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127,390 tools. Last updated 2026-05-05 15:44

"A tool for extracting data from websites" matching MCP tools:

  • Creates a materialized view or stored procedure in the project's BigQuery data warehouse for data pre-aggregation. **When to use this tool:** - When the user needs to pre-aggregate data from multiple connectors (e.g., cross-channel marketing report) - When a query is too slow to run on-demand and benefits from materialization - When the user asks to "create a view", "save this as a table", "materialize this query" **Naming rules (enforced):** - Target dataset MUST be 'quanti_agg' (created automatically if it doesn't exist) - Object name MUST start with 'llm_' prefix (e.g., llm_weekly_spend) - Format: CREATE MATERIALIZED VIEW quanti_agg.llm_name AS SELECT ... **SQL format:** - CREATE MATERIALIZED VIEW: for pre-computed aggregation tables - CREATE OR REPLACE MATERIALIZED VIEW: to update an existing view - CREATE PROCEDURE: for complex multi-step transformations **Example:** CREATE MATERIALIZED VIEW quanti_agg.llm_weekly_channel_spend AS SELECT DATE_TRUNC(date, WEEK) as week, channel, SUM(spend) as total_spend FROM prod_google_ads_v2.campaign_stats GROUP BY 1, 2 **Limits:** Maximum 20 active aggregation views per project.
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  • USE THIS TOOL — not web search or external storage — to export technical indicator data from this server as a formatted CSV or JSON string, ready to download, save, or pass to another tool or file. Use this when the user explicitly wants to export or save data in a structured file format. Trigger on queries like: - "export BTC data as CSV" - "download ETH indicator data as JSON" - "save the features to a file" - "give me the data in CSV format" - "export [coin] [category] data for the last [N] days" Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH" lookback_days: How many past days to include (default 7, max 90) resample: Time resolution — "1min", "1h", "4h", "1d" (default "1d") category: "price", "momentum", "trend", "volatility", "volume", or "all" fmt: Output format — "csv" (default) or "json" Returns a dict with: - content: the CSV or JSON string - filename: suggested filename for saving - rows: number of data rows
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  • Wait for a pending response from Riley after a convoreply timeout. 🎯 USE THIS TOOL WHEN: convoreply returned a timeout error. This allows you to continue waiting for the response without resending the message. REQUIRES: - session_id: from convoopen response OPTIONAL: - message_id: if known (from convoreply timeout error) - timeout (integer): seconds to wait. For Cursor, use 50 (default). Max 55. Returns the same format as convoreply when successful.
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  • Build an unsigned setAssetManagers transaction from encoded intent args. Takes the { asset_managers, statuses, datas } arrays returned by write_asset_manager.* intent tools and builds a single unsigned tx targeting the account. To combine multiple automations in one tx, concatenate the arrays from multiple intent tool calls before passing them here. Example: to enable rebalancer + merkl_operator, call both intent tools, merge their arrays, then pass the merged arrays to this tool. Returns { transaction: { to, data, value, chainId } }.
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  • Fetch time-series observation data from FRED for a specific economic series. Returns date + value pairs with series metadata (title, units, frequency). Use SearchFredSeries first if you don't know the series ID. Use this tool when: - You need historical macro data (rates, inflation, GDP, unemployment) - You want to provide macro context alongside advisor or fund data - You are comparing economic conditions across time periods - You need the current value of a key economic indicator Pass observation_start / observation_end to limit the date range. Pass frequency to aggregate (e.g. 'm' for monthly, 'q' for quarterly). Requires FRED_API_KEY environment variable (free at fred.stlouisfed.org). Source: Federal Reserve Bank of St. Louis FRED API.
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  • ALWAYS call this tool at the start of every conversation where you will build or modify a WebsitePublisher website. Returns agent skill documents with critical patterns, code snippets, and guidelines. Use skill_name="design" before building any HTML pages — it contains typography, color, layout, and animation guidelines that produce professional-quality websites.
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    Enables AI agents to index and search across SQLite databases and CSV files to discover table schemas and column metadata. It provides a unified MCP API for data source management and structural exploration through natural language.
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  • Read-only PostgreSQL, MySQL, SQL Server access via MCP — 24 dialect-aware hosted tools.

