205,128 tools. Last updated 2026-06-15 05:53
"Google BigQuery" matching MCP tools:
- Lists pre-configured reports (prebuilds) available for a connector. **What is a prebuild?** A prebuild is a standardized report maintained by Quanti for a given connector (e.g., Campaign Stats for Google Ads). It defines the BigQuery table structure (columns, types, metrics) and the associated API query. **When to use this tool:** - When the user asks "what reports are available for [connector]?" - When the user doesn't know which data or metrics exist for a connector - BEFORE get_schema_context, to explore available reports for a connector - To understand the data structure before writing SQL **Difference with get_schema_context:** - list_prebuilds → discover which reports/tables EXIST for a connector (catalog) - get_schema_context → get the actual BigQuery schema for the client project (effective data) **Response format:** Returns a JSON with for each prebuild: its ID, name, description, BigQuery table name, and the list of fields (name, type, description, is_metric). Fields marked is_metric=true are aggregatable metrics (impressions, clicks, cost...), others are dimensions (date, campaign_name...). **SKU examples**: googleads, meta, tiktok, tiktok-organic, amazon-ads, amazon-dsp, piano, shopify-v2, microsoftads, prestashop-api, mailchimp, kwankoConnector
- 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.Connector
- "Hours / phone / reviews of [business]" / "Google business info for [place]" / "is [restaurant] open" — full details for a Google Place: address, phone, hours, website, ratings, user reviews. Requires a place ID from `maps_place_search`. Use after search to drill into one specific business.Connector
- Get Google organic search results for SEO rank tracking. Returns up to 100 results per request with position, title, URL, and snippet. Ideal for monitoring keyword rankings and SERP analysis.Connector
- "Google Maps directions from A to B" / "transit / public-transport directions" / "bus / subway / train route" / "best way to get from [X] to [Y]" — turn-by-turn directions via Google Maps. Modes: driving, walking, transit (bus/subway/train), bicycling. Requires Google Maps API key. PREFER over Mapbox/OpenRouteService specifically for public-transit routing — Google has the best transit data.Connector
- Initiate an OAuth handoff to a vendor integration (Google Ads, GA4, Search Console, Sheets, Drive, BigQuery, Meta Ads, Jira, Confluence). Returns an authorization URL the user opens in a browser. After the user clicks Allow, the connection is created and you can poll check_integration_status(handoff_id) to find out when the data is ready.Connector
Matching MCP Servers
- Alicense-qualityDmaintenanceGoogle BigQuery MCP Server by CDataLast updatedMIT
- Alicense-qualityDmaintenanceEnables natural language exploration and querying of Google BigQuery datasets through four tools: listing datasets, inspecting table schemas, generating SQL queries with LLM assistance, and executing approved queries.Last updated1MIT
Matching MCP Connectors
The BigQuery remote MCP server is a fully managed service that uses the Model Context Protocol to connect AI applications and LLMs to BigQuery data sources. It provides secure, standardized tools for AI agents to list datasets and tables, retrieve schemas, generate and execute SQL queries through natural language, and analyze data—enabling direct access to enterprise analytics data without requiring manual SQL coding.
Local business lead extraction with email + phone enrichment from Google Maps.
- Lists directly accessible Google Ads customers for the configured Google Ads credentials, including descriptive names when Google returns them. Use this to discover customer IDs before running Google Ads hierarchy or reporting tools.Connector
- Deletes an aggregation view (materialized view or procedure) from the project. **When to use this tool:** - When the user explicitly asks to delete/drop a view - To clean up unused or obsolete aggregations - When the project has reached the maximum number of views (20) **Warning:** This marks the view as dropped in Quanti's tracking. The actual BigQuery object may need manual cleanup. **Tip:** Use list_aggregation_views first to get the view ID.Connector
- "Travel time matrix between [N] origins and [M] destinations" / "drive-time grid via Google Maps" / "transit times between addresses" — N×M distance and duration matrix between many points via Google Maps. Modes: driving, walking, bicycling, transit. Use for delivery routing, multi-stop optimization, transit-heavy planning.Connector
- Resolves a list of Google Maps URLs into canonical Google Maps Place IDs. **When to call this tool (CRITICAL):** * Use this tool when the user provides one or more Google Maps sharing links or URLs (e.g. 'https://maps.app.goo.gl/...', 'https://www.google.com/maps/place/...', or 'https://maps.google.com/...') and you need to extract the underlying canonical Place IDs. * You can specify up to 20 URLs to resolve in a single batch request. **Input Requirements (CRITICAL):** * **`urls` (array of strings - MANDATORY):** The list of Google Maps URLs to resolve. Each URL must be a valid, single-place Google Maps URL. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some URLs resolve successfully while others fail). * The output list of `entities` is guaranteed to map 1:1 with the input `urls` indices. A failed URL resolution will result in an empty `Entity` message (no fields are set) at its corresponding index in the `entities` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific URL index failed. The key of `failed_requests` represents the 0-based index of the failed URL in the request. Do not assume the entire batch call failed because of a partial failure.Connector
