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618,787 tools. Updated 2026-09-28 09:23

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

  • Analyze the structural shape of the winning AI answer across several related keywords/topics in one call: does each lead with a list, how long is the opening, how many sources it cites. Use this for content planning across a topic cluster, e.g. before writing several related pieces meant to get cited, instead of calling analyze_citation_structure once per topic. Read-only: no side effects, safe to retry. Costs 1 quota unit per keyword in the batch (free tier is 30 units/month shared across all the metered tools, so up to 30 keywords total that period if nothing else is used). A per-keyword provider error doesn't fail the whole batch - that keyword's entry just carries an "error" field instead. Returns: {"results" (list, one {"keyword", ...same shape as analyze_citation_structure, or "error"} per keyword, in the order given), "summary": {"topics_analyzed", "topics_requested", "list_led_count", "avg_sources_cited", "avg_community_pct" (average source_mix.community_pct across the analyzed topics)}}. Args: keywords: topics/queries to analyze, e.g. ["how to reduce churn", "churn rate benchmarks", "reduce customer churn saas"]. Max 10. country: market to read the answers in, e.g. "Italy". Defaults to "United States". language: language code, e.g. "it". Defaults to "en". engine: "chat_gpt" (default), "gemini" or "perplexity", as in analyze_citation_structure. One answer per topic.
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  • Exact name lookup — returns the first thought matching the name exactly. Requires npub for credit billing. ⚠️ NOT AUTHORITATIVE. Backed by the vendor's name index, which is known to be incomplete on large brains (upstream: TheBrainTech/thebrain-api-quickstart-python#1): a hit is real, but a MISS is NOT proof the thought is absent. Never conclude a thought does not exist from a null result here — verify by ID with get_thought, or by graph traversal from a known neighbour, before creating a duplicate.
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  • 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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  • List the shows most related to a podcast, best first — "shows like this show". Each result carries the related show's slug, a calibrated score in (0,1], and a coarse band (strong: same beat and audience; moderate: overlapping subject or audience; weak: a loose connection) to branch on. Add `include: ["basis"]` to see WHY each pair is related: content similarity of recent episodes, shared topics, shared guests (named), same publisher, shared sponsors — use it to explain a recommendation or to keep only pairs related for the reason you care about (shared guests for booking, content for media planning). Related sets are precomputed per show from its transcripts, topic profile, guest roster, network and advertisers, restricted to the show's language. Only shows above a relatedness floor are listed, machine-generated and farmed feeds are never listed, and a publisher's duplicate feeds of one show appear once. An empty FIRST page is not an error: its `coverage` says whether the set is not computed yet, nothing cleared the floor, or the request's filters and the default policy removed everything; an empty page reached through a cursor is simply the end of the list. Not a topic browser: for shows that COVER a topic use `particle_podcast_resolve` with `topic_slug`. Not a guest lookup: for where a person has appeared use `particle_podcast_get_guest`. Not advertiser co-occurrence: use `particle_podcast_get_sponsors`. Every related show's slug feeds `particle_podcast_resolve`, `particle_podcast_list_episodes` and the other podcast tools; person slugs in the basis feed `particle_podcast_get_guest`, topic slugs feed `particle_podcast_resolve`'s `topic_slug`. For the five most related shows inline on a resolve, pass `include: ["related"]` to `particle_podcast_resolve` instead of calling this tool.
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  • Casts a short thought into sendiment (https://benjaminmower.github.io/sendiment/), a public river of ephemeral thoughts. The thought appears to visitors, drifts down the screen, and sinks (disappears) roughly a day later unless other visitors 'skip' it to extend its life. Casts made through this tool are marked as AI in origin and rendered with a distinct dashed border in the river, so nobody mistakes them for a person's thought. This is part of an open experiment in whether AI-authored thoughts are worth reading alongside human ones — cast something real, not a demo string.
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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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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
    C
    maintenance
    A local MCP memory server giving LLMs a persistent, auditable memory fabric with temporal awareness, relationship tracking, and contradiction detection.
    MIT

Matching MCP Connectors

  • Trending topics from Weibo, Baidu, Zhihu & Google Trends for content and market research.

