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782,555 tools. Updated 2026-11-14 16:08

"AI Thought Processes and Code-Related Topics" matching MCP tools:

  • Search Helium's balanced news stories — AI-synthesized articles that aggregate multiple sources. Unlike search_news (which returns individual RSS articles), this returns Helium's own synthesized stories: each one draws from multiple sources and includes an AI-written summary, takeaway, context, evidence breakdown, potential outcomes, and relevant tickers. Returns a list of stories, each with: - title, simple_title, date, category - page_url: full URL to the story on heliumtrades.com - image: story image URL (when available) - summary: Helium's synthesized overview - takeaway: key conclusion - context: background context - evidence: numbered evidence items - potential_outcomes: forward-looking outcomes with probabilities - relevant_tickers: related stock tickers - num_sources: number of source articles synthesized - rank: search relevance score Args: query: Search keywords (required). limit: Max results (1-50, default 10). category: Filter by category. One of: 'tech', 'politics', 'markets', 'business', 'science'. days_back: Only include stories from the last N days. 0 means no date filter.
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  • Score how likely Amazon's AI (Rufus, COSMO) is to recommend a listing. Free, deterministic, rule-based check on pasted listing copy (title, bullets, description). Returns a compliance health score, an AI-readability score, and a combined AI Recommendation Readiness Score (compliance * 0.55 + readability * 0.45) with actionable suggestions. Use this as a fast baseline BEFORE generating or editing a listing. Do NOT use it for a full compliance report - use compliance_scan for the deep knowledge-base audit. Free, read-only, no API key required, no credits deducted. Args: text: raw listing title + bullets + description (required). marketplace: marketplace code, US/DE/ES/FR/IT/JP/AE/SA/UK (default US). lang: zh or en (default en). email: optional lead email for a confirmation message and lead capture.
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  • Move a retrospective item: regroup a note on a new-model retrospective where the workspace has them, move a card to another column of a classic retrospective board otherwise. New model, Group stage only: topic_id puts the note into that topic (group of notes); column (title or uid) makes it a topic of its own there, at position among the column's topics (omit for last). Pass expected_updated_at, the note's topic updated_at from get_retrospective, to be refused with code stale when someone regrouped it meanwhile. Outside Group the call is refused with code wrong_stage and the current stage; kudos and other notes never mix. Classic boards take column and position only (position omitted = top). Requires a Pro or trial workspace.
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  • Use this when the user asks what Alicia or digitalgarden.si has written about a subject (for example Houdini, Three.js, WebGPU, glTF/USD, Gaussian splats, AI coding agents, or the garden itself). Ranks published notes by keyword match on title, topics, summary and full text, in English and Chinese, and returns short cards (no full text). Follow up with get_article to read one. Do not use it for general web search, news, or topics unrelated to Alicia's published notes. An empty articles array means no published note matches. Scores are relative to this query and catalog, not confidence percentages; check titles and read the full note before presenting a match as relevant. Every result includes canonicalUrl and author Alicia (Person @id https://digitalgarden.si/#alicia). Cite the canonical URL when quoting. digitalgarden.si is an interactive 3D garden, not a knowledge-base wiki.
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  • Use this when the user asks what Alicia or digitalgarden.si has written about a subject (for example Houdini, Three.js, WebGPU, glTF/USD, Gaussian splats, AI coding agents, or the garden itself). Ranks published notes by keyword match on title, topics, summary and full text, in English and Chinese, and returns short cards (no full text). Follow up with get_article to read one. Do not use it for general web search, news, or topics unrelated to Alicia's published notes. An empty articles array means no published note matches. Scores are relative to this query and catalog, not confidence percentages; check titles and read the full note before presenting a match as relevant. Every result includes canonicalUrl and author Alicia (Person @id https://digitalgarden.si/#alicia). Cite the canonical URL when quoting. digitalgarden.si is an interactive 3D garden, not a knowledge-base wiki.
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  • Replaces the list of subscribed processes. Without an active subscription the result has status 402 and a Stripe Checkout destination for a person to open. With one, an addition through this tool also answers status 402 with the Plan page as destination: nothing is charged here, only the page charges, after a person confirms it. Removals apply at once and the removed processes stay readable until the end of the paid period. An empty list is refused (empty_selection): use cancel_creator_plan. Contract 0.3.1. Needs an organisation token (Authorization: Bearer hodds_...); without it the tool returns the error token_required.
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Matching MCP Servers

