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127,484 tools. Last updated 2026-05-05 18:07

"A server for finding football predictions" matching MCP tools:

  • Checks that the Strale API is reachable and the MCP server is running. Call this before a series of capability executions to verify connectivity, or when troubleshooting connection issues. Returns server status, version, tool count, capability count, solution count, and a timestamp. No API key required.
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  • Switch between local and remote DanNet servers on the fly. This tool allows you to change the DanNet server endpoint during runtime without restarting the MCP server. Useful for switching between development (local) and production (remote) servers. Args: server: Server to switch to. Options: - "local": Use localhost:3456 (development server) - "remote": Use wordnet.dk (production server) - Custom URL: Any valid URL starting with http:// or https:// Returns: Dict with status information: - status: "success" or "error" - message: Description of the operation - previous_url: The URL that was previously active - current_url: The URL that is now active Example: # Switch to local development server result = switch_dannet_server("local") # Switch to production server result = switch_dannet_server("remote") # Switch to custom server result = switch_dannet_server("https://my-custom-dannet.example.com")
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  • Search Cochrane systematic reviews via PubMed. Finds Cochrane Database of Systematic Reviews articles matching your query. Returns PubMed IDs, titles, and publication dates. Use get_review_detail with a PMID to get the full abstract. Args: query: Search terms for finding reviews (e.g. 'diabetes exercise', 'hypertension treatment', 'childhood vaccination safety'). limit: Maximum number of results to return (default 20, max 100).
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  • Given a product ID, find similar products across the entire catalog. Useful for "more like this" recommendations or finding alternatives. Returns compact product cards, not full variant detail; call get_product for SKU-level variants, exact variant prices, merchant description, store info, and all images. Returns page and hasNextPage. Returns up to 10 results per page, paginated (max 3 pages).
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  • Returns VoiceFlip MCP server health and version metadata. No authentication required. Use this first to verify the server is reachable from your MCP client.
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Matching MCP Servers

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    license
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    maintenance
    Provides real-time access to football (soccer) data including fixtures, standings, teams, players, transfers, and injuries through the API-Football service via the Model Context Protocol.
    Last updated
    3
  • A
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    quality
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    Provides comprehensive A-share (Chinese stock market) data including stock information, historical prices, financial reports, macroeconomic indicators, technical analysis, and valuation metrics through the free Baostock data source.
    Last updated
    24
    MIT

Matching MCP Connectors

  • Fetch HTTP response headers for a URL. Use when inspecting server configuration, security headers, or caching policies.
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  • Composite server-side investigation tool. Pass a question and the server automatically: (1) detects intent (aggregation/temporal/ordering/knowledge-update/recall), (2) queries the entity index for structured facts, (3) builds a timeline for temporal questions, (4) retrieves memory chunks with the right scoring profile, (5) expands context around sparse hits, (6) derives counts/sums for aggregation, (7) assesses answerability, and (8) returns a recommendation. Use this as your FIRST tool for any non-trivial question — it does the multi-step investigation that would otherwise take 4-6 individual tool calls. The response includes structured facts, timeline, retrieved chunks, derived results, answerability assessment, and a recommendation for how to answer.
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  • Run a generic M/M/c queue simulation. Provide an arrival rate (λ, arrivals/hour), a service rate per server (μ, customers/hour each server can finish), and a server count (c). Optional: distribution shapes, service coefficient of variation, run length. Returns per-hour metrics and an overall summary (avg wait, queue length, offered load, throughput). This is the primary tool for 'how many servers do I need?' / 'what's my average wait?' style questions. ALSO preferred over simulate_scenario for what-if questions about scheduled scenarios (Coffee Shop, ER) when the user wants flat uniform numbers — pull the peak params from describe_scenario and run them here. That usually matches user intent better than collapsing a schedule.
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  • [역할] Daily validation history of Level 2 structure predictions. Each row shows hit_rate for a specific day, enabling time-series verification of sustained performance. [호출 시점] After get_structure_calibration. [선행 조건] 없음. [후속 추천] get_monthly_accuracy_trend for macro-level comparison. [주의] Returns overall_hit_rate summary across the window. Args: market_id: Optional market filter days: Lookback window in days (default 90)
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  • Check if the API is responding. Returns status and server timestamp.
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  • Fetch current NFL football game scores, schedules, and results. Returns team matchups, final scores, scheduled start times, team standings, and individual player stats. Use for fantasy football, sports analysis, or following NFL season progress.
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  • Connectivity check — returns server version and current timestamp. Use to verify MCP server is reachable before calling other tools.
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  • [역할] Currently pending predictions (outcome IS NULL) — shows OneQAZ is actively making forecasts right now. Combined with get_prediction_accuracy, proves we don't cherry-pick past wins; we're on record for future outcomes. [호출 시점] To verify ongoing prediction activity. [선행 조건] 없음. [후속 추천] get_prediction_accuracy to see historical hit rates on similar predictions. [주의] Returns most recent first. Args: target_market: Optional target market filter (coin_market, kr_market, us_market) limit: Max active predictions to return (default 20)
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  • Search for UK SIC 2007 codes by business activity description. Describe what a business does in plain English and get ranked SIC code recommendations with relevance scores, hierarchy breadcrumbs, and GICS/ICB cross-classification mappings. Useful for finding the right SIC code for Companies House registration.
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  • Search or fetch posts from the MetaMask Embedded Wallets community forum (builder.metamask.io). Use for troubleshooting real user issues, finding workarounds, and checking if an issue is known. Provide a query to search or a topic_id to read the full discussion.
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  • Run hosted inference on an image using a trained model. Returns JSON predictions only. For visualized/annotated images, use workflow_specs_run with a visualization block instead.
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  • Search for UK SIC 2007 codes by business activity description. Describe what a business does in plain English and get ranked SIC code recommendations with relevance scores, hierarchy breadcrumbs, and GICS/ICB cross-classification mappings. Useful for finding the right SIC code for Companies House registration.
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  • Build a Tableau dashboard from a Microsoft SQL Server table (end-to-end). Pipeline: MSSQL → schema inference → chart suggestion → workbook creation → live MSSQL connection → .twb output. Requires pyodbc for schema inference and ODBC Driver 17 for SQL Server. IMPORTANT FOR AI AGENTS: see ``csv_to_dashboard`` — auto-charts come from rules, not natural-language requests. Use ``required_charts`` to guarantee specific charts, ``reference_image`` for image-based styling, and cite the returned manifest dict when describing results. Args: server_host: MSSQL server hostname. dbname: Database name. table_name: Table to visualize. username: Database username (ignored if trusted_connection=True). password: Database password (used for schema inference only). port: Server port (default 1433). trusted_connection: Use Windows Authentication instead of SQL auth. output_path: Output .twb path (defaults to <table>_dashboard.twb). dashboard_title: Dashboard title. max_charts: Maximum charts (0 = use rules default). template_path: TWB template path. theme: Theme preset name. rules_yaml: Optional YAML string with dashboard rules overrides. required_charts: See ``csv_to_dashboard.required_charts``. reference_image: See ``csv_to_dashboard.reference_image``. Returns: Structured manifest dict describing what was actually built.
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