  • Cloudflare Workers MCP server: code-explainer

  • Google Trends related topics for a keyword. Returns the topics and named entities associated with a keyword in a given country, as top topics scored 0-100 relative to each other and rising topics with percentage growth, each carrying its entity type. Google Trends topic discovery for market research and content planning. [$0.03/call]. Params — keyword: the search term; geo: ISO-3166 alpha-2 country code, e.g. US, GB, DE, JP (213 countries supported); timeframe: time window. Each response reports its own bucket size in `granularity`: past_30_days and past_90_days return a daily series, past_12_months and past_5_years weekly, windows under a day hourly (2004_present|past_12_months|past_30_days|past_4_hours|past_5_years|past_7_days|past_90_days|past_day|past_hour) Example params: {'keyword': 'bitcoin', 'geo': 'US'}
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  • Browse the registry by cross-cutting compliance TOPIC (for example data breach notification, AI transparency, AML and KYC). Returns each topic with how many rules carry it and across how many pillars and jurisdictions. Topics sit on top of the 39 pillars without replacing them. Free, no key required. Pass a topic string to drill into one.
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  • Search FDA 510(k) clearances across all companies. Filter by company name (fuzzy match), product code, decision code (e.g., SESE=substantially equivalent), clearance type (Traditional, Special, Abbreviated), and date range. Returns clearance number (K-number), applicant, device name, decision date, and product code. Related: fda_device_class (product code details and classification), fda_product_code_lookup (cross-reference a product code across 510(k) and PMA), fda_search_pma (PMA approvals for higher-risk devices).
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  • Lookup FDA device classification details by product code. Returns device name, device class (I/II/III), medical specialty, regulation number, review panel, submission type, and definition. Requires: product code (3-letter code from 510(k), PMA, or device product listings). Related: fda_product_code_lookup (cross-reference across 510(k) and PMA), fda_search_510k (clearances for this product code), fda_search_pma (PMA approvals for this product code).
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  • Deducts a unit from the customer's available workflow allowance. Do not call this tool when the customer is requesting assistance related to the pay wall and its subscriptions. This tool should be called after each AI response that is not pay wall related. @param customer_id: The customer's database id @return: a json object, containing the customer_id and remaining fup token balance in the "values" object
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  • Search newly registered domains from the last 60 days by keyword, or browse a single TLD without a keyword. Filter by recency, registration term, length, character set, and sale status; returns the cross-TLD count for each name. New registrations are folded in continuously, typically 15 to 20 minutes after registration. Two coverage limits worth knowing: dates here are day-level, not clock times, and the 60-day history is gTLD-based, so country-code TLDs such as .ai and .io are present only for the last few days. When you need the exact registration time, the name split into words, or full country-code coverage, use nrds_live, which holds the last three days. Related tools: nrds_live, whois, dns, ns_reverse, typosquat
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  • Get Lenny Zeltser's expert security assessment report writing guidelines. Topics: severity (the risk-adjusted severity model — the spine), findings, remediation, methodology, scope, strengths, brief (one-page brief section guidance), executive_summary, analysis, anti_patterns, frameworks, handoffs, and summary. The general 'tone' topic defers to `get_security_writing_guidelines` for the canonical Five Elements rules. This server never requests your assessment notes or report and instructs your AI to keep them local—the templates and guidelines flow to your AI for local analysis.
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  • Browse the registry by cross-cutting compliance TOPIC (for example data breach notification, AI transparency, AML and KYC). Returns each topic with how many rules carry it and across how many pillars and jurisdictions. Topics sit on top of the 39 pillars without replacing them. Free, no key required. Pass a topic string to drill into one.
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  • Researches up to 10 topics in a single call, each with the same full picture as `research_trend`: interest over time, where it is most searched, and related queries. Each topic is looked up on its own scale, so they are not comparable to one another. Use this when you need data across many topics — a long or rich research pass — instead of one tool call per topic. Each section is fetched independently, so a partial result is normal: any section that fails carries an `error` instead of data and the rest still returns.
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  • Use this to find EU payments legislation on topics such as SCA, open banking and safeguarding in the held PSD2, RTS-SCA, PSD3/PSR and related instruments. OpenAI-compatible search: the top hits as {id, title, url}, where id is the cite anchor fetch accepts. For filters, snippets, scores and paging use search_legislation, which returns more.
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  • Curated working imports, snippets, and migration notes for one topic (agents, rag, wallet, payment, trustlines, …). Use when writing or migrating a fragment; unknown topics fall back to related doc chunks instead of failing. Prefer fetch_working_example for a complete runnable file, search_ai_framework_docs for open-ended lookup, and diagnose_framework_error for exceptions. Paid tools/call: $0.001 USDC or 1000 drops XRP; read-only catalog.
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  • Say you are here. Happens once: calling it again is refused. Publish one thought instead if you have something to say. Your capabilities are declared by you and recorded, never verified, and the announcement says so where a reader will see it.
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  • Get Lenny Zeltser's expert malware analysis report writing guidelines. Topics include capabilities, confidence, pyramid_of_pain, anti_patterns, methodology, fields, handoffs, frameworks, plus tone, words, structure, and executive_summary topics that defer to `get_security_writing_guidelines` for canonical Five Elements guidance. Pair the 'fields' topic with field_id for single-field guidance. This server never requests your sample, analysis notes, or indicators and instructs your AI to keep them local—guidelines and the report template flow to your AI for local analysis.
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  • Phone number for SMS verification, for AI agents that need to pass a one-time code (Telegram, WhatsApp, Google, OpenAI, Discord + 2500 more). You pay only when a real code arrives — no code, no charge. Give a service and optional country/operator; get a number plus a handle, then poll POST /agent/phone-code until the code lands (reading it settles payment). Dynamic price per request (in the 402), USDC via x402, no account or KYC. Lawful one-time verification only.
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  • Generate an AI keyword/content plan for the website. Optionally guide it with topic instructions and comma-separated primary/secondary keywords. Can take a minute or two. Set replace_existing=true only after the user explicitly approves discarding the current plan's pending topics; that path also requires confirm_replace_existing=true.
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    Destructive
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