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524,660 tools. Updated 2026-09-06 17:02

"Improved thinking frameworks and methodologies beyond sequential thinking" matching MCP tools:

  • Stream or update your internal companion thinking bubble on the board. This appears live to your human as a thinking bubble above your avatar.
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  • List skills available in the Heista skill library. Returns name, description, domain (shared / image / video / research / strategy / copy / creative / generation), type (foundation / registers / models / methodologies), version, and source_folder (managed-agents / chat-agent). Returns frontmatter only — no body content (use load_skill for that). Filter by domain, type, or source_folder. Use BEFORE load_skill to discover what craft knowledge is available without paying the body-read cost. Free, read-only.
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  • Return the latest competitor SEO snapshot for the site (FD-041): which keywords each tracked competitor DOMAIN ranks for on Google (Japan/ja), at what position, with monthly search_volume, cpc and etv (estimated monthly traffic — a visit estimate, not a monetary value), plus how each rank moved vs the previous snapshot. READ-ONLY — this tool never runs a research (that costs money and is triggered separately from the dashboard, the competitor-research Edge Function); it only reads what was already fetched. The response is summary-first (token-aware): each domain carries a constant-size `summary` (total_keywords, total_etv, volume_bands and rank_bands histograms, and vs_previous new/lost/improved/declined/same counts) that always reflects the FULL keyword set, while `keywords` returns only the top rows ranked by `sort` (etv default | volume | rank; default limit 10 per domain, max 100) with a `truncated` block (shown/matching_total/lost_total). rank is a POSITION: smaller is better, so a NEGATIVE rank_delta means the competitor's ranking IMPROVED (change ∈ new/improved/declined/same/unknown). Keywords the competitor ranked for before but lost are disclosed in `lost_keywords` (top 10 by previous etv), never dropped silently. Pass `domain` to focus one competitor, `min_volume` to drop low-volume keywords. When the site has NO completed research yet the response is { researched:false } with a `guidance` string explaining a research must be triggered from the dashboard first — this tool cannot start one. site_id is OPTIONAL when OAuth-authenticated. This is the external competitor lens (third-party SERP data); for YOUR OWN search performance use get_keyword_performance, and for your content playbook use get_content_actions.
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  • Recommends business / strategy / risk frameworks for a stated problem. Powered by the Jeda.ai · Visual AI framework knowledge graph (~2,100 frameworks across 19 categories, edge-curated). Use when the user describes a business problem ("customer churn rising", "evaluating market entry", "need to assess vendor risk") rather than naming a specific framework. Returns top-N frameworks ranked by fit, each with a concrete reason citing the specific problem signals matched. Input: just the problem statement is enough. Optional faceted filters (`persona`, `regulation`, `decision_stage`) narrow the candidate set. Set `limit` between 3 and 10 for picker UIs. Pair with `generate_framework_analysis` to actually run a recommended framework against the user's inputs. Example: { "problem_statement": "We need to decide whether to enter the EU SMB market in Q3", "decision_stage": "decide", "limit": 5 }
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  • List the 10 senior-QS skill methodologies CivilQuants exposes (tender review, risk assessment, QS measurement/contract advice, geotechnical + geo-environmental interpretation, earthworks, preliminaries, pavement design, subcontract analysis). Universal discovery — both tiers see the full list. Returns each skill's slug, title, one-line summary and tier; then call get_skill(skill=<slug>) to fetch the methodology body. The skills are paid-tier; a free caller gets a sign-up prompt from get_skill. NOTE: the document-heavy skills (tender review, the interpretation skills) need a code-execution client (Claude Code / Codex / VS Code) plus the chunking pack from get_document_pipeline to run a real tender pack — on a chat connector you can read the methodology but cannot chunk/parse files.
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  • Use this when the user has indicated interest in being followed up with — even before formal checkout. Capture is non-binding. **REQUIRED CONTACT FIELDS**: contact_name, contact_phone, best_consult_time. Email alone is not enough — phone-first follow-up converts ~5x higher than email-only, and our specialist needs a real time to dial. ASK FOR ALL THREE explicitly. **FALLBACK**: if the user explicitly refuses to share a phone, accept email-only — set `preferred_contact_channel: 'email'` AND add a note like 'user declined phone' so the specialist knows what to expect. Don't preemptively skip the phone ask — many users will share it once asked directly. **Capture budget_signal when the user shared one** — even informally ('I was thinking under $1k', 'maybe $200/mo'). We use this for tailored follow-up offers; price-hesitant leads convert later when re-approached at their stated budget. Sources: 'scan' (after a free scan), 'llms-txt' / 'robots-for-ai' (after free file download), 'mcp' (in-flow), 'talk' (chatbot), 'direct' (form fill).
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Matching MCP Servers