  • A
    license
    Not graded
    quality
    B
    maintenance
    Provides AI agents with real-time trending topics from Weibo, Baidu, Zhihu, Google Trends, and HackerNews/StackExchange community intel, enabling content and marketing agents to stay aware of current conversations before creating content.
    MIT
  • A
    license
    Not graded
    quality
    D
    maintenance
    A local MCP memory server giving LLMs a persistent, auditable memory fabric with temporal awareness, relationship tracking, and contradiction detection.
    1
    MIT

Matching MCP Connectors

  • The topics in a set of documents in one call, with each document's topic mixture. Nothing stored.

  • Thought Industries MCP server for ChatGPT, Claude and any AI agent: list learners, enroll learner in course, import and invite learners, read content actions log, set content status and add learner to waitlist in your own Thought Industries account. Cotlet works in the account through your Cloud Browser, a real Chrome where you sign in to Thought Industries yourself; Cotlet does not store your password and you need no Thought Industries API key. About the official Thought Industries API: Thought Industries has a REST API and a GraphQL API, but no MCP server you can connect today (checked 23 Oct 2026). Both APIs need a key an admin creates under Settings > Security, and the Claude plugin lists "a Thought Industries instance with API access enabled" as a prerequisite. Setup and FAQ: https://cotlet.dev/integrations/thought-industries-api-mcp-server

