to contact or coordinate something with the guide of their GuruWalk booking, or thinks they are talking directly to the guide: they can't find them at the meeting point, the guide didn't show up, they're running late, they treat you as if you were the guide, ask for the tour photos, or ask about bringing a pet or paying the guide, or have a question only the guide can answer. - free_tour_modification: The traveler wants to modify or reschedule their GuruWalk free tour — change the day, time, language or number of people — or asks how to do it. - group_booking: The traveler wants to book or extend a GuruWalk booking for a group (they usually say how many; treat it as a large group from around 6 people), asks how to book for many people, can't book for the whole group, sees a large-group notice or is asked for a card or payment for the group, or had a booking cancelled as "group or duplicate". The rules aren't intuitive; consult this before advising. - paid_cancellation: The traveler wants to cancel or change a paid activity booked on GuruWalk, asks about a refund, or can't cancel from their account. Call this when the traveler raises a support topic covered above. Pass the exact topic; the guide content is returned.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    面向 Codex、WorkBuddy 等 AI 工具的知你AI助手合并版 Skills,涵盖当前会话分诊、客户查询与画像、历史会话检索、客户分群和 API Key 用量查询,并连接个微、企微、视频号、微信小程序、公众号、服务号、微信客服、微信小店、抖音号、小红书、微博、网站及H5客服等渠道。
    MIT No Attribution
  • A
    license
    Not graded
    quality
    C
    maintenance
    这是面向智能运维场景的 MCP 工具服务,让 Agent 能够按需检索日志内容并获取主机与应用的监控指标数据。它把实时的日志与指标证据接入 Plan-Execute-Replan 诊断流程,从而支撑自动故障排查与根因分析。
    3
    MIT

Matching MCP Connectors

  • 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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  • The published guides. With no slug: the list, newest first, each with its title, description, written date and address, optionally only those whose title, description or slug contain every word of q. With a slug: that guide in full, its body as markdown. A guide that is not published is not found.
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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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  • Use this when a veteran has a VA compensation and pension examination scheduled for a condition and wants to know what it involves. It does not schedule, reschedule or contact VA, and the examiner's findings and VA decide the rating. Returns the examination type and typical length, what the examiner does, the questions examiners commonly ask, the Disability Benefits Questionnaire sections that apply, and records worth bringing. It does not return advice about what to describe, emphasize or omit at the examination. For a condition with a guide on file it also returns the diagnostic code for that condition and where its rating criteria are published, which are what the examiner's findings are scored against; any other condition returns a general exam guide. Educational reference about the examination process.
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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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  • Use this when a veteran needs what a VeteranHQ guide on a VA topic says, given a slug from search_guides. A guide states the rules as VeteranHQ read them from the cited sources on the date it reports, and only VA decides a claim. Returns the slug, title and summary, the date the facts in it were last verified against its sources, the public URL of the guide on veteranhq.app, the body split into the sections the guide itself defines, each with a heading and its text, and the sources the guide cites, each with a title and a URL. A slug this library does not hold returns a tool error carrying GUIDE_NOT_FOUND, whose message says to call search_guides and use a slug from its results. A guide longer than one result can carry returns the sections that fit, plus omittedSections counting the sections left out and a note stating that count and the guide URL. A single section larger than the whole budget is served shortened at a paragraph or sentence boundary, with truncatedSection naming its heading and the note repeating it, so a section that was cut is distinguishable from one served whole. Those three fields are absent when the whole guide is returned, so a shortened answer is distinguishable from a complete one. It reads no account data, so the answer is the same for every caller with the same inputs.
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  • Save a guide on a project. With guide_id it is a new version of that guide; with a name no main guide on the project has yet it starts a new guide (one project can hold many videos); otherwise it is a new version of the newest guide. kind "auth" is the login flow (never recorded, may use {USERNAME}/{PASSWORD}); kind "main" is the walkthrough that becomes the video. Call get_guide_instructions before writing a guide and validate_guide before saving it.
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  • Fetch an xTiles guide/documentation document by its `xtiles://guide/...` URI. The same documents are also exposed as MCP resources — use this tool when your client cannot read resources directly. Before generating Markdown for any `*_from_markdown` tool, read `xtiles://guide/markdown/overview` (and `/canvas`, `/collections`, `/blocks`) to get the syntax. `xtiles://guide/markdown/design` holds the colours, styles, layout and tab colours created content takes. `xtiles://guide/markdown/tasks` covers tasks — where a task goes, whose it is, and which dates to set.
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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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  • No key needed. Without customer_type: the list of guides (one line each), the start page and how to get a key. With customer_type (mineral-processing | dark-proteins | alloys): the full guide, which says what to supply, what runs, what comes back and what it costs. With template (openmm-stability): the script text of that template, ready to save and submit.
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  • Return Genpio's guide for one country or market: what that market's platforms allow for an AI livestream host, quoted from their own policies with links, which local platforms Genpio does not stream to, which languages Genpio Voices speaks there, and the guide's full text as Markdown. Use it whenever a question names a country, and pass the language the person is writing in so the guide comes back in it. For a country without a guide it says so and gives only what holds worldwide; do not carry another country's platform rules over to it. With no country, it lists every guide.