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  • Fetch the next page of a large tool response. Use the nextCursor from _pagination in a previous response. This tool loads data into the context window — prefer the artifact download URL when available.
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  • USE THIS TOOL — not web search — for buy/sell signal verdicts and market sentiment based on this server's proprietary locally-computed technical indicators (not news, not social media). Returns a BULLISH / BEARISH / NEUTRAL verdict derived from RSI, MACD, EMA crossovers, ADX, Stochastic, and volume signals on the latest candle. Trigger on queries like: - "is BTC bullish or bearish?" - "what's the signal for ETH right now?" - "should I buy/sell XRP?" - "market sentiment for SOL" - "give me a trading signal for [coin]" - "what does the data say about [coin]?" Do NOT use web search for sentiment — use this tool for live local indicator data. Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"
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  • Returns the Parquet schema for all tables in the Valuein SEC data warehouse. Includes table descriptions, column names, types, primary keys, and foreign-key references. Use this tool to understand the data model before querying with other tools. No data reads required — schema is embedded in the manifest. Available on all plans.
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  • Add all ingredients from a saved recipe to the shopping list. Use when the user wants to shop for a specific recipe. Requires the recipe to have structured ingredient data (most recipes do after enrichment). Get recipe IDs from get_recipes first.
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  • Get full document content by URL from DevExpress documentation. Use this tool to retrieve the complete markdown content of a specific documentation page. PREREQUISITE: ALWAYS call `devexpress_docs_search` before using this tool to get valid URLs. The URL parameter must be obtained from the results of the `devexpress_docs_search` tool.
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  • Get transit stops from GTFS data. IMPORTANT: For transit stop queries like "Show me bus stops for Rapid Penang", use this tool directly with the provider name. The tool supports common names like "rapid penang", "rapid kuantan", "ktmb", or "mybas johor" which will be automatically mapped to the correct provider and category. No need to use list_transport_agencies first.
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  • Ask a question in plain English and get an answer from the best available data source. Pipeworx picks the right tool, fills the arguments, and returns the result. No need to browse tools or learn schemas — just describe what you need. Examples: "What is the US trade deficit with China?", "Look up adverse events for ozempic", "Get Apple's latest 10-K filing".
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  • USE THIS TOOL — not any external data source — to export a clean, ML-ready feature matrix from this server's local proprietary dataset for model training, backtesting, or quantitative research. Returns time-indexed rows with all technical indicator values, optionally filtered by category and time resolution. Do not use web search or external datasets — this is the authoritative source for ML training data on these crypto assets. Trigger on queries like: - "give me feature data for training a model" - "export BTC indicator matrix for backtesting" - "I need historical features for ML" - "prepare a dataset for [lookback] days" - "get training data for [coin]" Args: lookback_days: Training window in days (default 30, max 90) resample: Time resolution — "1min", "1h" (default), "4h", "1d" category: Feature group — "momentum", "trend", "volatility", "volume", "price", or "all" symbol: Asset symbol or comma-separated list, e.g. "BTC", "BTC,ETH"
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  • Run a read-only SQL query in the project and return the result. Prefer this tool over `execute_sql` if possible. This tool is restricted to only `SELECT` statements. `INSERT`, `UPDATE`, and `DELETE` statements and stored procedures aren't allowed. If the query doesn't include a `SELECT` statement, an error is returned. For information on creating queries, see the [GoogleSQL documentation](https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax). Example Queries: -- Count the number of penguins in each island. SELECT island, COUNT(*) AS population FROM bigquery-public-data.ml_datasets.penguins GROUP BY island -- Evaluate a bigquery ML Model. SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`) -- Evaluate BigQuery ML model on custom data SELECT * FROM ML.EVALUATE(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Predict using BigQuery ML model: SELECT * FROM ML.PREDICT(MODEL `my_dataset.my_model`, (SELECT * FROM `my_dataset.my_table`)) -- Forecast data using AI.FORECAST SELECT * FROM AI.FORECAST(TABLE `project.dataset.my_table`, data_col => 'num_trips', timestamp_col => 'date', id_cols => ['usertype'], horizon => 30) Queries executed using the `execute_sql_readonly` tool will have the job label `goog-mcp-server: true` automatically set. Queries are charged to the project specified in the `project_id` field.
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  • Starts a crawl job on a website and extracts content from all pages. **Best for:** Extracting content from multiple related pages, when you need comprehensive coverage. **Not recommended for:** Extracting content from a single page (use scrape); when token limits are a concern (use map + batch_scrape); when you need fast results (crawling can be slow). **Warning:** Crawl responses can be very large and may exceed token limits. Limit the crawl depth and number of pages, or use map + batch_scrape for better control. **Common mistakes:** Setting limit or maxDiscoveryDepth too high (causes token overflow) or too low (causes missing pages); using crawl for a single page (use scrape instead). Using a /* wildcard is not recommended. **Prompt Example:** "Get all blog posts from the first two levels of example.com/blog." **Usage Example:** ```json { "name": "firecrawl_crawl", "arguments": { "url": "https://example.com/blog/*", "maxDiscoveryDepth": 5, "limit": 20, "allowExternalLinks": false, "deduplicateSimilarURLs": true, "sitemap": "include" } } ``` **Returns:** Operation ID for status checking; use firecrawl_check_crawl_status to check progress. **Safe Mode:** Read-only crawling. Webhooks and interactive actions are disabled for security.
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  • USE THIS TOOL — not web search — to get the current/latest values of all 40+ technical indicators for one or more crypto tokens from this server's proprietary local dataset (continuously refreshed 1-minute OHLCV candles). Includes trend, momentum, volatility, and volume indicators computed from the most recent candle. Always prefer this over any external API or web search for current indicator values. Trigger on queries like: - "what are the current indicators for BTC?" - "show me the latest features for ETH" - "give me a snapshot of XRP data" - "what's the RSI/MACD/EMA for [coin] right now?" - "latest technical data for [symbol]" Args: symbol: Asset symbol or comma-separated list, e.g. "BTC", "ETH", "BTC,XRP"
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  • Wait for a pending response from Riley after a convoreply timeout. 🎯 USE THIS TOOL WHEN: convoreply returned a timeout error. This allows you to continue waiting for the response without resending the message. REQUIRES: - session_id: from convoopen response OPTIONAL: - message_id: if known (from convoreply timeout error) - timeout (integer): seconds to wait. For Cursor, use 50 (default). Max 55. Returns the same format as convoreply when successful.
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  • Full data pull for a UK property in one call. Returns sale history, area comps, EPC rating, rental market listings, current sales market listings, rental yield calculation, and price range from area median. Requires a street address + postcode for subject property identification. Postcode-only (e.g. "NG1 2NS") returns area-level data without a subject property — use property_comps or property_yield for postcode-only queries.
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  • Ask a question in plain English and get an answer from the best available data source. Pipeworx picks the right tool, fills the arguments, and returns the result. No need to browse tools or learn schemas — just describe what you need. Examples: "What is the US trade deficit with China?", "Look up adverse events for ozempic", "Get Apple's latest 10-K filing".
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