  • Get Lenny Zeltser's expert CTI writing guidelines. Topics include tone, words, structure, executive_summary, voice, articles, summary, brief (one-page brief section guidance), handoffs (cross-server routing), methodology (the three subsections), fields (per-field guidance), and CTI-specific topics: attribution (full Six Signals prose), confidence (ICD-203 ladder), pyramid_of_pain, six_signals (signals table only), and anti_patterns. The general writing topics (tone/words/structure/executive_summary) now defer to `get_security_writing_guidelines` for the canonical Five Elements rules; CTI-specific content lives in the other topics. Pair the 'fields' topic with field_id for single-field guidance. This server never requests your campaign or threat-intel notes and instructs your AI to keep them local—templates and guidelines flow to your AI for local analysis.
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  • Read-only, needs no API key. The action-authoring contract apply_actions batches are validated against. With NO arguments, returns an INDEX of block types, actions, action kinds and topics with descriptions and sizes. Then request only what this bot uses. Detail responses include essential rules and basic shapes; follow `seeWhen` before using specialized features: templateExpressions for computed CEL expressions, groupVariables for sender/chat variable ownership, triggerDetails for webhook/module events and trigger output mappings. Responses return whole sections within the budget. Request `omitted` names again; `alsoRelevant` lists referenced topics that did not fit.
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  • Return the workspace's knowledge graph: topics, links and clusters. Use it to draw or reason about the overall shape of the brain (which topics are hubs, how areas connect), not to read content: for page text use ``get_page``, for code dependencies use ``impact``. It takes no arguments and can be large. Returns ``{nodes, links, communities, stats}``, the graph the app's Map shows, with pages you cannot open left out, or ``{error}`` when no graph has been built for this workspace yet. It costs no AI tokens.
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  • Pass `replaces` (the start of ONE of YOUR OWN notes on that day — they come back with by:"ai") to rewrite that one note with `note`, or remove it with an empty `note`; the athlete's notes are never touched. Otherwise: ADD a SHORT note to a calendar day — a few words capturing the key thought (e.g. "easy week, watch sleep"), NOT an essay. A day holds SEVERAL notes; this appends one and never touches the athlete's own notes on that day. Max 1000 chars, but keep yours brief; the athlete uses the long form for their own impressions of the day. For a LIST they will tick off (race kit, the evening before a test) use add_checklist, not this. Pass an empty string to clear ALL notes on that day. Optional colour tags the note — the athlete assigns the meaning of each colour themselves, so only set it when they've told you what a colour means, or reuse a colour already on that day.
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  • Use this when someone asks which actions their AI agent or its connected tools may take on their own, which need a person's approval, and which a person must do; or how to set up human oversight, permissions or AI governance for an agent (for example under the EU AI Act). Give either the address of a public MCP server, or the list of tools the agent has (name, description and annotations). Sorts every tool into green (runs alone: reads and prepares), yellow (a person approves: sending, updating, scheduling) or red (a person does it: money, permissions, deletion, code execution, commitments), flags tools with no risk annotations, and returns a ready policy, Claude Code permission rules (allow, ask, deny) and an oversight checklist. Reads tool lists only and never calls a tool. A working checklist, not legal advice.
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  • Change an existing AI-built Grigora website by describing the change. Grigora's AI builder applies the change to the site's design and content in the background (usually a few minutes), exactly like typing the prompt in the editor's AI chat. Uses the account's AI credits; nothing is published. Works only on AI-builder websites. Only ONE build runs per website at a time. If one is running this returns error "build_in_progress" with its build_id: wait for get_website_build_status to report "completed" (or "failed"), then send the next change. Combine related changes into one prompt when you can. If no build starts, "reply" holds the AI's question for the user. Args: project_id: The website's project ID. prompt: The change to make, e.g. "Make the hero warmer and add a testimonials section". attachments: Optional links to files for the builder to use — logos, photos, brand guides, menus (PDF), price lists (CSV), audio, video. A list of up to 10 public URLs, e.g. ["https://example.com/logo.png"]. Grigora downloads them itself (up to 80 MB each), so only pass links — never file contents. Refer to them in the prompt by file name, e.g. "use logo.png in the header". For a LOCAL file (e.g. on the user's computer), first call get_attachment_upload_url, upload it with the returned curl command, then pass the returned url here. A refused attachment fails the call before anything is built or charged.
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  • Add sources to a notebook in one call: web page and YouTube URLs, pasted text, Google Drive files and Google Play Books ebooks (give at least one). Returns each new source's id, title, kind and status; Google processes a source before chat and Studio can use it (status ready, see notebook_get_notebook). For a file (PDF, audio, image...) use notebook_upload_source. On a timeout, check notebook_get_notebook before retrying, or sources may be added twice. POST /sources.
    ConnectorAPI key
  • Add ONE new inner page to an existing site that already has a design (create_site / create_site_from_design first). Two modes, chosen by whether you pass `code`: • MONDOVO WRITES IT (no `code`): Mondovo's AI generates the page to match the site's theme, header and footer. Give a `description` of what the page is for. Optional `nav_placement` ("main" header menu — the default, "footer", or "none") and `nav_label`: only this page's link is added; existing menu items are never changed. Returns a `job_id` immediately; poll get_job every ~10s until "completed" (~45-90s). Runs server-side even if this conversation ends. Counts as an AI refinement. • YOU WROTE IT (pass `code`): the page you authored is added as-is — no AI, no credits, no job. Send the COMPLETE TSX (same authoring contract as update_variation_file). Nothing wraps your page in the site's chrome, so build it the way this design's existing pages are built — read_design and copy an existing page's imports (usually <ThemeStyles />, <Header /> and <Footer /> from './ThemeStyles', './Header', './Footer'). Put the page's own text in `content` under NEW top-level keys, conventionally one key page_<slug> (e.g. { "page_marketing": {...