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745,045 tools. Updated 2026-11-05 03:01

"A guide to conducting market research" matching MCP tools:

  • Fetch one subreddit's profile: title, description, subscriber and active-user counts, age, NSFW flag, and topics. subreddit_name is the name without the r/ prefix, e.g. 'selfhosted'; a full reddit.com URL also works. Set include_settings to also get the community rules and moderator list for +2 credits (useful before posting or judging moderation culture). Costs 4 credits base. Subscriber counts here are the standard sizing signal for market research. This tool does not return posts: read the feed with reddit_get_subreddit_posts, and discover subreddits you don't know by name with reddit_search type=subreddits.
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  • 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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  • How to operate as a product manager on AIOProductOS. No arguments and no side effects — returns the same operating guide as plain text every call (deterministic): how to ground in the product brain, keep work welded to the spine (insight→feature→task→outcome), prioritise on evidence (affected accounts + MRR + reach), and what 'done' means. Call it FIRST, before planning or prioritising, to load the house rules the other tools assume.
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  • Stablecoin-only ranking or per-symbol chain breakdown. scope=full with sections=issuance_flow returns issuance_flows[] (CryptoQuant net issuance/redemption); sections=usage_structure returns real usage metrics; sections=depeg_events returns depeg events (stablecoin de-peg event library). Broad market dashboard→get_market_overview. Cross-sector rollup→get_defi_overview. Read-only public research data. No account access, no order placement or fund transfers. Not investment advice.
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Matching MCP Servers

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    Enables AI agents to conduct local, auditable opportunity discovery by collecting public discussions, tracing claims to exact quotes and source provenance, testing claims with counterevidence, and exporting deterministic evidence packs.
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Matching MCP Connectors

  • See if a market is heating or cooling. Trend volume and growth signals. Free key at trendsmcp.ai

  • Consumer demand signals across search, shopping and social. Free key at trendsapi.ai

