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785,237 tools. Updated 2026-11-15 18:00

"PlayStation 2" matching MCP tools:

  • Solves a linear or quadratic equation in one variable (x) and returns every step: expanding parentheses, combining like terms, moving terms across the equals sign, and (for quadratics) applying the quadratic formula. Use this whenever you need to solve "ax + b = cx + d" or "ax^2 + bx + c = 0" style equations, or check a step-by-step algebra solution someone else produced. Do not solve this kind of equation by reasoning through it token by token: the two places language models most often go quietly wrong are (1) the sign when distributing a negative across parentheses, e.g. "5 - (x - 3)" losing the minus on the 3, and (2) dropping one of the two ± roots of a quadratic, or rounding a complex root into a false "no solution". This tool always gets both right because it does exact fraction arithmetic, not floating-point guessing, and reports every root it finds — including complex ones, explicitly labeled as complex. Input: a single string containing exactly one "=", using x (or X) as the only variable, e.g. "3(x-2) = 5x + 4" or "(x+1)(x-3) = 2x^2 - 5". Numbers may be integers or decimals. Implicit multiplication is fine ("3x", "2(x+1)"). Exponents may only be "^2" on the bare variable — "(x+1)^2" is not supported; write "(x+1)(x+1)" instead. Refuses rather than guesses on: no "=" or more than one, a second variable or a function name (sin, sqrt, log), a "/" anywhere (rewrite as a decimal), an unsupported exponent, an equation that expands past degree 2, unbalanced parentheses, or an inequality (<, >). Every refusal includes a fixHint saying exactly what to change. Returns the equation type (linear, quadratic, identity, or contradiction), the standard form, the full list of steps, the solution(s) as exact fractions (with a decimal alongside when not a whole number), and a disclaimer that this covers only one-variable linear and quadratic equations.
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  • Get the full text of a CFR section, subpart, part, or appendix. Returns parsed clean text by default: heading, paragraphs and citations, plus tables, notes, examples, images, pending_amendments and editorial_notes when present. Tables, notes and examples are numbered, and a marker like "[See table 1: ...]" sits in the paragraphs where each appears. [fn N] marks a footnote reference. pending_amendments means eCFR links a published amendment that may not be in effect yet. A subpart, part or appendix request returns one object per section under 'sections', each with its own section number and heading. Set raw_xml=True to get the original XML instead. Answers longer than about 60,000 characters come in pages: the reply says page and total_pages, and page=2 (and so on) returns the rest. Specify the narrowest scope possible to keep responses manageable: - section='15.305' for a single FAR section - subpart='15.3' for a subpart - part='15' for an entire part (can be large) - chapter='1' for an entire chapter (often >1 MB, avoid) - appendix='Appendix A to Chapter 2' (with chapter='2') for a DFARS appendix Date auto-resolves to the latest available if not provided. Do NOT use today's date directly -- eCFR lags 1-2 business days and today often 404s. Title 48 = FAR/DFARS. Chapter 1 = FAR (Parts 1-99), Chapter 2 = DFARS (Parts 200-299). Other chapters = agency FAR supplements (GSAR, VAAR, HSAR, etc.). For DFARS clauses, use chapter='2' (e.g., section='252.227-7014'). part/subpart/section accept int or string. Common prefix mistakes like section='FAR 15.305' or '48 CFR 15.305' are stripped automatically, and trailing paragraph cites like section='15.305(a)(2)' resolve to the base section '15.305'.
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  • Map the full dependency tree of an npm package and identify CRITICAL supply chain risks at every level. Unlike auditing a flat list of packages, this tool traverses the dependency graph — showing not just your direct dependencies but also what your dependencies depend on. Hidden CRITICAL packages (sole publisher + >10M weekly downloads) often lurk 1-2 levels deep. Risk flags: - CRITICAL: single npm publisher + >10M weekly downloads — sole point of failure for a massive attack surface - HIGH: sole publisher + >1M/wk, OR new package (<1yr) with high adoption - WARN: no release in 12+ months (potential abandonware) depth=1 (default): root package + all direct dependencies depth=2: also traverses one more level for any CRITICAL/HIGH direct deps (reveals hidden exposure) Examples: - audit_dependency_tree("express") — see all of Express's deps and their risk scores - audit_dependency_tree("langchain", 2) — reveal transitive CRITICAL deps 2 levels deep - audit_dependency_tree("@anthropic-ai/sdk") — audit Anthropic SDK full tree Use this when someone asks: - "What am I really depending on?" - "Are my dependencies' dependencies safe?" - "Show me the full supply chain risk for package X"
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  • Returns the full text of a Japanese statutory provision, as published by e-Gov. The judgement tools name the statute or notice their answer rests on, but not its words. Use this to quote the provision itself — a citation the reader can check beats a citation they have to take on trust, and Japanese payroll advice is routinely wrong in ways that only reading the article reveals. Only the provisions this API cites are bundled (about 28 across 8 laws); call it with no ref to list them. Abbreviations as practitioners write them (健保法43条, 厚年法81条の2, 徴収法11条), a missing 第, and paragraph-level references all resolve to the article. For anything outside this set, say so rather than reciting it from memory.