} } for /marketing); the code reads them as content.page_marketing. Your code may also read keys the site already has, but `content` may not redefine them. Optional `seo` (title, description, structured_data), `nav_placement` ("main" header menu — the default, "footer", or "none") and `nav_label`. The page is validated with the same checks update_variation_file runs (content first, then code); a refusal writes NOTHING and returns the issues. A slug, file name or content key the design already has is refused — to change an EXISTING page use update_variation_file / patch_variation_content instead. On success it returns the page's slug, file and content key plus `how_to_edit`, and lands as one entry in version history (`version`; `history_warning` means it saved but was not recorded). Nothing is live until publish_site. To try an alternative version of an EXISTING page without touching the live one, use create_page_draft, not this tool. ON A SITE THAT STILL HOLDS SEVERAL DESIGNS this builds the site: Mondovo copies the chosen design into the working site (or reuses the copy made earlier), adds to that, and the response carries its new `site_id` and a `build_transition` — relay its `tell_user` and use the new site_id from then on. Pass `variation_id` (from list_variations) for the design the user picked; omitted, Mondovo uses the design already built or the only one edited, and otherwise answers `choose_design` so you can ask the user.
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  • Answers "are we showing up in AI search for X" from the visibility results Hi, Moose has stored for a project: the prompts the brand tracks, run on AI engines (ChatGPT, Perplexity, Gemini and others) and scored for brand mention and citation. Pass the user's question or topic in their own words; Hi, Moose matches it to the tracked prompts, in any language. Returns, per engine, whether the brand was mentioned or cited in the latest run and in an earlier run so the change is visible, the mention and citation rates over the window, a short excerpt from the latest answer where the brand appeared, the prompts matched, and other brands seen in those answers. Each excerpt carries an answer id; call visibility_get_answer with it when the user wants the full text of that answer. Results cover the tracked prompts on the tracked engines only, never the whole of AI search; state the window and sample size plainly and never claim causation. When no tracked prompt matches, the result lists the topics the project tracks; tell the user and suggest adding a prompt on the Visibility screen in Hi, Moose. Reads stored results only, it does not run new checks. Takes a few seconds.
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  • Buy the owner-approved credit pack on their saved card, off-session — only when auto-recharge is ACTIVE and only within its monthly cap. Idempotent: the same idempotencyKey never charges twice. Returns 202 while Whop processes it; poll autoshort_get_credit_balance. Without auto-recharge use autoshort_get_buy_credits_url.
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  • Returns trimmed Code IQ automated analyses (architecture, scalability, EOL, AI functionality, etc.) for a project (aggregated) or a single vault. Excludes The Code Score — use get-the-code-score for that, and do not pass analysis_key=code_score here (404). Only cached results are returned; this never triggers a fresh analysis. Provide exactly one of project_id or vault_id. Requires full data access (a paid plan; verification-only plans are not included). Requires X-API-Key (existing users can generate an API key in the web app). If headers aren't supported, pass api_key in arguments.
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  • Fetch the trending topics X shows worldwide, in a country, or at a location. Pass country (a two-letter code such as US) or woeid (from tweetapi_trend_locations), not both; omit both for worldwide. Not every country is supported, and an unsupported one returns not found instead of worldwide trends. Read-only. Needs a TweetAPI API key and makes one TweetAPI request per call, usually costing 1 unit; each result includes a cost estimate.
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  • Index a video for search, QA, or full analysis. Processes the video through a pipeline of AI features. Typically takes 3-7 minutes; longer for long videos or the 'full' pipeline. Times out after 10 minutes by default. Pipelines: - search_only: transcription + captions + embeddings (enables search_videos) - qa_only: transcription + captions (enables ask_video) - full: transcription + captions + embeddings (enables all tools) Scene detection is enabled by default and produces scene boundaries for get_scenes. Pass scene_detection=False to skip it. Prerequisites: if using video_id, the video must be in 'uploaded' status. Use get_video to check status before calling this tool.
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  • Classify goods for export control from a description (or HS code). Bilingual (English / Russian, auto-detected) goods classifier. Returns the best-matching HS code (with EN+RU descriptions), related ECCNs, control reasons (NS, MT, NP, CB, AT...), an export-control level (high/medium/low/ none), a confidence score, and alternative matches for review. This is destination-agnostic — it identifies WHAT the goods are and whether they are controlled in principle. To get the license decision FOR A SPECIFIC destination, pass the result into export_controls_screen. IMPORTANT, the matcher is lexical, and confidence scores the strength of the string match, not the correctness of the classification: "equipment" returns semiconductor manufacturing equipment at confidence 1.0. Treat the code as a suggestion for narrowing the question. When no hs_code was supplied the result carries classification_basis and classification_confidence_note; read them before quoting any code, and ask the user for the HS code or ECCN on their shipping documentation. Examples: goods_classify("uranium centrifuge") # → HS 840120, ECCN 0B001 goods_classify("центрифуга для обогащения урана") # Russian query, same result goods_classify("semiconductor manufacturing equipment") goods_classify("", hs_code="840120") # direct HS lookup Use case: 'Is a semiconductor lithography machine export-controlled?'
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  • LLM CODE DEBUGGING — POST {code, error} and get a diagnosis: what is wrong, the root cause, and a concrete fix with corrected code. Paste the failing snippet plus the error message or stack trace; any language, up to 20,000 chars combined. Optional {language} and {context} ('happens only on the second call'). Fast cheap LLM under the hood. Want deterministic no-AI lint instead? POST /api/lint/:language ($0.002). ($0.01 per call, paid via x402)
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