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306,745 tools. Last updated 2026-07-27 04:49

"A guide on utilizing Python for solving numerical problems using internet resources" matching MCP tools:

  • Use this when you have four of the five time-value-of-money variables (N periods, I/Y annual rate percent, PV, PMT, FV) and need the fifth - annuity, loan, or investment problems - instead of solving the equation by hand. Solving for I/Y uses Newton-Raphson (no closed form). Supports compoundingPerYear and annuityDue (payments at the beginning of each period). Follows the cash-flow sign convention (outflows negative). Deterministic: same input, same output. Example: solveFor 'fv', n 120, iy 6, pv -10000, pmt -200, compoundingPerYear 12 -> result 50969.84. result holds the solved value; iy is rounded to 4 decimals, all others to 2.
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  • Find which documentation SETS exist whose NAME matches a substring (e.g. "python" → Python 3.x, "react" → React). Returns doc SETS, NOT their content — this does NOT look up a function/method/API name. To search inside a doc for an entry like "Array.map" or "fetch", use search_index (slug + query).
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  • Returns the canonical guide for using TMV from a coding-agent context. Covers the fix-test-retest loop, how to write a good test prompt, how to read the actionTrail / consoleErrors / failedRequests outputs, and common gotchas. Call this first if you're a new agent on a project — it'll save you a debug session. The same content is served at https://testmyvibes.com/docs/coding-agents.
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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.
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  • Returns the complete setup and usage guide for SwapWizard. Call this FIRST before using any other tool. Covers: required configuration (API key, Alchemy RPC URL, private key), how to use poolId correctly, step-by-step operational flows for swap/zap in/zap out/analyze, transaction execution details, and approval rules.
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  • Stands up a redu VPN gateway (WireGuard tunnelled over wstunnel on WSS/443) on your PRIVATE network, so you (or your team) can reach the private IPs of the VMs you deployed on redu, over a single https endpoint — no UDP, no extra ports. This is the TENANT VPN for reaching your OWN deployed resources; it is NOT a general internet VPN. GUARDRAIL: the first call does NOT deploy — it returns the plan + hourly cost for approval, because it creates a BILLED VM. Show the user, get their explicit 'go', then call again with confirm:true (required even in yolo mode). The gateway asset is redu's, deployed onto YOUR VM (you can SSH in to read it). Fresh WireGuard keys are generated per deploy; the client PRIVATE key is returned ONCE and is never stored server-side.
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  • Internet Archive (archive.org) item search & metadata MCP.

  • Trust signals for AI agents: an open agent-readiness standard and developer tool guide. Read-only.