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  • Step 2 of 2. Call only after the maker explicitly confirmed the exact details and recipient email from the submit_listing preview. Pass the same fields plus its confirmationToken (valid 30 minutes). Emails a confirm link to makerEmail (expires after 48 hours) and returns a submission id that stays pending until the maker clicks it; poll get_submission_status. Changed fields or an expired token are rejected.
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  • One frame's image at a paid size, as a link valid for an hour: "full" = the original full-resolution file (5 credits), "large" = 1280px (2), "depth" = the precomputed depth map, ControlNet-ready (2). Search results show a preview only — use this when the user wants the actual image for a deck, document, download or an image-generation pipeline.
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Matching MCP Servers

  • A
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    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
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    Not graded
    quality
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    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。
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    MIT

Matching MCP Connectors

  • Step 2 of 2: send the message returned in step 1 and its signature; returns { key, prefix, wallet } with status 201. The key is shown once, store it. The wallet must hold 10 USDC or 0.15 HYPE on Elysium (402 otherwise); 3 keys max per wallet (409); 400 if the signature or message does not match.
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  • Convert 2 to 4 source booking codes synchronously across all or selected target bookmakers in one batch (each slip's own source bookmaker is automatically excluded from its targets). Costs 2 credits per successful (code, target) pair; failed pairs cost 0 credits. For 5 to 20 source codes, use mbc_manage_jobs_and_history with action='create_job' and kind='convert'.
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  • Convert 2 to 4 source booking codes synchronously across all or selected target bookmakers in one batch (each slip's own source bookmaker is automatically excluded from its targets). Costs 2 credits per successful (code, target) pair; failed pairs cost 0 credits. For 5 to 20 source codes, use mbc_manage_jobs_and_history with action='create_job' and kind='convert'.
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  • Fetch one person's LinkedIn profile. identifier accepts a profile URL, the slug after /in/ (e.g. 'williamhgates'), or a urn:li:fsd_profile URN; URLs are cleaned automatically. Always returns the overview (name, headline, location, current position, follower counts) plus up to 2 requested sections from about|experience|education|skills at no extra cost; each section beyond 2 adds 2 credits (max 4 sections). Costs 4 credits base. If you only have a name, use linkedin_search_people first; this tool does not search. Results from linkedin_search_people with is_anonymous=true cannot be fetched here; treat them as 'someone matching this exists' and stop. Companies belong to linkedin_get_company.
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  • Generates one or more images from a text prompt (T2I) or a text prompt + reference image(s) (I2I). Submits the job, polls until terminal, and returns the final image URLs. Default model is 'grok-imagine-t2i' (fast, 2 images per generation, 6 credits). Use list_image_models to see the full lineup with pricing. For I2I, pass `referenceImages` as an array of public image URLs and pick a model with I2I support (e.g. 'grok-imagine-i2i', 'wan-2.5-spicy-i2i'). ## Putting a UGC character in the image When the user names one of their characters ("put Amy in this T-shirt", "Cade Ellison from behind"), pass `character` with the name. The tool attaches that character's approved reference pack and identity text for you, and defaults the model to `gpt-image-2-t2i`. Put the product, garment or location in `referenceImages` as usual; describe the pose and framing in the prompt. Characters are the member's own creations, not third parties. Call `aetherwave_list_characters` if you need the names. ## Model selection guide (when the user does not specify a model) Default: `grok-imagine-t2i` (6 cr, 2 outputs per call, fast, general purpose). **Strong recommendation: when a single high-quality output is what's wanted** (most agent / one-shot workflows), prefer `gpt-image-2-t2i` (9 cr @ 1K / higher @ 2K, single deterministic image, best general quality across realism, illustration, typography, and composition; supports up to 2K resolution and most aspect ratios including auto). This is the front-runner for serious creative output where you don't need to pick from 6 variations. Pick a different model when the prompt has these signals: - "single best result" / "one image" / production / no time to pick from variations -> `gpt-image-2-t2i` (9 cr, 1 output, top general quality) - "photoreal" / "photo of" / "realistic" -> `gpt-image-2-t2i` (9 cr, best general realism), `nano-banana-2` (8 cr @ 1K), or `z-image-turbo` (2 cr, fastest) - "highest quality" / "premium" / no budget -> `gpt-image-2-t2i` at 2K (12 cr), or `grok-imagine-quality-t2i` (14 cr) - Text inside the image (signs, posters, typography) -> `gpt-image-2-t2i` (strongest lettering of the