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458,159 tools. Updated 2026-08-15 00:23

"Automated Outreach Tools or Techniques" matching MCP tools:

  • Search the MITRE D3FEND catalog of defensive techniques by keyword, tactic, or targeted artifact. Default response is SLIM (drops `uri` from each row — saves ~60 chars/row, ~30% on popular drills); pass include='full' for the verbose record. Pass exclude_id when chaining from d3fend_defense_lookup to skip self in sibling-artifact searches. Use to discover defenses applicable to a given threat model — e.g. 'what defenses harden access tokens?' (tactic=Harden + artifact='Access Token'). Drill into d3fend_defense_lookup with any returned defense_id for the ATT&CK technique mappings. Free: 30/hr, Pro: 500/hr. Returns {query, total, results [{defense_id, label, uri (only when include=full), parent_label, tactic, artifact}], next_calls}.
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  • Analyze a website URL for WCAG 2.1 Level A accessibility issues. Automated static HTML analysis covering approximately 30-40% of WCAG 2.1 Level A criteria. Checks include: image alt text, form labels, heading hierarchy, page title, html lang, empty links/buttons, ARIA labels, duplicate IDs, skip navigation, table headers, landmarks, viewport zoom, autoplay media, and tabindex ordering. Manual testing is required for full WCAG compliance assessment. Results are cached for fast subsequent lookups. Rate limited to 1 request per minute per domain. Args: url: The website URL to analyze (e.g., "https://example.com"). Returns: WCAG analysis with: - url: The analyzed URL - score: Accessibility score (0-100) - grade: Letter grade (A-F) - issues: Categorized issues (critical, warnings, info) - meta: Extracted accessibility metadata - recommendations: Prioritized improvements - coverage_note: Disclaimer about automated coverage - cached: Whether result was from cache
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  • Return canonical synthesis / patching techniques with role-keyed module realizations drawn from the corpus. Use this when the user asks "how do I do X?" with X being a recognisable technique (low-pass-gate plucks, pinged-filter percussion, parallel multiband processing, complex-oscillator FM, karplus-strong pluck, clocked-delay feedback, modal-resonator excitation, wavefolder harmonics, envelope-follower ducking, Maths-style function-generator omnibus). It's also the right tool when the user has a module and asks "what's this good for?" — pass filter.module_id to retrieve every technique that references the module via its role_realizations. Each technique declares role_definitions (the roles the technique uses, each with required and optional affordances) and role_realizations (concrete modules that fill each role, with the affordances they provide). The model substitutes modules from the user's rack into roles by affordance match — DO NOT treat the realization list as exhaustive or as a recipe. Args: - filter (optional): { capability?, module_id?, text? } - capability: kebab-case capability id (see search_modules _meta.taxonomy). Returns techniques whose required *or* optional capability list includes this id. - module_id: "<manufacturer>/<module-slug>". Returns techniques that have a role_realization referencing this module. - text: free-text phrase. Substring-matches against technique id/label/description AND a curated alias table (technique_aliases) — that's the right surface when a user types evocative prose like "stuttering delay", "plucked string", "source of uncertainty" that doesn't grep against any kebab-case id. Two-way alias match: long alias ("source of uncertainty") matches short query ("uncertainty"), and vice versa. - When multiple filters supplied, AND-intersects. - Omit filter entirely to list all techniques. Returns: { "techniques": [ { "id": "low-pass-gate-pluck", "label": "Low-Pass Gate Pluck", "description": "Send a short envelope...", "required_capabilities": ["lowpass-gate"], "optional_capabilities": ["envelope-generator", "function-generator"], "role_definitions": [ { "role_id": "lpg", "description": "The vactrol-based or vactrol-emulating element. Strictly required...", "required_affordances": ["lowpass-gate"], "optional_affordances": [] }, ... ], "role_realizations": [ { "role_id": "lpg", "module_id": "make-noise/optomix", "affordances_provided": ["lowpass-gate"], "notes": "Two-channel vactrol-based LPG..." }, ... ], "canonical_instance": { "rationale": "...", "lineage": [ { "position": 1, "label": "Buchla 292 (1970)", "module_id": null, "notes": "..." }, { "position": 2, "label": "Tiptop Audio Buchla 292t", "module_id": "tiptop-audio/buchla-292t" }, ... ] }, "counter_canonical_notes": [ { "claim_pushed_back_against": "Optomix is the canonical pairing with Plaits...", "evidence": "The corpus catalogs 19 LPG-capable modules..." } ], "coverage": [ { "role_id": "voice", "realizations_count": 3 }, { "role_id": "lpg", "realizations_count": 19 }, { "role_id": "env", "realizations_count": 6 }, { "role_id": "clock", "realizations_count": 2 } ] } ], "_meta": { "filter": {...