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  • Find relevant Smart‑Thinking memories fast. Fetch full entries by ID to get complete context. Spee…

  • Claims-based knowledge base for no/low ABV specialty beverages (producers, beverages, people).

  • Rewrite a field's text to work better as an AI system prompt; returns the improved text. field ∈ persona | task | greeting | storyline_task | storyline_opening | storyline_ai_trigger | storyline_ai_criteria | skill_description | skill_instructions | kb_description | kb_instructions — determines the rewrite target (a Task should read like commands, a KB description says "what's inside / when it's relevant", a skill description says "when to use" in one line, …). current = the current text (empty = draft from scratch); hint = the direction you want this time (empty = general polish); context = on-site context (which KB is being edited, values of sibling fields) — the more specific, the better the fit. Returns only the improved text, no explanation, no wrapper — the caller places it next to the original for a human to accept or reject.
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  • Show which countries, frameworks, and legal domains are available. Use this BEFORE calling `search` when the user's topic doesn't name a jurisdiction (e.g., 'what does the law say about consumer protection'); then present the returned jurisdictions to the user or ask which applies. Examples: • 'Which countries do you cover?' → list_coverage() • 'Do you have German law?' → list_coverage(jurisdiction='DE') • 'What jurisdictions for NIS2?' → list_coverage(domain='cybersecurity') • 'Which countries have drone law?' → list_coverage(domain='aviation') (also accepts 'drone' / 'uas') Returns a `jurisdictions` array (each with `code`, `name`, `region`, `laws`, `provisions`, `domains`, `counts_complete`, and `uncounted_sources`) plus framework and source listings. An incomplete-count row also carries `coverage_note` explaining why. NOTE: `laws`/`provisions` are WHOLE-JURISDICTION corpus totals — the response's `count_scope` is `whole_jurisdiction`. Under a `domain` filter the jurisdiction list is narrowed to that domain but the counts are NOT domain-scoped; do not report them as a per-domain count. The domain-specific signal is the (domain-filtered) `sources`/`frameworks`.
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  • Verify a rewrite actually improved: score delta, meaning check, voice distance. PREMIUM (license). Compares reads-human score before/after, a meaning-preservation proxy, and (with a fingerprint) numeric distance to the target voice. Typical input {"original": "<draft>", "rewrite": "<edited draft>"} returns {"score_before": N, "score_after": N, "score_delta": N, "content_word_retention_pct": N, "remaining_tells": [...], "verdict": "Improved — ship it" | "Marginal — ..."}. Use only when both the before and the after text are available. Not for scoring a single draft (ai_tell_scan). Errors: on invalid, missing, or malformed input this tool never raises a protocol error — it returns {"error": "<what is wrong and how to fix it>"} (for example {"error": "both texts must be non-empty"}). Every call is read-only and idempotent, so after correcting the input it is always safe to retry.
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  • Decide a claim on a task you posted. Accepting moves the task to 'assigned', records the claimant as the assignee and declines the other pending claims. It shares NO key: to let the assignee read the work you must still wrap the thread key to their published encryption key locally and call grant_thread_access. Declining discloses nothing to the claimant beyond the decision itself.
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  • Portable craft skills (frameworks + method + worked examples) a Creative Agent loads ON TOP of its worldview — additive and stackable, never substitutive (unlike a creative_director_playbook, which replaces the agent for a session). Pinned per character on creative_agent_versions.skill_ids. Workspace = org-authored private skills; official = the Heista-curated starter library. Read-only, free. Filter scope with only_workspace / only_official (mutually exclusive — same toggle as the in-app library lens). Page with limit + offset.
