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305,087 tools. Last updated 2026-07-23 01:19

"WhyLabs AI Observability Platform" matching MCP tools:

  • Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.
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  • Dispatch to the SOCIAL LISTENING RESEARCHER — multi-platform community-signal interpretation. Use for: "what are practitioners saying about X across platforms / what jargon is emerging in field Y / what is the cross-platform discourse around brand/topic Z". Treats T3 community sources as primary data, distinguishes cross-platform patterns from single-platform noise. ≥3 platforms sampled per brief. Returns: Signal map (Signal / Platforms / Volume / Sentiment + recency) + Per-platform evidence trail + Cross-platform vs single-platform classification + Confidence flag + Sources. NOT for: single-source thematic work (use dispatch_qualitative_researcher) / numerical sentiment effect sizes (use dispatch_quantitative_researcher). ASYNC version: returns { job_id } immediately, the specialist runs durably on a Vercel Workflow (no 300s timeout). Use this version when the specialist is expected to take >90s. Call get_dispatch_result(job_id) periodically (respect wait_ms_hint in the response) until status === 'completed' or 'failed'. Idempotent: same brief + same org reuses the same job_id, so retries don't fan out duplicate runs.
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  • Hand a natural-language prompt to the FreeAppStore VibeCode AGENT — the platform's own AI writes the code AND deploys it. This is different from create_app/update_files (where the CALLING model writes the code): here you just prompt, and the platform builds. Uses your stored AI key (provider must be in your vault). Long-running; it builds in the background. Returns the session_id — poll agent_status to watch it and get the live URL. Tip: include the app id in your prompt, e.g. 'Build a dice roller and deploy it as dice-roller'.
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  • List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.
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  • List application guides that show how Blueprint principles apply to engineering challenges (security, evaluation, observability, etc.). Use this to discover which guides exist before drilling in. Prefer guides.search when the user describes a topic or failure mode in natural language. Prefer guides.get when you already know the guide slug and need full detail.
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  • Returns the list of languages supported by Makuri, with separate coverage details for user interface versus AI tutor interactions. Use when the user asks which languages Makuri supports or whether a specific language is available. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.
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  • Query application logs, traces, and metrics from your AI coding assistant via Foam's MCP server.

  • Free MCP tools: the only MCP linter, health checks, cost estimation, and trust evaluation.

  • Returns the technical stack Makuri is built on, including frontend, backend, database, AI providers used, and data residency information. Use when the user asks how Makuri is built or which AI models it uses. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.
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  • Trigger a Grok-AI gemological appraisal of a single gem on GemHunt (https://gemhunt.app — Father's gem-discovery platform). Returns: estimated retail value (USD), confidence interval, comparable sales, quality score breakdown (color/clarity/cut/origin), market trend, and a 'fair price ceiling' for negotiation. Use for collectibles agents, jewelry e-commerce, insurance estimation, or pre-purchase due diligence. Premium ($0.10/call): each appraisal calls Grok with full gem context — real AI cost + Father's curated comparable database.
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  • Get high-level facts about the ACCRUE platform: fee structure, custody model, supported chains, wallets, KYC requirements, withdrawal terms, and AI agent integration status. Use this when the user asks "what is ACCRUE", "how does ACCRUE work", "what are the fees", or anything about the platform itself rather than a specific vault.
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  • Returns structured information about what the Recursive platform includes: features, AI model details, supported integrations, and what's included at every tier. Use for systematic feature comparison.
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  • Returns Makuri's regulatory posture across EU AI Act, GDPR, GDPR-K (children data), COPPA, and ISO 42001 — as design intentions and operator self-assessment, NOT certified or audited compliance. No formal audit or conformity assessment has been performed. Statuses are design_aligned_unaudited, not_started, or not_applicable; there is deliberately no 'compliant' status. Use when the user asks about regulatory compliance, AI Act classification, or data protection for children — and present results as posture, not certification. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.
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  • Fetch the full record for a single creator by ID or exact platform username. Use this when you already have either: - a canonical creator UUID returned by `search_creators`, `semantic_search_creators`, `autocomplete_creators`, or `find_lookalike_creators`; or - an exact platform+username pair such as platform "instagram" and username "niickjackson". Pass `include: ['profiles']` to also receive the creator's social profile summaries when using a creator UUID. For platform+username inputs, this tool resolves through the profile endpoint and returns the profile record plus the underlying creator record, so you already get the matched profile context. Examples: - User: "Get creator 123e4567-e89b-12d3-a456-426614174000" -> call with id. - User: "Get @niickjackson on Instagram" -> call with platform "instagram" and username "niickjackson", or use `get_profile` if profile metrics are the main need. - User: "Tell me about @niickjackson and include his profiles" -> use platform "instagram" and username "niickjackson"; then use `get_profile`/`get_posts` for platform-specific metrics and content if needed. Use `lookup_profiles` for batch exact profile lookups.
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  • Check live API & system health — operational/degraded verdict, per-source freshness, MCP tool count — Public health status of all CryptoWhaleInsights data sources, MCP server, and OpenAPI spec. Returns overall verdict (operational/degraded/outage), per-source health with age in seconds, recent 24-hour error count, MCP tool count, and OpenAPI path count. Useful for AI agents and developers to verify the platform is live before making requests. Cached ~30s.
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  • Rally the ProductClank community to engage with a specific social post. Creates a boost campaign and spends the user's credits: 'replies' generates 10 AI reply drafts (200 credits); 'likes' (30 likes) and 'repost' (10 reposts) cost 300. Supports Twitter/X, Instagram, TikTok, LinkedIn, Reddit, and Farcaster — the platform is auto-detected from the URL. Requires a product_id from search_products. Confirm the action and its credit cost with the user before calling.
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  • Filter free-to-play games on FreeToGame by a dot-separated tag combination (e.g., "3d.mmorpg.fantasy", "shooter.pvp") and optional platform (pc/browser). Returns matching games with title, genre, platform, and release date.
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  • List every Stimulsoft product/platform that has indexed documentation available through this MCP server. Returns a JSON array of { id, name, description } objects covering the full Stimulsoft Reports & Dashboards product line (Reports.NET, Reports.WPF, Reports.AVALONIA, Reports.WEB for ASP.NET, Reports.BLAZOR, Reports.ANGULAR, Reports.REACT, Reports.JS, Reports.PHP, Reports.JAVA, Reports.PYTHON, Server API, etc.). CALL THIS FIRST when the user's question is ambiguous about which Stimulsoft platform they are using, or when you need to pick a valid `platform` value to pass into `sti_search`. The returned platform `id` values are the exact strings accepted by the `platform` parameter of `sti_search`. This tool is cheap (no OpenAI call, no vector search) — call it freely whenever you are unsure about platform naming.
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  • List application guides that show how Blueprint principles apply to engineering challenges (security, evaluation, observability, etc.). Use this to discover which guides exist before drilling in. Prefer guides.search when the user describes a topic or failure mode in natural language. Prefer guides.get when you already know the guide slug and need full detail.
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  • Search application guides by free-text query, matched against section answers and action items. Use this when the user describes an engineering challenge (security review, evaluation harness, observability) and wants matching guides. Prefer guides.get when you already have the guide slug; prefer guides.list when you need the full inventory.
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  • Search application guides by free-text query, matched against section answers and action items. Use this when the user describes an engineering challenge (security review, evaluation harness, observability) and wants matching guides. Prefer guides.get when you already have the guide slug; prefer guides.list when you need the full inventory.
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