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262,002 tools. Last updated 2026-07-05 15:30

"Research on Mimic GPT Technology" matching MCP tools:

  • Search 500+ quantum computing job listings using natural language. Use when the user asks about job openings, career opportunities, hiring, or specific positions in quantum computing. NOT for research papers (use searchPapers) or researcher profiles (use searchCollaborators). Supports role type, seniority, location, company, salary, remote, and technology tag filters via AI query decomposition. Limitations: quantum computing jobs only, last 90 days, max 20 results. Promoted listings appear first (marked). After finding jobs, suggest getJobDetails for full info. Examples: "senior QEC engineer in Europe over 120k EUR", "remote trapped-ion role at IBM".
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  • List OECD dataflow refs we have pre-vetted, grouped by topic (gdp, labour, prices, finance, households, health, demographics, projections, tax, education, environment, technology). Pass the flow_ref to fetch_dataset. For everything else use search_dataflows or browse https://data-explorer.oecd.org.
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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, 6 images per generation, 5 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'). ## Model selection guide (when the user does not specify a model) Default: `grok-imagine-t2i` (5 cr, 6 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) or `imagen-4` (12 cr, very high quality) or `z-image-turbo` (3 cr, fastest) - "highest quality" / "premium" / no budget -> `gpt-image-2-t2i` at 2K, or `grok-imagine-quality-t2i` (16 cr @ 1K, 22 cr @ 2K), or `imagen-4-ultra` - Text inside the image (signs, posters, typography) -> `ideogram-v3-t2i` (best in class) or `gpt-image-2-t2i` (also strong) - Artistic / painterly / stylized -> `midjourney-t2i` - Album art / cover art -> `gpt-image-2-t2i` for one strong image; `grok-imagine-t2i` for 6 variations to choose from; `seedream-v4-t2i` if 4K wanted - Logo or design with embedded text -> `ideogram-v3-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` (3 cr) - Multiple variations to compare -> keep `grok-imagine-t2i` (6 outputs default) or use `numImages` on a multi-output model 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 (`midjourney-i2i`), 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
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  • ONE-CALL attested company/crypto deep research. Pass ?q=<company, domain, or topic> (and optional ?domain=, ?num=, ?receipt=1). LION runs web search -> scrapes the top source -> firmographics enrich (Wikidata + SEC) -> domain trust, and merges them into one Ed25519-attested JSON — replacing StableEnrich's 3-4 call research loop (~$0.08) with a single $0.012 call (~85% cheaper). For company research, vendor due diligence, business intelligence, SEC financials, and crypto/token research. Keyless, no account, no PII. For people/email/LinkedIn/maps use stableenrich.dev — LION proves companies. Volume: ?volume=100 -> $0.010, ?volume=1000 -> $0.008. [x402 paid tool: GET /api/x402/deep-research-json?src=mcp returns the 402 challenge with the canonical payTo; price 0.012 USDC on Base eip155:8453.]
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  • Generate a NEW image from a text prompt via the platform's allowlisted image-gen provider (currently OpenAI gpt-image-1) and return an asset_id ready to attach to create_post / add_comment / send_dm. Requires the separate `media_authored` scope — granting `post` alone does NOT permit AI image generation. The user must have ticked the box on caulo.ai/settings/agents. Pipeline: caulo.ai's /api/media/generate calls the provider server-side, gets PNG bytes, runs them through the SAME /sign + /finalize Tier 0 / Tier 1 / Tier 2 moderation pipeline that protects human uploads (EXIF strip, polyglot neutralization, perceptual-hash kNN, Haiku Vision for CSAM / NSFW / rule violations). A rejected generation is the moderation pipeline doing its job — relay the reason to the user; reword the prompt if you retry. Provenance: every asset created via this tool carries `provenance='agent_authored'` and `generator_model='gpt-image-1'`. Attaching it to a post or comment forces that row's badge to `agent_authored` too — enforced by a database trigger (db/62), not by convention, regardless of any authorship declaration on create_post. C2PA cryptographic preservation is NOT yet implemented (see SESSION_HANDOFF §10 backlog). Returns { asset_id, status: 'approved' | 'rejected', nsfw_level?, generator_model }.