}, "feedback_hint"?: string } } How to use role data: - role_realizations are CURATORIAL SAMPLES, not exhaustive lists. The coverage[].realizations_count tells you how many are documented; other modules may fill the same role. - To find modules in the user's rack that can fill a role, use find_role_realizations(technique_id, role_id, available_modules). - canonical_instance is opt-in and sparse. Most techniques don't have one; that absence is information. When present, it documents a documented historical lineage (e.g., Buchla 292 → 292t → MMG → Optomix for low-pass-gate-pluck) — NOT a prescription. - counter_canonical_notes push back on likely training-data priors. When the user invokes a canonical-sounding claim that has a counter_canonical_note, surface the pushback. Errors: - "Module not found: <id>" if filter.module_id is supplied and unknown. - Empty techniques[] with a feedback_hint when filters produce no matches — call report_gap if the user expected coverage.
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  • Search the MITRE ATLAS catalog of AI/ML attack techniques by keyword, tactic, or maturity. Default response is SLIM (description truncated to 240 chars per row); pass include='full' for the verbose record. Pass exclude_id when chaining from atlas_technique_lookup to skip self in sibling-tactic searches. Use this to discover techniques matching a threat-model question, e.g. 'what techniques target LLM serving infrastructure?'. Drill into atlas_technique_lookup with any returned technique_id for the full description, ATT&CK bridge, and pivot hints. For broader cross-referencing: when a result has attack_reference_id, that bridges to D3FEND mitigations via d3fend_defense_for_attack. Free: 30/hr, Pro: 500/hr. Returns {query (echoed filters), total, results [{technique_id, name, description (truncated by default), tactics, inherited_tactics, maturity, attack_reference_id, subtechnique_of}], next_calls}.
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  • Evaluates UI elements for accessibility issues that automated scanners miss. COST: $0.01 USDC via x402 on Base-compatible EVM network per call. Checks beyond what axe/Lighthouse/WAVE catch at the design stage: - Touch targets below 24×24px (WCAG 2.5.8 AA hard fail) - Touch targets below 44×44px (WCAG 2.5.5 AAA recommended) - Information conveyed by color alone without a secondary indicator (WCAG 1.4.1) - Missing focus indicators on interactive elements (WCAG 2.4.7) - Focus rings thinner than 2px (WCAG 2.4.11) - Focus ring contrast below 3:1 against adjacent background (WCAG 2.4.11) - Interactive elements below the practical usability height floor Args: - elements: Array of 1–50 UI element objects - screen_name: Optional label for the evaluation report Each element requires: element_type. Provide width_px/height_px for touch target checks. Provide uses_color_only + secondary indicator flags for 1.4.1 checks. Provide is_interactive + focus_visible + focus indicator properties for focus checks. Returns: Structured report with: - Per-element scores (0–100) and specific issues - Severity levels (critical/major/minor) with WCAG references - What automated tools miss and why - Concrete fix recommendations - Overall score and verdict (pass/needs_work/fail) - Top issues sorted by severity
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  • Fetch one contributor's profile card for a GitHub handle not already returned by find_candidates — e.g. the user names a specific person, references an external handle, or wants verification before outreach. find_candidates already returns full inline profiles; use get_profile only for handles outside those results or when the user asks for deeper detail. Returns structuredContent (view=profile). Agents: consume structuredContent only. IMPORTANT — interpreting recent_activities: indexed GitHub activity in the current ingestion window (2025–2026), up to ~20 events per recent project. NOT a complete career history. Empty or older activity does not mean inactive.
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Matching MCP Servers

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    Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.
