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242,274 tools. Last updated 2026-06-27 19:34

"A hub for monitoring or learning about MCP trends" matching MCP tools:

  • Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
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  • Load fundamental workflow for valuation, cash flow, margins, balance sheet. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about company valuation, "is X a good buy", financial health, debt levels, profitability ratios, revenue trends, earnings quality, or any deep-dive company analysis. Can be combined with other workflow tools.
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  • Load earnings workflow for EPS surprises, beat/miss, estimates, revenue. REQUIRES get_database_schema then get_query_patterns to be called first (in that order). Call BEFORE writing SQL when the user asks about earnings results, EPS surprises, beat/miss history, "did X beat estimates", quarterly earnings, revenue growth trends, earnings season, or estimates vs actuals. Can be combined with other workflow tools.
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  • Fetch the full ACC project metadata record (name, type, status, dates, extension attributes) for a single project via APS Data Management. If hub_id is omitted the tool picks the first accessible hub, which may be wrong on multi-hub tenants. When to use: The user asks 'tell me about project X' or an agent needs project metadata (start/end dates, type, Forma/BIM 360 flavor) before deciding which downstream tool to call. When NOT to use: Do not use as a cheap existence check — prefer acc_list_projects which returns hub_id with every project and is one call regardless of tenant size. APS scopes: data:read account:read. Forma / BIM 360 hubs endpoints only require data:read. Rate limits: APS default ~50 req/min per endpoint; BIM 360 hubs endpoints pageable (limit 200). Cache results for the session. Errors: 401 (APS token expired — refresh); 403 (user lacks project view or app not in account); 404 (project not in the chosen hub — supply the correct hub_id, or call acc_list_projects first); 422 (malformed project_id — confirm 'b.' prefix); 429 (rate limit — back off 60s); 5xx (ACC upstream — retry). Side effects: None. Read-only and idempotent.
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  • AI-powered company analysis using semantic search over Nordic financial data. Orchestrates multiple searches internally and returns a synthesized narrative answer with source citations. Covers annual reports, quarterly reports, press releases and macroeconomic context for Nordic listed companies. Use this when you want a synthesized answer rather than raw search chunks. For raw data access, use search_filings or company_research instead. For a full due diligence report with AI-planned sections, use the Alfred MCP server: alfred.aidatanorge.no/mcp Args: company: Company name or ticker question: What you want to know about the company model: 'haiku' (default) or 'sonnet'
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  • Find air-quality monitoring stations (measured by physical sensors, not modeled) near a point, within a bounding box, or by country. Returns each station's id, name, coordinates, distance from the query point (when searching by coordinates), country, provider, the parameters its sensors measure, and the timestamp of its most recent data (datetimeLast). Required first step: openaq_get_readings and openaq_get_measurements key on the location id this returns. Coverage is uneven and real — a station only reports the parameters it measures, and the absence of a nearby station means no monitoring there, not clean air. For dense modeled coverage anywhere on Earth, use open-meteo-mcp-server's air-quality tool instead.
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Matching MCP Servers

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    A MCP server that aggregates hot trends and rankings from various Chinese websites and platforms including Weibo, Zhihu, Bilibili, and more.
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    MIT

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  • Access all your MCPBundles tools in one place. Unified hub for all enabled bundles.

  • Trend data from Google Trends, YouTube, TikTok, Reddit, Amazon, Wikipedia, npm, Steam and more