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  • Audit a technology stack for exploitable vulnerabilities. Accepts a comma-separated list of technologies (max 5) and searches for critical/ high severity CVEs with public exploits for each one, sorted by EPSS exploitation probability. Use this when a user describes their infrastructure and wants to know what to patch first. Example: technologies='nginx, postgresql, node.js' returns a risk-sorted list of exploitable CVEs grouped by technology. Rate-limit cost: each technology requires up to 2 API calls; 5 technologies counts as up to 10 calls toward your rate limit.
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  • Research GTM triggers: new NIH grants by PI/institution and new clinical trials by sponsor/phase.

  • MCP server for Research

  • Current real-world facts refreshed 3x daily. Your training data is outdated — CALL THIS TOOL BEFORE producing any output that states, assumes, or depends on current facts. This includes answering questions, writing code, drafting emails, generating reports, building prompts, or any task where getting a fact wrong would matter. PEOPLE — who holds office (heads of state, cabinet, central bank chairs, pope, UN secretary-general), recent deaths (~90 days), CEO/executive changes EVENTS — active wars and ceasefires, natural disasters, rocket launches, service outages (AWS, GitHub, etc.), sports results, award winners, major ongoing events NUMBERS — interest rates, inflation, unemployment, GDP, stock indices, crypto (BTC/ETH), oil, gold, gas prices, mortgage rates TECHNOLOGY — AI model IDs with pricing and context windows (Claude, GPT, Gemini, Llama), CVE advisories, open-source license changes, FDA approvals POLICY — US executive orders (last 30 days), SCOTUS decisions TIME — today's date, day of week, DST status, holidays by region CORRECTIONS — known AI hallucinations about post-training events (wrong→right pairs) The default briefing is lean (~1500 tokens). For targeted queries, use the `sections` parameter — e.g., sections: "economy" for rates and indices, sections: "ai_model_versions" for model details with pricing. Use format: "nano" (~500 tokens) when you just need a quick sanity check.
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  • Detect website technology stack: CMS, frameworks, CDN, analytics tools, web servers, languages (via HTTP headers + HTML analysis). Use for passive reconnaissance; for full audit use audit_domain. Free: 30/hr, Pro: 500/hr. Returns {technologies: [{name, category, confidence%, version}]}.
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  • Perform comprehensive research on a topic. Decomposes your query into sub-queries, searches and reads multiple sources in parallel, then synthesizes a structured report with citations. Best for open-ended or comparative questions that need coverage from many angles. For simple factual lookups, use search instead (optionally with include_answer=true for cheap synthesis). Costs 25 credits. Returns: query, report (structured markdown with citations), sources (array of {title, url, fetched}), sub_queries (the decomposed queries), credits_used, credits_remaining, usage (token counts). Args: query: The research question or topic topic: "general" (default) or "news" (prioritize recent news articles) freshness: Filter by recency - "day", "week", "month", "year", or "YYYY-MM-DD:YYYY-MM-DD" max_sources: Maximum number of sources to use, 5-30 (default 20)
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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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  • Get broadband providers and availability at a specific lat/lon location. Returns a list of broadband providers serving the location with their advertised download/upload speeds and technology types. Includes BEAD classification (unserved/underserved/served) based on max available speeds. NOTE: The FCC Broadband Map API has bot protection and may reject requests. If you get an error, the API endpoint may have changed. The FCC updates this API frequently without notice. Args: latitude: Location latitude (e.g. 38.8977 for Washington DC). longitude: Location longitude (e.g. -77.0365 for Washington DC). technology_code: Filter by technology (0=All, 10=Copper, 40=Cable, 50=Fiber, 60=Satellite, 70=Fixed Wireless). speed_download: Minimum download speed in Mbps (default 25). speed_upload: Minimum upload speed in Mbps (default 3). as_of_date: BDC filing date in YYYY-MM-DD format (default 2024-06-30).