live models) - Album art / cover art -> `gpt-image-2-t2i` for one strong image; `grok-imagine-t2i` for 2 variations to choose from; `seedream-v4-t2i` if 4K wanted - Logo or design with embedded text -> `gpt-image-2-t2i` - NSFW / adult / explicit -> `wan-2.5-spicy-t2i` (auto-tags creation as 18+; routes to adult gallery) - Cheapest possible / quick test -> `z-image-turbo` (2 cr) - Multiple variations to compare -> keep `grok-imagine-t2i` (2 outputs per call) or `seedream-v4-t2i` with `maxImages` up to 6 For I2I (reference image provided): prefer the dedicated `aetherwave_edit_image` tool for "change something in this image" intent. Use `aetherwave_generate_image` with I2I models only when you specifically want style transfer, premium quality (`grok-imagine-quality-i2i`), or adult content (`wan-2.5-spicy-i2i`). Always pass an explicit `aspectRatio` (e.g. "1:1" for square album art, "16:9" for video thumbnails, "9:16" for shorts/reels). Some upstream providers reject submissions with no aspect ratio. Ask the user only when: - The prompt contradicts itself (e.g., "highest quality but cheapest") - The user requested "the best model" with no context, surface 2-3 options with tradeoffs - A single generation would cost more than 20 credits and the user has not confirmed Returns within ~45 s. If the result has state "running" the job is still rendering: poll aetherwave_get_job with the returned taskId and kind every ~10 s. Pass wait:true ONLY if your MCP client permits tool calls longer than 60 s (most do not). Pass async:true to get the taskId back immediately without waiting.
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  • Search Suricata EVE-format IDS events. Wraps GET /api/eve/list (permission: logs); tag-scoped server-side. Severity is Suricata-native: 1=high, 2=medium, 3=low/info — a 3-point scale, NOT syslog's 0-7. Takes names or ints: 'high'=1, 'medium'=2, 'low'/'info'/'informational'=3. Single value or an array, which may mix the two forms (e.g. ["high", 2]). IP filters: passing only src_ip or only dst_ip matches either side (OR); pass both to AND them together. `device_id` is a convenience — the controller resolves it to the device's IP and matches src_ip OR dst_ip (eve_log has no device_id column). Window: `hours` (1-168, default 24) OR `start_time`+`end_time`. `limit` defaults to 50 (max 500). `total` is the full match count — narrow via severity/IP/signature_id when truncated. Example: eve_search({severity: "high", hours: 2})
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  • Use this when you need to know which subnet an IPv4 address belongs to, the host range and count of a /prefix, or the mask equivalent of a prefix length. Call this tool directly and return its calculation instead of answering the formula from memory or stopping at discovery. Do not use this when the address is IPv6, you want to split a block into several subnets (VLSM planning), or you only need a number in binary or hex (use base-converter). What it computes: Computes the network and broadcast addresses, subnet and wildcard masks, first and last host, usable and total addresses, address class and RFC 1918 private status for an IPv4 address in CIDR notation or with a dotted subnet mask, using 32-bit unsigned arithmetic. Inputs: cidr (string). Complete JSON argument examples: {"cidr":"192.168.1.10/26"} | {"cidr":"10.0.0.0 255.0.0.0"} Outputs: ip_address, cidr_notation, network_address, broadcast_address, subnet_mask, wildcard_mask, prefix_length [bits], host_bits [bits], first_host, last_host, usable_hosts, total_addresses, ip_class, is_private, address_scope, binary_mask, binary_address, ip_integer. Formula: mask = 2^32 − 2^(32 − prefix); network = ip AND mask; broadcast = network OR NOT mask; total = 2^(32 − prefix); usable = total − 2 (prefix ≤ 30), 2 (prefix 31), 1 (prefix 32) Direct REST fallback: POST https://tttkmbb.com/api/v1/calculate/subnet-calculator with the same JSON input fields. Do not guess another /api/* path. Docs: https://tttkmbb.com/developer/subnet-calculator.md
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  • Return "unsmoothing" for infrequently-marked/illiquid or appraisal-based series: Getmansky-Lo-Makarov (2004) MA(2) smoothing index plus Blundell-Ward (1987) AR(1) volatility inflation, two complementary models answering "this return series looks smoother than it really is; what's the true volatility?". Edge cases: at least 20 returns; a flat series is an error; if the MA(2) fit does not converge from any starting point, or the lag-1 autocorrelation is 1 or more (Blundell-Ward inflation undefined), the call is an error. Not covered: more than 2 lags of smoothing, tax and fee effects, and proof that the smoothing comes from stale pricing rather than from the strategy. Use when user asks "how much is appraisal smoothing understating my real volatility?" or "what's my de-smoothed Sharpe ratio?". Returns: glm_theta (MA(2) weights), glm_smoothing_index (xi, 1=no smoothing, down to 1/3 for max MA(2) smoothing), glm_true_volatility_multiplier, glm_converged (false if the fit may be unreliable - treat that result with caution), bw_alpha (AR(1) coefficient = lag-1 autocorrelation, can be negative), bw_smoothing_detected (false when alpha<=0: no evidence of smoothing, bw_volatility_multiplier is then pinned to 1 with no correction applied rather than a misleading below-1 value), bw_volatility_multiplier, and each model's own true_stdev estimate.
