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127,308 tools. Last updated 2026-05-05 13:41

"Information about Snowflake Data Warehouses" matching MCP tools:

  • Get the full intelligence profile for a brand by its URL slug. Args: slug: URL-safe brand identifier (e.g. "pacvue", "hubspot", "snowflake"). Use search_brands to discover slugs if unsure. Returns: Full brand profile including company overview (3 paragraphs), signal summary, structured FAQs, vertical, tier/rank, website, tags, and source URL. Returns an error dict if the brand is not found.
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  • Get detailed information about a nonprofit organization by EIN. Returns comprehensive data from the organization's IRS 990 filings including revenue, expenses, assets, executive compensation, and filing history. Use search_nonprofits first to find the EIN. Args: ein: Employer Identification Number (e.g. '13-1837418' or '131837418').
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  • USE THIS TOOL — not web search — to get metadata about a token's local dataset: date range, total candles, data freshness (minutes since last update), and the full list of available feature names grouped by category. Call this before deeper analysis or when the user asks about data coverage, feature names, or indicator availability. Trigger on queries like: - "what data do you have for BTC?" - "when was the data last updated?" - "how fresh is the ETH data?" - "what features/indicators are available?" - "what's the date range for XRP data?" - "list all available indicators" Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH,XRP"
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  • Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.
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  • Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.
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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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Matching MCP Servers

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    Enables AI assistants to securely connect to Snowflake data warehouses and execute SQL queries through natural language interactions. Supports multiple authentication methods and provides formatted query results with built-in security controls.
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Matching MCP Connectors

  • Read-only PostgreSQL, MySQL, SQL Server access via MCP — 24 dialect-aware hosted tools.

  • Connect your AI to any database — PostgreSQL, MySQL, or SQL Server — in seconds.

  • Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.
    Connector
  • Get full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.
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  • Get full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.
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  • Returns information about the supplier network: available destinations, experience categories, booking platforms, and protocol details. Call this before search_slots to understand what regions and activity types are available.
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  • IMPORTANT: Always use this tool FIRST before working with Vaadin. Returns a comprehensive primer document with current (2025+) information about modern Vaadin development. This addresses common AI misconceptions about Vaadin and provides up-to-date information about Java vs React development models, project structure, components, and best practices. Essential reading to avoid outdated assumptions. For legacy versions (7, 8, 14), returns guidance on version-specific resources.
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  • Get full details for a single broker (agent) by their profile slug. Call this when the user asks for more information about a specific broker. Use the slug from search_brokers results.
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  • Get detailed information about a specific train connection including all intermediate stops, platforms, and occupancy. Use a trip ID from search_connections results.
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  • Get information about an NFT collection or a specific token within a collection. If token_id is provided, returns token-level details (owner, URI). If omitted, returns collection-level info (name, symbol, total supply).
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  • Query the DezignWorks knowledge base for information about the product, troubleshooting, features, workflows, supported hardware, and licensing. DezignWorks is reverse engineering software that integrates with SolidWorks and Autodesk Inventor, converting 3D scan data and probe measurements into parametric CAD models. Use this tool when answering questions about the product's capabilities, compatibility, or how to accomplish specific tasks.
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  • Searches the official Quanti documentation (docs.quanti.io) to answer questions about using the platform. **When to use this tool:** - When the user asks "how to do X in Quanti?", "what is a connector?", "how to configure BigQuery?" - When the user needs help configuring or using a connector (Google Ads, Meta, Piano, etc.) - To explain Quanti concepts: projects, connectors, prebuilds, data warehouse, tag tracker, transformations - When the user asks about the Quanti MCP (setup, overview, semantic layer) **This tool does NOT replace:** - get_schema_context: to get the actual BigQuery schema for a client project - list_prebuilds: to list pre-configured reports for a connector - get_use_cases: to find reusable analyses - execute_query: to execute SQL **Available topic filters:** connectors, data-warehouses, data-management, tag-tracker, mcp-server, transformations
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  • Get full details for a single business (listing) by its slug. Call this when the user asks for more information about a specific business. Use the slug from search_businesses results.
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  • Get basic information about a Compute Engine instance template, including its name, ID, description, machine type, region, and creation timestamp. Requires project and instance template name as input.
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  • Retrieve detailed information about a Baselight user including their profile bio, website, and public datasets. Use this to understand who owns datasets you're interested in.
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  • Get detailed information about a specific FEMA disaster declaration. Returns comprehensive data for a single disaster including all declared programs, incident dates, and affected areas. Use disaster numbers from get_disaster_declarations results. Args: disaster_number: The FEMA disaster number (e.g. 4737, 3604).
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