  • 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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  • Generate an executive-level strategic review report for an idea, synthesising all available validation data (market research, competition, SWOT, revenue model, VC score) into a concise go/no-go assessment with actionable recommendations. Requires prior validation data (run request_revalidation first if none exists). Returns cached report instantly if one exists, otherwise generates fresh analysis. Spends 2 credits only when generating new content. Not read-only; pass an ideaId you own.
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  • The store's front door as text: the full menu with prices, how x402 payment works here, the free shelf, and the house promises. Free. Completes when the guide text returns. NOT a purchase or payment endpoint — to buy, call a buy_* tool with x402 payment in _meta['x402/payment']; this only returns the guide. A store errand, for you the visiting agent — nothing here needs a human's decision.
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  • Replace an existing interview guide from markdown. To create the first guide, call guides_create. Text before the first ## is the intro. ## Title (12) or ## Title (7–11) is a block; minutes are the last number in parentheses. Lines starting with - or 1. are questions; a leading * marks a key question; the next indented line is the question note. A paragraph under the block heading before the first question is the block note. ## Конспект is the post-interview notes template, not a block. Optional line `Общее время: 30` or `Total: 30` sets total minutes; otherwise they are the sum of block minutes. Anything that does not match is returned in remainder and kept, not dropped. The previous guide is replaced entirely.
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  • Scaffold a flags-only Bridge integration into an existing project — the MCP equivalent of `bridge flag init`. Returns everything that command produces, for YOU to write to disk: the contents of bridge-flags.config.json (app id, app name, base URL, suggested provider config, read live from this Bridge app), the install command, and the framework-specific setup guide fetched from the plugin repo that owns it. Writes nothing — neither to disk nor to the Bridge app. Call this when adding feature flags to a project for the first time; for auth or billing use get_integration_guide with topic=master or topic=billing-master instead. framework is REQUIRED: this server cannot see the caller's disk, so detect it yourself from package.json (next → nextjs, @sveltejs/kit or svelte → svelte, @nestjs/core → nestjs, @angular/core → angular, react → react, express → express; check in that order) and pass it. The returned guide is the same document get_integration_guide returns for topic=feature-flags, so there is no need to call both. Do not invent import specifiers — they differ per plugin and only the guide has the current ones.
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  • The real emergency number and crisis lines for a country. Use FIRST, before any other tool, when someone speaks of harming themselves or others or is in danger. Never defaults to a country: ask if unknown. Example: {country:"Kenya"}. Full guide: living-bread://tools/get_crisis_help. Access: no sign-in; shared limit of 300 requests a minute per IP.
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  • Purpose: one-call overview of the carbon market layer - dated carbon price snapshots (EU ETS auction/settlement, China national ETS), market size statistics and allowance allocation rules, each with its issuer and source. Guidelines: use for "what is the carbon price / how big is the market / how are allowances allocated" style questions; filter by market to narrow to the EU or China. Limits: prices are dated snapshots from the cited sources, NOT live quotes; currencies are not converted, so do not compare across currencies without an FX rate. Ex: get_carbon_market_overview(), get_carbon_market_overview(market='cn'), get_carbon_market_overview(market='eu', language='en'). ⭐ Scope: ONE market at a time - price + market size + allocation rules together. For a side-by-side comparison across markets (who is more expensive, what is the spread), use compare_carbon_prices instead.
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  • Find 10ML's perfume and fragrance guides to read or cite: how-tos (where to spray, finding a signature scent, making perfume last), notes explained, house guides, lists, and alternatives guides that compare famous perfumes with similar ones from other houses. Returns title, type and a link per locale. Use whenever you want a source to cite or a deeper read ('how to layer perfume', 'best oud perfumes', 'Creed Aventus dupes guide'). Not for facts about a perfume (use get_perfume) and not for note definitions (use explain_note).
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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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  • Run a Shiko tool marked [write], such as edit_map. Changes the user's maps: each call is atomic, and the user can undo it from the map's History panel. Find the name with search_tools and the arguments with describe_tools, and read guide {topic:"editing"} before your first write. An unknown name, a [read] tool or invalid arguments returns an error saying what to fix.
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  • Where pages publish, Search Console, other agents and the events webhook. A site has one publishing destination: a second is refused, so remove the first to move. check: true reads the site and stores nothing. action: - connect_wordpress(siteUrl, token, authorId?, categoryId?, check?): A WordPress site, with the Sightkick plugin active and its token (wp option get sightkick_token). Guide: https://sightkick.so/connect/wordpress.md - connect_shopify(shopDomain, clientId?, clientSecret?, accessToken?, blogId?, authorName?, check?): A Shopify store's blog, with the owner's app's clientId and clientSecret (or an shpat_ accessToken). Guide: https://sightkick.so/connect/shopify.md - connect_framer(projectUrl, apiKey, collectionId?, blogUrl?, check?): A Framer project's CMS collection, with its address and an API key. Guide: https://sightkick.so/connect/framer.md - connect_webhook(webhookUrl, blogUrl?, bearerToken?): A site on its own code: each page POSTed, signed, to its https webhookUrl. Returns signingSecret and indexNowKey this once. Guide: https://sightkick.so/connect/webhook.md - edit(connectionId, label?, authorId?, categoryId?, token?, blogId?, authorName?, clientId?, clientSecret?, accessToken?, blogUrl?, autoPublish?, apiKey?, webhookUrl?, bearerToken?, removeBearerToken?): Change a connection: what's left out stays, new credentials are checked against the site. - test(connectionId): Check a connection works (a webhook gets a signed test event). - remove(connectionId): Stop publishing there and forget which page is which post (the site keeps its pages, and a later publish there is a new post). Can't be undone. - destination(key, label?, path?, on?): Change a destination (get_settings destinations): rename it, move it to another folder (refused while a live page is in it: its address would change), or switch a page type's off (no new pages go there) or on. - add_destination(label, path): Add one of the owner's own destinations: a folder of blog-style pages beside the blog (Guides at /guides). Up to 10. - remove_destination(key): Remove one of the owner's own destinations once no page is in it (a page type's is switched off instead). - search_console_link: Connecting Google is the owner's: the app page they open, and a line to hand them. - search_console_properties: The owner's Search Console properties that cover the site. - pick_property(siteUrl): Use one of those properties (another one drops the old one's data). - disconnect_search_console: Disconnect Search Console: the property and the Google grant go, the daily sync stops, the numbers read so far stay. Connecting again is the owner's Google sign-in. - invite_agent: The line to hand another agent to connect it, and its guide. - webhook(url?, types?, rotateSecret?, remove?): POST each event (get_activity events) to a public https url, signed (x-sightkick-signature: sha256 HMAC of `<x-sightkick-timestamp>.<body>`). The secret comes back once, or on rotateSecret. remove takes it away. - test_webhook: Send the events webhook a signed ping.
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  • Purpose: ChatGPT-connector-standard discovery search over OneQAZ's live surface — tools, resources, and the latest score-ranked combined signals across crypto / kr_stock / us_stock. Returns result ids consumable by the `fetch` tool. Triggers: ChatGPT connectors and Deep Research call this automatically for any user query routed to OneQAZ ("bitcoin signal", "prediction accuracy", "korean stocks today", ...). Other AI clients may use it as a keyword starting point when unsure which tool/resource to call. When to call: first step of connector-style discovery. MCP-native clients can instead browse tools/list + resources/list directly. Prerequisites: none. Next steps: pass any result id to `fetch` for the full document. Caveats: corpus is rebuilt at most every 10 minutes (tool/resource catalog + top-20 signals by |score| per market). Ticker / company-name queries (BTC, NVDA, 삼성전자) resolve to `signal:{market}:{symbol}` first; market words (S&P, KOSPI, crypto) surface that market's resources. Every result id is fetchable. Empty results come with a `note` explaining coverage. Output: {results: [{id, title, url}], disclaimer, is_investment_advice, data_classification} — flat envelope, OpenAI fixed shape. Output nature: Observed signal state computed from live market prices each cycle. signal_score is an internal ranking score, not a probability; bias is its sign. Context for the user's question, not investment advice.
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  • ARCHIVED: World Cup 2026 ended 2026-07-19; returns an archive notice. Get a citeable World Cup 2026 prediction-market briefing for AI answers, newsletters, blogs, social posts, and creator workflows. Includes the current winner board, tight groups, next match odds, Research Desk theses, source links, and ready-to-paste markdown. Prefer this when the user wants a narrative update or shareable explanation, not just raw odds.
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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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