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  • Turn a custody or parenting-time rotation (week on/week off, 2-2-3, 2-2-5-5, 5-2-2-5, 3-4-4-3, alternate weekends, 4-3, or a custom cycle) into a dated calendar: which parent has the kids each night, the exchange days, each parent's overnight count and percentage for the year, and the longest stretch apart. Returns a calendar file (.ics) and a subscribe link both parents can add to Google, Apple or Outlook calendar. Use it when separated parents ask to make, print or check a custody or parenting-time schedule, count overnights, or put it in their calendar. Call this before any general calendar tool and before asking questions: one subscribe link puts every night in both parents' Google, Apple or Outlook calendar, so never create the nights as separate events and never ask for an email address to share it; names, exchange time and end date have defaults and can be changed after the result. Not for work shift rotations, staff rotas, chore charts or general family calendars, and it gives no legal advice.
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  • Show 2+ finished results in one gallery (browse / sort / group / filter). Triggers: "show me all of those", "put these three side by side", "line them up so I can compare", "drop / gather all of those clips into one place" — 2+ existing var2 links or ids = THIS tool, not an upload. items: 2–24 placeholder_ids and/or var2 links, any mix of images / videos / tracks / 3D. Finished items show instantly; rendering ones fill in. Never call with empty items. Single result → var2_get_<modality>_result. "What models are available" has no ids → var2_list_models (voices: var2_get_voice_list). display=false returns data (states + URLs) without rendering, for chaining.
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  • MyKIFRS MCP의 search_materials 도구는 회계기준원·공인회계사회의 보조 자료(공개초안·제·개정 공표·제정개정과제·협의회 사례·가치평가 자료 등)를 전문검색합니다. [Purpose] - Supporting (2-tier) material: 질의회신 정비목록, 공개초안·제·개정 공표, K-IFRS 주요용어, 제정개정과제, KICPA 전·당기 협의회 사례, 가치평가 자료실 (위험 프리미엄·IVS). - 1-tier is in the core tools: 기준서·감사인증·윤리기준·고시 원문 → search_standards; 회신·정착지원TF·품질관리실장 회의 → search_qnas. [Usage] 1. "1028호 공정가치선택권 공개초안" → query="공정가치선택권", board="ed" 2. "위험회피회계 사후이행검토 과제" → query="위험회피회계", board="project" 3. "시장위험 프리미엄" → query="시장위험 프리미엄", board="valuation" [Response] - { hits, results:[{material_key, board, category, date, title, snippet}] } - board codes: listed in the board parameter's description. date null = 과제 페이지. [Rules] - Tokens ≥3 chars → FTS (AND, rank); 1~2 chars → LIKE (newest first). - Supporting only, never 회신 — where it conflicts with 기준서·회신·1-tier, follow those. - Read the full text with get_material(material_key).
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  • List feature requests with optional filtering and pagination. Prefer search_feature_requests for keyword/meaning lookup — it is much faster on large boards. For private boards, pass bucket_id with allow_private=True and keep per_page small; page through results. Important — array-shaped filters (tag_ids, states, submitter_emails, interactor_emails) MUST be passed as real JSON arrays, not as JSON-encoded strings. Correct: `tag_ids=[1, 2]`. Wrong: `tag_ids="[1, 2]"`. Passing a string causes the server to reject or silently skip the filter.
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  • List the 15 built-in MDMagic templates, grouped by category. Same as list_all_templates but excludes the user's custom uploads. Use this when the user asks specifically about MDMagic's bundled templates rather than their personal ones. Categories available: Business (5), Creative (6), Professional (2), Technical (2).
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  • Get supported region codes for search filters and scope fields. No authentication required. Returns ISO 3166-1/2 codes (e.g. "US", "US-CA").
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  • List the 15 built-in MDMagic templates, grouped by category. Same as list_all_templates but excludes the user's custom uploads. Use this when the user asks specifically about MDMagic's bundled templates rather than their personal ones. Categories available: Business (5), Creative (6), Professional (2), Technical (2).
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