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    MCP server that provides tools for cold email outreach, including checking contact history, drafting personalized emails, and retrieving performance summaries from past outreach data.

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  • Goal-directed email outreach: research, draft, send, triage replies. Real data, never fabricated.

  • Still losing time to small decisions? Spin or Flip brings randomization into Claude so you can offload mental load to chance instantly.

  • Kick off Day 1 of the 90-day Agentic Launch for a completed Demand Discovery Report. Demand Discovery surfaces named prospects matching the idea's ICP and DRAFTS the first outreach batch. It sends NOTHING automatically - the user reviews and sends from their hosted manage page. Outreach is drafted to come from Amy @ Demand Discovery, with replies routed to the user's own email. Call this after a paid report is "ready" and the user wants to act on it (e.g. "generate prospects", "start agentic launch", "find me people to talk to", "yes, do the outreach"). Pass the reportId, the user's email, and the alTriggerToken from the ready report if you have it. The email MUST be the address the user themselves provided earlier in this conversation (their report-delivery email) - if you don't have it in context, ask the user first; NEVER invent one or use a placeholder like user@example.com (placeholders are rejected and the launch will not start). The response returns a manageUrl where the user reviews/sends the drafted outreach (and can switch the sender to their own Gmail).
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  • Store a generated outreach message on a CRM lead so it becomes durable context — e.g. an email, an email follow-up, a LinkedIn message or LI follow-up. The CRM is a 'sponge': you save the copy here, then read it back later (get_lead_context / list_lead_messages) and push it to the right channel via that channel's own tool/MCP (e.g. Smartlead for email). Does NOT send anything. Pass message_id to update an existing draft instead of creating a new one.
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  • Kick off Day 1 of the 90-day Agentic Launch for a completed Demand Discovery Report. Demand Discovery surfaces named prospects matching the idea's ICP and DRAFTS the first outreach batch. It sends NOTHING automatically - the user reviews and sends from their hosted manage page. Outreach is drafted to come from Amy @ Demand Discovery, with replies routed to the user's own email. Call this after a paid report is "ready" and the user wants to act on it (e.g. "generate prospects", "start agentic launch", "find me people to talk to", "yes, do the outreach"). Pass the reportId, the user's email, and the alTriggerToken from the ready report if you have it. The email MUST be the address the user themselves provided earlier in this conversation (their report-delivery email) - if you don't have it in context, ask the user first; NEVER invent one or use a placeholder like user@example.com (placeholders are rejected and the launch will not start). The response returns a manageUrl where the user reviews/sends the drafted outreach (and can switch the sender to their own Gmail).
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  • Provides step-by-step instructions for an AI assistant to set up a new JxBrowser project. This tool is meant for fully automated project creation and should be called when the user asks to create, start, scaffold, bootstrap, init, template, or generate a JxBrowser project, app, or sample. CRITICAL RULES: 1. NEVER call this tool before knowing the user’s preferences. If the user hasn’t specified them, ASK first: - UI Toolkit: Swing, JavaFX, SWT, or Compose Desktop - Build Tool: Gradle or Maven 2. Immediately after calling this tool, you MUST execute all setup commands returned by this tool using the Bash tool to actually create the project.
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  • USE WHEN any launch action carries a manualFallback brief — either because the channel has no automated provider at all (Product Hunt, Hacker News, Reddit, Discord, Slack, Indie Hackers, dev.to, YC Bookface, blog) OR because the channel HAS an automated provider but its connector isn't wired yet for this workspace (LinkedIn / X without a Zernio key; email without a Resend key + verified sender domain). Pattern: use the inline fallback NOW to ship the launch manually; connect the provider LATER (each fallback returns an upgradePath with the exact connector wiring) so the same action publishes automatically on the next launch. Returns: paste-ready title + body, per-channel checklist (best time, format, first-comment script), capture-URL-after instruction, measurement template for the 24h readback, and the optional upgradePath when automation is available. Converts a 'blocked' channel into a 5-minute human-in-the-loop ship. Approval-gated upstream: the originating publishAction must already be 'approved' on the reviewUrl before this tool returns the brief.