- 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, transformationsConnector
- Run a SQL query in the project and return the result. Prefer the `execute_sql_readonly` tool if possible. This tool can execute any query that bigquery supports including: * SQL Queries (SELECT, INSERT, UPDATE, DELETE, CREATE, etc.) * AI/ML functions like AI.FORECAST, ML.EVALUATE, ML.PREDICT * Any other query that bigquery supports. Example Queries: -- Insert data into a table. INSERT INTO `my_project.my_dataset`.my_table (name, age) VALUES ('Alice', 30); -- Create a table. CREATE TABLE `my_project.my_dataset`.my_table ( name STRING, age INT64); -- DELETE data from a table. DELETE FROM `my_project.my_dataset`.my_table WHERE name = 'Alice'; -- Create Dataset CREATE SCHEMA `my_project.my_dataset` OPTIONS (location = 'US'); -- Drop table DROP TABLE `my_project.my_dataset`.my_table; -- Drop dataset DROP SCHEMA `my_project.my_dataset`; -- Create Model CREATE OR REPLACE MODEL `my_project.my_dataset.my_model` OPTIONS ( model_type = 'LINEAR_REG' LS_INIT_LEARN_RATE=0.15, L1_REG=1, MAX_ITERATIONS=5, DATA_SPLIT_METHOD='SEQ', DATA_SPLIT_EVAL_FRACTION=0.3, DATA_SPLIT_COL='timestamp') AS SELECT col1, col2, timestamp, label FROM `my_project.my_dataset.my_table`; Queries executed using the `execute_sql` tool will have the job label `goog-mcp-server: true` automatically set. Queries are charged to the project specified in the `project_id` field.Connector
- Get keyword ideas with real search volume, competition, and CPC data from Google Ads Keyword Planner. Provide seed keywords and/or a URL to discover new keyword opportunities. Returns avg monthly searches, competition level, average CPC, and top-of-page bid estimates. No Google Ads account connection required — works for all users. Use searchGeoTargets first to find geo target IDs for location targeting. Keyword Planner is a separate API (not GAQL) — use this tool, not runScript.Connector
- User-facing render tool for Google Ads visual weekly reports. Use this directly for prompts like 'show me a Google Ads report', 'generate a Google Ads dashboard', or 'show 7/30/90-day Google Ads performance'. Do not first call google_ads_get_weekly_group_report unless you already need raw data for a non-visual answer; when this visual report renders, keep any assistant text to a brief confirmation.Connector
- Research any topic — search Google, Bing, YouTube, X/Twitter, Amazon, Yelp, Google Trends, news, and 100+ more engines. Read webpages, extract video transcripts, find reviews, track competitors. Works without a domain.Connector
- Resolves a list of Google Maps URLs into canonical Google Maps Place IDs. **When to call this tool (CRITICAL):** * Use this tool when the user provides one or more Google Maps sharing links or URLs (e.g. 'https://maps.app.goo.gl/...', 'https://www.google.com/maps/place/...', or 'https://maps.google.com/...') and you need to extract the underlying canonical Place IDs. * You can specify up to 20 URLs to resolve in a single batch request. **Input Requirements (CRITICAL):** * **`urls` (array of strings - MANDATORY):** The list of Google Maps URLs to resolve. Each URL must be a valid, single-place Google Maps URL. **Error Handling (CRITICAL):** * This is a batch processing tool. A request might return "mixed results" (e.g. some URLs resolve successfully while others fail). * The output list of `entities` is guaranteed to map 1:1 with the input `urls` indices. A failed URL resolution will result in an empty `Entity` message (no fields are set) at its corresponding index in the `entities` list. * You **MUST** check the `failed_requests` map field in the response to identify which specific URL index failed. The key of `failed_requests` represents the 0-based index of the failed URL in the request. Do not assume the entire batch call failed because of a partial failure.Connector
- Pause a POSITIVE (active) keyword. Does NOT work on negative keywords — Google Ads has no 'pause' for negatives; call `removeNegativeKeyword` instead (and `addNegativeKeyword` to re-add later). Returns changeId.Connector
- List configured review platforms (Google, Hipages, Facebook, etc) with their URLs. Useful for knowing where to direct review requests.Connector
- Returns busy windows from YOUR connected Google calendar within a time window, plus free intervals of at least the requested minimum length. Use this to check your own availability before scheduling anything — gatherings, calls, anything. The 'busy' result is sourced directly from your Google calendar's freeBusy API; no event titles or details are returned, only the time ranges. Requires an active Google calendar connection (call lyra_connect_calendar first if you don't have one) and API key authentication. Returns a clear error if no calendar is connected.Connector
- Returns the parent's personal iCal feed URL — subscribe in Google/Apple/Outlook Calendar to see practices + games in your normal calendar app. Refreshes hourly.Connector