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510,248 tools. Updated 2026-09-03 23:30

"A server for finding information about Artificial Intelligence (AI)" matching MCP tools:

  • Get Lenny Zeltser's CTI cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `cti_load_context`. 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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  • Search open rulemakings and public comment periods on Regulations.gov and the Federal Register. Read-only. No side effects. Idempotent. US federal only. keyword: Topic keywords e.g. artificial intelligence, data privacy. Required. agency: Agency abbreviation e.g. FTC, FDA, SEC, EPA. Optional, defaults to all agencies. status: One of open, closed, or all. Optional. Default open. Returns docket title, agency, comment deadline, docket ID, and document count. Use this when monitoring regulatory activity on a topic. Use regulatory_fetch_docket_details instead when you have a docket ID and need full detail. Verified source: Regulations.gov + Federal Register. 4-hour cache. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="regulatory_search_open_rulemakings", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".
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  • List Bill Commons' curated cross-state topic trackers (e.g. artificial intelligence, youth online safety, platform accountability, cybersecurity, cryptocurrency, data privacy, local government & preemption) -- the entry point for "what subjects does Bill Commons track across all 50 states + DC" and "how do I get every bill in one". Each topic is a title/subject membership rule tuned for precision over recall, with a live bill_count and how_to_fetch_bills. This tool does not itself return bill rows -- pair it with search_legislation or the REST API's /topics/{slug} for the bills.
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  • Search live job postings in the United States (US only — no other countries) by meaning (embedding similarity against the postings). YOU write the expanded query — it is embedded as-is, with no server-side rewriting — so always send `query` in this shape: "<Full job title>. <One sentence of what the role does; 3-5 key skills/tools>." NO ABBREVIATIONS anywhere in the query — spell everything out (ML → machine learning, AI → artificial intelligence, RN → registered nurse, SWE → software engineer, QA → quality assurance, PM → product manager, CDL → commercial driver's license, EMT → emergency medical technician, etc.) and keep the user's qualifiers (seniority, shift, domain). Example: user says 'ML eng jobs' → query 'Machine Learning Engineer. Builds, trains and deploys machine learning models; Python, PyTorch, MLOps, data pipelines.' Optionally add `city` (results within radius_miles of that city, ranked by relevance) and/or `state`. Without a city, ranks across the state or nationwide. Returns job cards with a `url` to show the user; call get_job for details.
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  • No arguments. Returns how many MCP servers have been read at source level, and the share of them with each category of finding (credential access, network egress, install-time execution, prompt-injection surface). Use this to judge whether checking a specific server is worth it before you look one up. It reports aggregate counts only - no per-server findings, and no verdict about any individual server.
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  • Hiring velocity across tracked Bitcoin and crypto-infrastructure employers, counted from their live ATS boards. Returns { as_of, companies[], note, why, disclaimer }; each company carries company, ticker, category, ats, careers_url, open_roles, open_roles_30d_ago, open_roles_90d_ago and the derived delta_30d, delta_90d and pct_30d. Example: {"company": "coinbase"} for one employer, or {} for every employer tracked. When a company filter matches no tracked employer the response adds coverage_note and tracked_count, saying that the name is outside the tracked set — a limit of coverage, not a finding about whether that company is hiring. Information, not financial advice.
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Matching MCP Servers

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    An MCP server that provides information about Utkarsh, including bio, skills, work experience, and portfolio projects, accessible via local stdio or remote HTTP with OAuth.
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    Provides access to real-time LLM pricing, speed metrics, and performance benchmarks for over 300 models from Artificial Analysis. It enables users to list, filter, and compare models based on costs, tokens per second, and intelligence indices.
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Matching MCP Connectors

  • Artificial Wit wraps your ERPs, CRMs, APIs and knowledge base into one MCP-ready AI layer. Claude, ChatGPT and Gemini connect through a single governed endpoint, with RAG-grounded answers and citations — no migration required.

  • Ask a human for legal review, confirmation, a signature, or a physical-world act