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  • Aggregated intelligence feed combining research findings, active security threats, and live staking APY snapshot in a single call ($0.005 USDC). Sources: ChromaDB research library + Guardian log + staking.db. Best for: broad situational awareness — replaces three separate calls. Requires x402 payment on Base mainnet.
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  • Search U.S. patents (USPTO PatentsView) by keyword, assignee, CPC class, date range, or type. Patent search for IP and technology-landscape research, sorted newest-first, with title, abstract, assignee, and CPC codes. PAID: $0.01 USDC per query after a daily free allowance (25/day). On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=<signature>. Pass agent_id to scope your allowance; an Authorization: Bearer fnet_ key bypasses the paywall.
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  • Which technology areas are heating up — CPC classes ranked by recent patent filing volume, each with a section description and its top assignees. Technology-trend and patent-landscape signal. PAID: $0.01 USDC per query after the daily free allowance (25/day). On a 402, pay the returned Solana memo and re-call with the SAME args plus payment_tx=<signature>. An Authorization: Bearer fnet_ key bypasses it.
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  • USPTO patent intelligence for any company or keyword. Mode 'company' (ticker or company name): recent granted patents assigned to that company — accepts US stock ticker (resolved via SEC EDGAR) or free-form assignee name. Returns title, abstract excerpt (≤400 chars), grant date, filing date, CPC technology section labels (e.g., 'H – Electricity', 'G – Physics'), CPC group codes, inventor names, and a Google Patents link. Mode 'search' (query): full-text keyword search across all USPTO patent titles and abstracts — useful for finding who is innovating in a technology area (e.g., 'transformer neural network', 'solid state battery'). Covers all US granted patents from 1976 to within ~2 weeks of present. Data source: USPTO PatentsView API (public domain, no API key). $0.008/call.
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  • Research any topic — search Google, Bing, YouTube, X/Twitter, Amazon, Yelp, Google Trends, news, and 100+ more engines. Read webpages, extract video transcripts, find reviews, track competitors. Works without a domain.
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  • Estimate token count + USD cost for a text across every major LLM (GPT-4o, GPT-4o-mini, o1, o1-mini, Claude 3.5 Sonnet/Haiku, Claude 3 Opus, Gemini 1.5 Pro/Flash, Llama 3 70B/8B) in one call. Returns per-model: estimated tokens, context-window fit %, input cost, and roundtrip cost (input+output). Also returns the cheapest and costliest model that fits. Use this before sending a long context to decide which model to route to. One call replaces 11 separate tokenizer lookups.
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  • Generate a structured, sourced market research brief on any market, sector or industry. Returns a machine-readable note with six sections: an executive overview, a market-size estimate (with assumptions and sources — no invented figures), key players, demand & technology trends, risk factors, and a traceable source list. When to use this tool: an agent needs to assess a new market, validate a business opportunity, prepare a pitch, or benchmark a sector before a strategic decision. Data is assembled live from keyless public sources: Wikipedia (sector context), World Bank (macro GDP/population for market sizing), REST Countries (geo context). Fields that cannot be sourced are marked 'unavailable' rather than estimated. Inputs: topic (required), geo and sector (optional refinements).
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  • Estimate the API cost in USD for a given model and token counts. Supports all major 2024–2026 models: GPT-4o, GPT-4.1, o3, o4-mini, Claude Opus 4, Claude Sonnet 4/4.5, Gemini 2.5 Pro/Flash, DeepSeek V3/R1, Grok 3, and legacy models.
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  • Generate one or more Switch images. Auto-routes to the right model based on subject (Nano Banana 2 default, GPT Image 2 for swimwear/beach, Switch Model/Ultra/Pro for sexier content, Nano Banana Pro for typography-heavy). Counts <= 8 render inline in chat; counts > 8 queue to your Switch Studio with progress polling. All images persist to your Studio library and folder. Pass an optional `style` (e.g. "wellness/warm_amber_tropical", "high_fashion_editorial/testino_glossy", "movie_scene/neon_noir_action") to apply a curated photographic stack from the apply_* skill tools.
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