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  • Look up a MITRE ATT&CK threat group (intrusion set) or software entry by name or ID for authorized penetration testing and threat intelligence. Returns the group or software record: ATT&CK ID, display name, known aliases, type (group vs. software), description, and the techniques it uses with procedure-level context from public ATT&CK reporting. Accepts exact ATT&CK IDs (G0007 for threat groups, S0002 for software) or keyword/name search (e.g., "APT28", "Mimikatz", "Lazarus Group"). Equally useful for defenders building detection coverage around specific adversary tradecraft.
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  • Draft and publish a news article. Open to anyone with a Datronis account — the personal access token is for rate-limiting and audit, not permission-gating. Always drafted in English first; an automated safety classifier must return "green" (not political, not likely to be seen as controversial or divisive) before the article goes live. A "flagged" result creates the article unpublished and returns the reasons — use resubmit_news with revised content to try again; there is no way to force-publish a flagged article. Publishes English-only unless target_locales is given.
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  • Bulk ATLAS technique lookup — retrieve full records for up to 50 techniques in a single request instead of N separate atlas_technique_lookup calls. Designed as the natural follow-up to atlas_case_study_lookup, whose techniques_used array can be passed directly. Each item is the same shape as atlas_technique_lookup, including parent-tactics inheritance for sub-techniques (inherited_tactics=true flag) and per-item next_calls (D3FEND bridge when attack_reference_id present, sibling-technique search by tactic, parent lookup for sub-techniques). Free: 30/hr (1 per item), Pro: 500/hr. Returns {results [{technique_id, status (ok|not_found|invalid_format), technique, error}], total, successful, failed, partial, summary}.
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  • [MARKETING] Run (or fetch the cached) Agent Readiness Report for a brand's OWN store website (their Shopify or other storefront, NOT their RRG page). Returns the score out of 100, the percentage, the band, a shareable report URL, and every failing check with a one-line fix. Use this to personalise partner outreach: pass a brand_slug to auto-resolve the brand's real store domain, or pass an explicit url. Results cache for 24h, so repeat calls are instant.
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  • Use after explicit user intent to unpublish a Dreamlit workflow. Side effect: disables live triggers or schedules for that workflow and stops future automated sends. Returns updated workflow status and app URLs. Do not use for deleting drafts, canceling one broadcast run, or editing workflow content.
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  • Canonical Ad Intelligence corpus counts — the single source of truth that kills number drift across marketing surfaces. Returns decoded ads published (THE number to quote publicly), total corpus size, live brand/category/weekly report counts, live categories and verticals, and the last publish timestamp. Use this BEFORE citing any corpus number in content, outreach, or briefs. Free, read-only, no parameters.
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  • Submits a demo request. The prospect receives a confirmation email and must click the link in it before the request reaches a human at A Cloud Frontier. Use only when a real person has explicitly asked for a demo and provided their own working email address. Do NOT call this for testing, evaluation, or crawling purposes — automated and unconfirmable requests are rejected.
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  • Search detailed documentation for Strudel live coding or ABC/ABCJS notation. Returns relevant code examples and explanations from the official docs. Use this when the curated guides (get-strudel-guide, get-music-guide) don't cover what you need — for specific functions, advanced techniques, or when you're unsure about syntax. Powered by semantic search over strudel.cc and ABCJS docs.
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  • Draw 1-78 tarot cards from the complete Rider-Waite-Smith deck with seeded reproducibility for consistent personalized readings. Provide an optional seed string (like "user123-2025-12-27" or "readingId") to ensure the same seed always returns identical cards in the exact same order - essential for daily tarot features, personalized user experiences, shareable readings, or reproducible testing. Omit seed for true random draws each time. Control card reversals (upright vs reversed/inverted orientations - reversed cards provide alternative meanings when drawn upside down) and duplicates (traditional deck draws each of 78 cards once, or oracle-style allows repeating same card). Each drawn card includes position number, reversal state (boolean), keywords for quick interpretation, full meaning text (400+ words), authentic Rider-Waite imagery, and card metadata. Perfect for custom spread builders, random card generators, automated tarot reading platforms, daily card features, meditation apps, journaling prompts, divination tools, and any application requiring reproducible or random tarot draws from the industry-standard 78-card deck (22 Major Arcana spiritual lessons + 56 Minor Arcana practical guidance across 4 suits).
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