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  • Check one file of SQL, Python (PySpark, a notebook's source) or YAML (a Databricks Asset Bundle, job, cluster or warehouse config) against the Field Guide's own best-practice rules, deterministically: partitioning where the guide would cluster, secrets and storage paths written into code, grants to people rather than groups, environments in table names, jobs on all-purpose clusters or without timeouts, warehouses and clusters without auto-stop, bundle targets without their modes, and the rest of the rules the chapters state. Each finding gives the line, why, the fix, the guide's passage verbatim with its section URL, and the docs.databricks.com links the guide cites for it; the result also lists the sections worth reading for this code. No model is called: weigh the findings yourself. One file per call.
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  • Review Supabase migration changes for missing RLS or policies, unrestricted read/write policies, exposed security definer functions and Data API grant gaps. Pass file contents: sql contains one migration's SQL text; files contains path and content for each file. Runs the VibeRaven 1.7.6 SQL rules and returns finding id, severity, file, line, a suggested fix and a guide link. For missing Data API grants, include the migration revoking default privileges or supabase/config.toml, plus browser files using supabase.from(...) (a "use client" file, or src files with package.json for Vite). Limits: supplied text only, up to 200 KB/50 files; cannot access your repository or database, does not execute SQL, and does not store or log file contents.
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  • Search Strong Saga's compared and ranked home gym gear with a plain-language query, e.g. "walking pad for a 300 lb person" or "power rack under $500 for a 7 ft ceiling". Returns results with id, title (name, guide rank and guide price) and url (the Strong Saga guide to cite). Call fetch with an id for the full record and its guide link. Same data as answer_home_gym_question, in the search/fetch shape ChatGPT connectors and deep research use. A general question with no gear type returns a priced starter set. An empty query returns the #1 pick of each Strong Saga guide.
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  • When to use: Hugging Face Hub models, datasets, Spaces, collections, papers, daily papers, today's trending models, current paper leaderboard, docs, and repository files. Examples: {"operations":[{"cmd":"ls","args":["hf://models/trending","--limit","10"]}]} {"operations":[{"cmd":"ls","args":["hf://papers/trending"]}]} {"operations":[{"cmd":"ls","args":["hf://papers/daily/latest"]}]} {"operations":[{"cmd":"cat","args":["hf://papers/2501.00001/paper.md"]}]} {"operations":[{"cmd":"search","args":["hf://models","--tag","base_model:finetune:org/repo"]}]} Use hf_fs for Hugging Face Hub filesystem operations. Call it with operations, an array of {cmd, args} items; multiple operations may be submitted together. Usage: {"operations":[{"cmd":"ls","args":["hf://models/org/repo"]}]} Grammar; each string below is one args array item: ls URI [--recursive] [--glob GLOB] [--type TYPE] [--sort SORT] [--limit N] cat URI [--offset N] [--max-bytes N] attach URI [--max-bytes N] stat URI find URI [--name GLOB] [--path GLOB] [--type TYPE] [--limit N] search URI [QUERY] [--type TYPE] [--sort SORT] [--tag TAG] [--kind mcp] [--limit N] COMMAND = ls|cat|attach|stat|find|search. TYPE = file|dir|repo|bucket|collection|paper|link. SORT = createdAt|downloads|likes|lastModified|likes30d|trendingScore|mainSize|id|trending|upvotes. URI is a canonical hf:// URI. QUERY and GLOB are each one string. Use search for resource discovery, not repository-content search; ls for a known directory, find for recursive file discovery by name/path (not file contents), stat for filesystem metadata or an uncertain target type, cat for text contents, and attach for a complete JPEG, PNG, or WebP image. When the request gives an exact text-file URI, use cat directly; do not add ls or stat first. stat does not read the contents of JSON, Markdown, or other text files. Search scopes: hf://models[/OWNER], hf://datasets[/OWNER], hf://spaces[/OWNER], hf://collections[/OWNER], hf://papers, and hf://docs[/...]. Repository and repository-file scopes are not supported: search a resource root or owner scope to discover resources; use find for file discovery within a repository or cat for a known text file. Paper and documentation search require QUERY. --tag filters models, datasets, and Spaces by Hub tag (repeatable; all must match) and applies only to hf://models|datasets|spaces[/OWNER]; omit QUERY when the tag already identifies the target, because QUERY also filters repository names. Derived models carry base_model:ID and base_model:RELATION:ID tags, where RELATION is finetune, adapter, merge, or quantized. --kind applies only to hf://spaces[/OWNER]; the only valid --kind value is mcp, which selects MCP Spaces. Tag families are documented at hf://README.md. Use ls hf://models/trending, hf://datasets/trending, hf://spaces/trending, or hf://papers/trending for trending listings. hf://papers/ID is a paper directory, not paper text. Use cat hf://papers/ID/paper.md for paper text and cat hf://papers/ID/metadata.json for metadata. No preliminary listing is needed for these known paths. Use ls hf://papers/ID to discover other resources. Omit --limit, --sort, and --type unless the request requires them. Limits and path-specific behavior are documented at hf://README.md. Issue one hf_fs call.
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