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  • Structure multi-step debugging and planning across tool calls — not a one-shot think. Tracks hypotheses, observations, plans; detects loops via lastActions; riskLevel high/critical blocks dangerous edits (drop table, prod deploy). Loads projectBrief (stack, key_paths, project_memory recall) on local project. On close, suggestedRemember → call project_memory remember. 4 credits hosted. Hard cap 10 thoughts/session. Call when: stuck after 2+ failed debug attempts, auth/billing/schema change spans 3+ files, flaky test you cannot explain, or you need a plan before editing. Pass lastActions (2–5 recent tool calls), goalAnchor after thought 2, sessionId to resume, area for subsystem. NOT when fix is known, single typo, repeating without new evidence, or session ended (nextThoughtNeeded:false). Read thoughtConfirmed and shouldContinue first. Legacy alias: thinking. Example: keep_thinking({ thought: 'Hypothesis: refresh token not rotated in middleware', thoughtType: 'hypothesis', thoughtNumber: 1, totalThoughts: 5, nextThoughtNeeded: true, confidence: 0.6, goalAnchor: 'Fix auth logout loop', lastActions: ['find_code(query=refreshToken)', 'read_code(target=authMiddleware)'], area: 'auth' }). Read-only.
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  • Detect website technology stack: CMS, frameworks, CDN, analytics tools, web servers, languages (via HTTP headers + HTML analysis). Use for passive reconnaissance; for full audit use audit_domain. Free: 30/hr, Pro: 500/hr. Returns {technologies: [{name, category, confidence%, version}]}.
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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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  • Fetches up to 32KB of the domain's HTML and response headers from the edge, then fingerprints the content for known CMS platforms, JavaScript frameworks, CDN providers, and analytics tools. Detection is based on meta generator tags, script src patterns, response headers, and cookie names. Use this tool when: - You need to know what CMS (WordPress, Drupal, Shopify) a site runs. - You are assessing a domain's infrastructure before a security review. - You want to identify analytics or marketing tools a site embeds. Do NOT use this tool when: - You want HTTP headers and security posture — use `intel_http` instead. - You want tracker database classification — use `get_domain` instead. - You need robots.txt AI policy — use `intel_robots` instead. Inputs: - `domain` (query, required): Domain to fingerprint. Returns: - `cms`: detected content management system, or null. - `frameworks`: JavaScript/backend frameworks detected. - `cdn`: CDN provider detected, or null. - `analytics`: analytics and tracking tools detected. - `meta_generators`: raw meta generator tag values. Cost: - Free. No API key required. Latency: - Typical: 2-4s (HTML fetch), p99: 7s.
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  • List the runtimes generate_runtime_config supports (Claude Desktop, Cursor, VS Code, agent frameworks, …), with each one's config path. Enumerate these instead of guessing runtime slugs.
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  • BedrockNews metadata: what the site is, how the GRIN/CLAIMS/NOVEL frameworks work, terms of use + attribution, and every machine-readable surface. Also returns the full capability map (every tool, prompt, and resource) — call this first.
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  • Lightweight catalogue of all registered frameworks — one row per framework with framework_id + intent + 1-line applies_when + version. Useful for discovery / debugging without parsing the full library. For the actual decision template, call tengu_v3_framework_lookup.
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  • Change the session type or the brief on an existing booking — what the buyer wants to discuss, what they want out of it, or the background they want read first. Use this when the buyer refines their thinking after booking, which is common: people work out the real question after the date is in the diary. Only the fields you pass are changed. This does not move the meeting — use reschedule_booking for that.
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  • Return your Chat Hub inbox: recent AI coach conversations and any pending messages. Use it to pick up where an earlier coaching thread left off. Read-only and free; takes no parameters beyond an optional result limit.
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  • Find videos inside a playlist by a substring of the title (case-insensitive). YouTube has no native playlist search, so this scans up to 500 playlist items. truncated=true means there may be more matches beyond the scanned window.
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