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521,841 tools. Updated 2026-09-06 12:28

"Google BigQuery" matching MCP tools:

  • Upsert the virtual dimension draft for an existing `virtualDimensionId` — updates a pending draft or seeds one from published state when none exists (response may include `warning: "Initialized draft from published state"`). `virtualDimensionId` in inputs equals `id` from list/get/search. Use create_virtual_dimension_draft only for brand-new VDIMs. Call get_skill with skillId: "virtual-dimensions" first — see skill for allocation shapes and workflow. For a new `telemetry` allocation, discover a live integration metric via list_metrics with includeExternal: true and a specific search term, then persist inline `externalMetric` { provider, integrationId, metricName, aggregator, groupByFields }. For BigQuery/S3, also set dateColumn and metricColumn from the returned `schema` (first DATE / first NUMERIC) and gapFillingMethod (default FORWARD_FILL). Catalog-complete providers (Tsuga, Datadog, CloudWatch, Amplitude, Google Cloud Monitoring) do not need those fields. Do not set `datasource` on new reallocations (echo a leftover stored `datasource` unchanged unless the user asks to switch). `bqName` is immutable; use returned `bqName` for groupBy/filterCel in query. Declarative: `rules` is optional — omit to change only metadata (`name`, `description`, `tagNames`); when provided, fully replaces the rules array. Omitting `rules` on a published-only VDIM still persists a draft (metadata-only promotion). Carry forward each existing rule's `id` and `allocation` from get; ids are sticky — reorder by moving `id` with its rule. Do not include leftover in `rules`. Rejects invalid payloads — nothing persisted unless validation passes. On success: `values`, `draftValidation: { ok: true }`, `draftPersisted: true`. Does not publish or refresh BigQuery. Clerk MCP only. EXAMPLE: "Add staging to Environment VDIM" — `rules` is the full desired set → { virtualDimensionId: "<id from create/list>", rules: [{ id: "<uuid from get>", name: "Production", conditionCel: "cos_environment in [\"prod\"]", allocation: { allocationType: "dimensionValue", dimensionValue: "prod" } }, { name: "Staging", conditionCel: "cos_environment in [\"staging\"]", allocation: { allocationType: "dimensionValue", dimensionValue: "staging" } }] }
    ConnectorOAuth
  • Create a new virtual dimension draft without publishing. `virtualDimensionId` in inputs equals `id` from list/get/search. Call get_skill with skillId: "virtual-dimensions" first — see skill for allocation shapes, CEL rules, and full workflow. For a new `telemetry` allocation, discover a live integration metric via list_metrics with includeExternal: true and a specific search term, then persist inline `externalMetric` { provider, integrationId, metricName, aggregator, groupByFields }. For BigQuery/S3, also set dateColumn and metricColumn from the returned `schema` (first DATE / first NUMERIC) and gapFillingMethod (default FORWARD_FILL). Catalog-complete providers (Tsuga, Datadog, CloudWatch, Amplitude, Google Cloud Monitoring) do not need those fields. Do not set `datasource` on new reallocations. `bqName` (BigQuery/CEL query field, e.g. Environment → virtual_environment) is set once from `name` at create and is immutable. Ordered `rules` use `conditionCel` + `allocation` — do not send rule `id` (generated on save) or `values` (derived). Do not include catch-all/leftover in `rules` — `leftoverRule` is auto-added. Rejects invalid payloads — nothing persisted unless validation passes. On success: `virtualDimensionId`, `bqName`, `name`, `description`, `tags`, `values`, rules with generated ids, `leftoverRule`, `draftValidation: { ok: true }`, `draftPersisted: true`. Use preview_virtual_dimension_draft next. Use returned `bqName` for groupBy/filterCel in query after publish. Does not publish or refresh BigQuery. Clerk MCP only. EXAMPLE: "Draft an Environment VDIM with a prod rule" → { name: "Environment", tagNames: ["finops"], rules: [{ name: "Production", conditionCel: "cos_environment in [\"prod\"]", allocation: { allocationType: "dimensionValue", dimensionValue: "prod" } }] }
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  • List the Google Business Profile listings SHARED WITH THIS BRAND — id, title, address, website and Maps link. These are the only listings anything here can post to or read: one Google login often manages several businesses (an agency manages its clients’), and the user ticks which of them belong to this brand. Call this before posting whenever more than one is shared and let the USER pick: a Post on the wrong storefront is a public mistake Hermoso will not make for them. If nothing is shared, ask the user to choose — list_connector_accounts("google_business") then set_connector_accounts — and never name or guess a listing. Read-only, 0 credits. Needs Google Business Profile connected (Settings ▸ Connectors ▸ Google Business Profile).