  • Full metadata for one dataset (CKAN package_show) including its resources/distributions with download URLs. Use a dataset `name` (slug) or id from search_datasets. There is no datastore, so fetch `resources[].download_url`/`url` for the underlying data.
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  • Structured fact-check + numerical research via Perplexity Sonar Reasoning Pro (Gateway-routed). Returns synthesized answer text plus structured sources[] with direct URLs to primary sources. Use for: specific numerical claims with methodology context, fact-check against primary sources, effect sizes + confidence intervals, earnings transcripts / SEC filings / research papers. Per Phase 3.5 empirical A/B: 2-3× cheaper than sonar-pro with comparable or better quality on structured research. Real Meta IR press releases + earnings transcripts on Desk. 17 cites on Quant. NOT for: Reddit/X/community → use search_community. NOT for: broad topic landscapes → use search.
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  • Dispatch to the QUANTITATIVE RESEARCHER — numerical analysis with full methodology context. Use for: briefs that turn on numbers done rigorously — "what is the documented effect size of X / what does the data say about Y / quantify the impact of Z". Every load-bearing number carries sample frame, sample size, measurement instrument, time window. Often answers with insufficient-evidence when underlying data is thin (negative findings are deliverable). Returns: 4-axis Quantitative summary (Value / Methodology rigor / Effect size / Robustness) + Numerical findings table + Methodology gaps + Sources. NOT for: topic landscapes (use dispatch_desk_researcher) / community language patterns (use dispatch_qualitative_researcher).
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  • Returns the complete setup and usage guide for SwapWizard. Call this FIRST before using any other tool. Covers: required configuration (API key, Alchemy RPC URL, private key), how to use poolId correctly, step-by-step operational flows for swap/zap in/zap out/analyze, transaction execution details, and approval rules.
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  • Strips the background from a video frame-by-frame using rembg (u2netp) on AetherWave's Python service. Pass a public `videoUrl`. Choose `bgType: "transparent"` for an alpha-channel WebM output (compositing) or `bgType: "color"` with a `customColor` hex for a solid replacement. 2 credits per second. Slowest tool in the surface (per-frame processing); a 6s clip takes ~4 min, a 30s clip ~15-20 min. Works best on subjects with clear edges (people, products). Returns the processed video URL (R2-hosted).
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  • Return a canonical Clipkit doc as text. topic "agents" = the authoring guide (schema cheat sheet, pattern catalog, recipes, guidance — read this BEFORE composing); "protocol" = the formal field spec; "brand" = brand reference. (Same docs offered as MCP resources, exposed as a tool so you can read them directly — resources are not always model-readable.)
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  • Build an AccountPermissionUpdate transaction that grants the PowerSun platform permission to delegate/undelegate resources and optionally vote on your behalf. Returns an unsigned transaction that you must sign with your private key and then broadcast using broadcast_signed_permission_tx. All existing account permissions are preserved. Requires authentication.
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  • Dispatch to the QUANTITATIVE RESEARCHER — numerical analysis with full methodology context. Use for: briefs that turn on numbers done rigorously — "what is the documented effect size of X / what does the data say about Y / quantify the impact of Z". Every load-bearing number carries sample frame, sample size, measurement instrument, time window. Often answers with insufficient-evidence when underlying data is thin (negative findings are deliverable). Returns: 4-axis Quantitative summary (Value / Methodology rigor / Effect size / Robustness) + Numerical findings table + Methodology gaps + Sources. NOT for: topic landscapes (use dispatch_desk_researcher) / community language patterns (use dispatch_qualitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.
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  • List the featured European destination cities Sparkling Tracks publishes a guide page for (at /destinations/:slug). Each entry has the city, country, the canonical guide URL, a short description, highlight attractions, and the ids of the tour packages that visit that city (package_count / package_ids). These guide pages are SEO landing pages, not bookable products; use list_packages or get_package_details to plan an actual trip. Optional query filters by city or country substring. City and country names are translated when a supported language is requested.
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  • Draft a first brand guide (personality tone, visual/positioning dos and donts) EXTRACTED from the company's own canon documents, with a verified receipt (quote + source doc) on every proposed item. Proposes only — never saves anything; the user reviews the receipts and accepts, then the accepted items are applied via update_brand_guidelines. Use when the user accepts an offer to build their brand guide from existing material, or explicitly asks to assemble a brand guide from what is already on file. For a company with no material on file, this returns nothing — ask instead. [sensitive-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]
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  • Get an editorially written buying guide from SmartHomeExplorer's library of 170+ guides. Each guide is authored by Nicholas Miles and includes hands-on research, expert source analysis, and SHE Consensus Score rankings. Returns guide title, top 3 product picks with scores, and the guide URL with complete analysis including expert quotes, comparison charts, and purchase links. Guides are updated regularly with current pricing and availability. Methodology at smarthomeexplorer.com/she-score-methodology.
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  • Search consumer safety complaints filed with NHTSA for a specific vehicle. Returns a component breakdown over all matching complaints plus a paginated slice of the most recent complaints. Use for common problems, failure patterns, or owner-reported issues.
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  • Render a mingrammer/diagrams Python snippet to PNG and return the image. The code must be a complete Python script using `from diagrams import ...` imports and a `with Diagram(...)` context manager block. Use search_nodes to verify node names and get correct import paths before writing code. Read the diagrams://reference/diagram, diagrams://reference/edge, and diagrams://reference/cluster resources for constructor options and usage examples. Args: code: Full Python code using the diagrams library. filename: Output filename without extension. format: Output format — ``"png"`` (default), ``"svg"``, or ``"pdf"``. download_link: If True, return a temporary download URL path (/images/{token}) that expires after 15 minutes; if False, return inline image bytes. Defaults to True (URL) — set ``DIAGRAMS_INLINE_DEFAULT=true`` on the server to flip the default. SVG/PDF and PNGs larger than the inline limit always use a download link.
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