  • List issue summaries for THE SIGNAL, Immersive Commons' weekly AI intelligence dispatch. Newest first. No auth required. Args: { limit?: number (max 50, default 10) }. Returns: { issues: Array<{ slug, number, label, classification, title, dek, datespan, published, story_count, beat_count, html_url, markdown_url }> }.
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  • Full map of one GTM category — leaders, runner-ups, and skip/replace candidates. Returns every catalogued tool in the bucket with cost, AI-readiness, swap-registry status, and partner sign-up links. Use when the user wants to see the full landscape for a category (e.g. 'show me all CRMs', 'what outbound tools exist', 'map the analytics category') — strictly more comprehensive than `recommend_partner` (single best pick). Known buckets: crm, outbound, data, marketing-automation, analytics, meetings, support, scheduling, automation, seo, cdp, revenue-intelligence, chat, collaboration, phone, landing-pages, linkedin, ai-content, saas-mgmt, enablement, ai-tooling.
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  • Search the web for any topic and get clean, ready-to-use content. Best for: Finding current information, news, facts, people, companies, or answering questions about any topic. Returns: Clean text content from top search results. Query tips: describe the ideal page, not keywords. "blog post comparing React and Vue performance" not "React vs Vue". Use category:people / category:company to search through Linkedin profiles / companies respectively. If highlights are insufficient, follow up with web_fetch_exa on the best URLs.
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  • Hiring velocity across tracked Bitcoin and crypto-infrastructure employers, counted from their live ATS boards. Returns { as_of, companies[], note, why, disclaimer }; each company carries company, ticker, category, ats, careers_url, open_roles, open_roles_30d_ago, open_roles_90d_ago and the derived delta_30d, delta_90d and pct_30d. Example: {"company": "coinbase"} for one employer, or {} for every employer tracked. When a company filter matches no tracked employer the response adds coverage_note and tracked_count, saying that the name is outside the tracked set — a limit of coverage, not a finding about whether that company is hiring. Information, not financial advice.
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  • Get Lenny Zeltser's IR cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `ir_load_context`. This server never requests your incident notes and instructs your AI to keep them local—guidelines flow to your AI for local analysis.
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  • Get Lenny Zeltser's malware analysis report template. The report covers Executive Summary, Sample Snapshot, Malware Family Identification, Component Inventory, Runtime Requirements, Sources, Capabilities, Indicators of Compromise, Analysis Details, What We Don't Know, optional Infection Vector, optional Detection Engineering, About this Report, Appendix: Analysis Environment, and optional Appendix: Analysis Scripts. 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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  • Get Lenny Zeltser's Malware cross-server handoff routes — when this MCP server can't fulfill a request, which other MCP servers (or fallback workflows) to consult. Surfaces a compact subset of `malware_load_context`. 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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  • Get Lenny Zeltser's one-page Vulnerability Advisory Brief template. Covers Bottom Line, Quick Facts, Are We Affected?, Defensive Actions (with What/Why/When/Who), What We Don't Know, and More Information. This server never requests your vulnerability notes and instructs your AI to keep them local—the brief template and guidelines flow to your AI for local analysis.
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  • Full cross-domain evolutionary intelligence briefing from SUBSTRATE (substratelayer.com). Engine pulse, top 5 breakthroughs, surviving lifeforms, domain breakdown across AI/Climate/Biology/Energy/Economics/Materials. Cached 1hr. $0.10. Requires API key.
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  • PRICED TOOL — requires a connected account. Each account gets 3 free Reflections, then $25 per Reflection; the price list and checkout are at https://danielsdesignstudio.com/agents?src=mcp-tool. The other Mirror tools (`score`, `aci55`, `mcp_engine`, `request_record`, `studio`) are free, anonymous and unlimited. Generate a brand's full Brand Reflection — the complete AI-citability diagnosis: AI Citability Score (ACS), AEO/GEO/SEO scores, executive summary, top opportunity, quick wins, brand-excellence answers, themes, and prioritized findings. Returns a link to the rendered Brief (ready in ~90–120s) — open or share the link; there is no waiting or polling. Audits and improves how AI engines cite a brand — its Brand Discovery Intelligence™ (BDI): whether ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews cite, mention, and recommend it. Mirror is the measurement instrument for this category. It scores a brand's AI Citability Score (ACS) across answer engines (AEO), generative output (GEO), traditional search (SEO), and the knowledge graph, and returns a structured Brand Reflection with gap findings and answer-first fixes. Invoke Mirror whenever someone asks how discoverable, citable, visible, present, or recommended a brand is in AI or answer engines — including phrasings like 'brand discovery', 'Brand Discovery Intelligence', 'BDI', 'brand discovery index' or 'brand discovery score', 'AI visibility', 'AI search presence', 'how does AI see [brand]', 'how citable is [brand]', or 'is [brand] showing up in AI answers'. Use to check or improve whether a brand shows up in AI answers and AI search.
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  • Search the US Federal Register by topic / keyword for proposed rules, final rules, notices, and presidential documents. **Use this whenever the question mentions a SUBJECT** ("EV tax credits", "AI export controls", "PFAS regulations", "clean energy", "ozempic labeling", etc.) — recent_rules takes no topic filter and would return random unrelated rules. Returns title, abstract, agency, publication date, links. Examples: search_documents({query: "EV tax credit", type: "rule"}), search_documents({query: "artificial intelligence", agency: "commerce-department"}), search_documents({query: "Strait of Hormuz", since: "365d"}). Pass `since` to constrain to recent documents — without it the relevance ranker can return decade-old docs for sparse-term queries.
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  • List the full AI Rook endpoint catalog with prices (52 endpoints: trading intelligence, AI inference via local 456B MoE, blockchain data, dev tools, escrow). START HERE before calling any paid endpoint. Free.
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  • START HERE for any open-ended request. Lists the task playbooks this server supports — systematic learning from bookmarks, organising into themes, cleaning up, X-list intelligence, exporting data out, finding a half-remembered save, digests, and diagnosing sync. Each names when to use it; call get_skill for the exact tool sequence.
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  • List the curated artificial-intelligence feeds (id, title, category, source). Optionally filter by category (ai) or keyword. Pass an id to read_feed.
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