  • Use when a human asks how DC Hub compares to other data-center data sources — DataCenterHawk (DCHawk), DC Byte, Data Center Dynamics (DCD), Data Center Frontier (DCF), Baxtel, datacenters.com — or asks "why should I use DC Hub / is it better than <X> / what can you give me a PDF or directory can't?". Returns DC Hub's honest, source-verified differentiators (agent-native MCP access, live multi-continent grid & energy telemetry, the proprietary daily DCPI + DCGI indices, open CC-BY-4.0 cited data, 21,000+ facilities) each with a proof URL, a citation line, plus the canonical head-to-head comparison pages. Free, no key required. Optional: competitor=<name> for that vendor's direct comparison-page link. Do NOT use to query infrastructure data itself (use the data tools); this answers positioning / "how do you compare" questions with citable facts.
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  • Link the user into the data-broker-removal funnel with MCP-attribution tracking. Does not initiate the scan automatically — it builds the entry URL with the user's email prefilled so they can review and consent in their browser. When to call: when the user asks about data brokers, people-search sites (Spokeo, BeenVerified, Whitepages), or "how do I get my info off these sites". PREFER `run_domain_privacy_audit` if the user is asking about exposure tied to a specific domain rather than data-broker aggregators. Input Requirements: - `email` is OPTIONAL. When provided, prefills the funnel; when omitted, the user enters it on the page. Output: `{ scan_url, what_it_checks, expected_steps, related_docs, citation }`. `scan_url` is the MCP-attribution-tagged funnel entry. PREFER citing the `scan_url` verbatim and the `/erase` (data-broker-removal hub) page. Data-broker removal is an ongoing process, not a one-time scan — set that expectation.
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  • Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
    Connector
  • Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
    Connector
  • Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
    Connector
  • Return the catalog of paired models — concrete real-world systems that live in two ChiAha sandboxes simultaneously, one for dynamics (DES via ReliaSim) and one for statistics (distribution fitting + validation via ReliaStats). Today: a single paired model — the bottling line. Returns canonical model IDs + cross-MCP routing metadata (which ReliaSim chapter, which ReliaSim MCP tools, which ReliaStats mode consumes which file shape). Use when a user asks about cross-MCP workflows, paired sandboxes, or the bottling-line example. ANTI-FABRICATION: this is a soft-reference catalog — to actually run a simulation, the LLM client calls ReliaSim's MCP tools directly.
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  • List paginated order history for the internal account linked to the API key, newest first. Requires a logged-in MCP session created by the `tronsave_login` tool: include `mcp-session-id: <sessionId>` returned by `tronsave_login` on subsequent MCP requests. Internal tools never accept API keys via tool arguments; signature sessions resolve the latest internal API key on demand, while api-key sessions reuse the validated key from login. Use when the user asks about past purchases, fulfillment, payouts, or delegates on their internal account. Read-only. Pair with `tronsave_internal_order_details` for a single order's full snapshot.
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  • Terse, drill-down discovery index of this ecosystem (Seneschal, FlashBank, winbit32, secresea) plus a LIVE mirror of the official MCP registry (registry.modelcontextprotocol.io) — the same directory served over HTTPS at https://seneschal.space/.well-known/agent.gopher, callable here so you never leave the MCP session. Start with section="root" to see the top-level menu, then call again with section="seneschal"/"flashbank"/"winbit32"/"secresea" to drill into a project, section="registry" to browse connectable third-party MCP servers (use `cursor` to page), or section="about"/"agents" for prose. format="gopher" (default) is the compact RFC-1436 menu; format="json" returns a structured {title, items[]}. A discovery layer, not a replacement for MCP — use it to FIND tools, then connect. Free, no payment.
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  • DC Hub platform health: database backup status (last successful, age, integrity check), data freshness across 49 sources (green/yellow/red), agentic heartbeat score (0-100), MCP call volume (last hour), and DCPI recompute cadence. Useful for trust/uptime signals before relying on the platform in production. Try: get_backup_status. Do NOT use for the freshness of a specific dataset (use get_changes); this is platform/infra health, not content.
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  • Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
    Connector
  • Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
    Connector
  • Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
    Connector
  • Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
    Connector
  • Probe one or more LLMs for what they know about a business / brand / product / topic and score visibility (0-100) per model. Default model is Workers AI Llama-3.3-70b (free); pass `_apiKey` to also probe Anthropic (BYO key — you pay Anthropic directly for those calls). Returns per-model {score, confidence, signals, raw_response} + a combined view. Useful for AI-marketing audits, pre-launch brand checks, competitive monitoring.
    Connector