    ConnectorNo auth
  • Read the text of a Google Doc Hermoso can reach — one it created, or one the user handed over with the Google file picker in the app (that is how an EXISTING doc becomes readable; find its id with list_drive_files). Pass documentId (from create_doc) OR paste a Google Docs URL as docUrl. Under the drive.file scope it reaches nothing else in the user’s Drive; if Google answers that the file was not found, the user has not picked it yet — ask them to pick it in the app rather than retrying. Returns the plain text. Read-only, free.
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  • Create a new Google Doc in the user's Drive. The content is inserted as plain text — Markdown is NOT rendered, so headings and bold written here arrive as literal ** and # characters. To produce a formatted document, create it and then call format_document, which converts Markdown into real Google Docs styling.
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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: ```sql -- 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 always have the job label `goog-mcp-server: true` automatically set in addition to any custom `labels` provided in the request. Queries are charged to the project specified in the `project_id` field.
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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.

  • Search Google Maps businesses via MCP - name, address, phone, rating, hours, GPS.

  • Get photos for a Google Maps place. Provide place_id from search results. The identifier also accepts the business identifier form (0x...:0x...). Optional cursor, region, and language are supported. Pass cursor from a previous cursor_next to fetch the next page. Returns place metadata and a photos array. Each photo has photo_url and description when available. cursor_next appears only when a pagination cursor is available. Additional upstream fields may appear. Cost = 3 tokens.
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  • List supported Google Maps place type values for search filters. Returns place_types as a string array. Use a value with place_type on google-maps.search or google-maps.nearby_search. Cost = 1 token.
    ConnectorNo auth
  • List all Google Trends category and subcategory labels you can pass to other Google Trends tools in the category field. Returns cat (array of category names, including All categories) and msg. Use this before interest-over-time or interest-by-region calls when filtering by category. Cost = 5 tokens.
    ConnectorNo auth
  • List all countries and subregions you can pass to other Google Trends tools in the country and region fields. Returns geo.countries: each country name maps to country (label) and regions (array of subregion names). Also returns msg. Use this before interest-over-time or interest-by-region calls when filtering by geography. Pair with google-trends.categories when filtering by category. Cost = 5 tokens.
    ConnectorNo auth
  • PUBLISH a reply to this review's public Google profile. This is a public, customer-visible action - call it ONLY when the user has explicitly approved this exact text. If Google rejects the publish, the text is preserved in ReputeMap with a manual fallback (status 'manual_required') - words are never lost.
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  • List saved Costory business metrics and, optionally, matching live external metrics from connected integrations (e.g. Tsuga, BigQuery, Datadog, CloudWatch, Google Cloud Monitoring). Saved metrics return id/name/type for { type: "metric", metricId: "..." } in query. Set includeExternal: true with a specific search term to return externalMetrics with provider, integrationId, integrationName, metricName, unit, capabilities, and attributes. That catalog is enough to build { type: "externalMetric", provider, integrationId, metricName, aggregator, groupByFields, conditions } for Tsuga, Datadog (attributes are tag keys; metricName is the Datadog metric name), CloudWatch (metricName is Namespace/MetricName such as AWS/EC2/CPUUtilization; attributes are dimension names), Google Cloud Monitoring (provider "cloudmonitoring"; metricName is the metric type such as compute.googleapis.com/instance/cpu/utilization; attributes are fully-qualified group-by fields such as metric.label.state or resource.label.project_id, and conditions is an optional Monitoring filter), or Amplitude. For BigQuery or S3, the same hit also includes `schema` (typed columns: DATE / NUMERIC / STRING). Pick dateColumn from the first DATE field, metricColumn from the first NUMERIC field, and groupByFields from STRING fields (also listed in attributes). gapFillingMethod is not in the catalog — default FORWARD_FILL unless the user specifies ZERO, LINEAR_INTERPOLATION, or SPREAD. Those three fields are required on both query and a new virtual-dimension telemetry allocation. Do not call includeExternal without search; external catalogs can be large, and the tool will ask for a search term instead of listing everything. externalLimit (default 50, max 50) caps matching external results. New virtual-dimension telemetry reallocations use includeExternal + an inline `externalMetric` (same fields as a query series, plus exactly one groupByFields entry as the series key). Pass `datasourceId` only to inspect a leftover saved usage-metric datasource's `groupByDimensions` — not for new reallocations. Then call `query` (`type: "metric"`, `metricId`, `groupBy`) to inspect the values for that leftover datasource. The `datasourceId` is the same `metricsDatasource` id this tool returns as a saved-metric `id` (strip any `::metricName` suffix). Does **not** return values (use `query`). EXAMPLES: • "What business metrics do we have?" → {} • "Find Tsuga metrics about requests" → { includeExternal: true, search: "request" } • "Find BigQuery tables about revenue" → { includeExternal: true, search: "revenue" } • "Find Datadog metrics about CPU" → { includeExternal: true, search: "cpu" } • "Find CloudWatch metrics about CPU" → { includeExternal: true, search: "CPUUtilization" } • "Find GCP Monitoring metrics about CPU" → { includeExternal: true, search: "cpu/utilization" } (Cloud Monitoring search matches the metric type, not its display name) • "What live metrics can I reallocate shared cost by?" → { includeExternal: true, search: "cpu" } • "What can I split a leftover saved-metric datasource by?" → { datasourceId: "clx…" }
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  • Convert a SQL statement from one dialect to another — mysql, postgres, sqlite, tsql, oracle, snowflake, bigquery, redshift, spark, hive, presto, trino, duckdb, clickhouse, databricks, doris, starrocks and more. Deterministic parser (sqlglot), not an LLM: the same input always produces the same output, and syntax errors come back with the exact line and column. Use it when migrating queries between databases or debugging dialect-specific syntax.
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  • Deletes a file or an empty folder from the synced Google Drive folder — Google Drive for Desktop syncs the deletion to the cloud (the item lands in Drive's trash). Deleting a .gdoc/.gsheet/.gslides pointer removes the real Google Doc/Sheet/Slides. Never deletes a folder that still has contents. First call returns a preview of what was actually found at that path; pass confirm=true to delete.
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  • Cancel (delete) one reminder by its reminderId (ids come from list_reminders or create_reminder). The saved item itself is not touched. Reminders synced to Google Calendar cannot be cancelled here - the user manages those at mark-it.co or in Google Calendar.
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    Destructive
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  • List sitemaps submitted for a Search Console property. Call google-search-console.list_sites to discover sites. Omit site_url to use the default property, or pass an exact site_url from that response. Returns sitemap paths plus submission, download, warning, and error details. Use an exact path from this response with get_sitemap, submit_sitemap, or delete_sitemap. Cost = 5 tokens.
    ConnectorNo auth
  • List Search Console properties for this account. Returns Vee3-managed domains plus sites added with google-search-console.add_site. Call this to discover sites, then omit site_url on later calls to use the default property, or pass an exact site_url from this response. If no properties appear, add a site with google-search-console.add_site or register a domain with domains.register. Cost = 5 tokens.
    ConnectorNo auth
  • Read cells from a Google Sheet Hermoso can reach — one it created, or one the user handed over with the Google file picker in the app (that is how an EXISTING spreadsheet becomes readable; find its id with list_drive_files). Pass the spreadsheetId (from create_sheet) OR paste a Google Sheets URL as sheetUrl. If Google answers that the file was not found, the user has not picked it yet — ask them to pick it in the app rather than retrying. Returns a 2-D array of values.
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  • ÉCRITURE GARDÉE : met un mot-clé en pause (réversible dans Google Ads). ids via ads_keywords. Sans confirm:true : dry-run validé par Google. Pilotage requis (write_enabled) ; journalisé.
    ConnectorNo auth
  • Publish a Post to the brand’s Google Business Profile — the panel that appears on Google Search and Maps for the business. Text, optionally ONE PHOTO, and a call-to-action button. Google’s Posts API accepts NO VIDEO, so pass a still image. This PUBLISHES immediately and publicly on the business listing — show the user the exact text, photo and button and get an explicit yes BEFORE calling. If the account manages several listings, call list_business_locations first and pass locationId. EVENT and OFFER posts both REQUIRE a title and a start date (Google’s rule). On an OFFER, Google IGNORES the button’s link — pass redeemOnlineUrl instead. A CALL button dials the number on the listing and takes no link. Needs Google Business Profile connected (Settings ▸ Connectors ▸ Google Business Profile).
    ConnectorNo auth