"Google BigQuery cloud data warehouse service" matching MCP tools:

• census_list_sourcesB

  Census MCP by usefulapiA

  List configured data warehouse sources (Snowflake, BigQuery, Redshift, Databricks, etc.). Census: GET /sources.

  ConnectorNo auth

• preview_stock_operationA

  wals.pro AI 4 weclappA

  Preview warehouse stock movements, transport orders and internal deliveries, issuing one approval token. Per-operation required parameters: * ``movement`` — documentless booking. kind + article_id or article_number + quantity (omit for serial-tracked) + places: INCOMING_WITHOUT_REFERENCE -> target_storage_place_id; OUTGOING_WITHOUT_REFERENCE -> source_storage_place_id; DIRECT_TRANSFER (same warehouse) -> source + destination storage place. Tracked stock: serial_numbers / batch_number; optional batch_expiration_date, valuation_price, movement_note. * ``internal_delivery`` — warehouse-to-warehouse via INTERNAL shipment (the only cross-warehouse channel). mode (CREATE_ONLY | COMPLETE_NOW) + source/destination_warehouse_id + items. * ``transport_order`` — same-warehouse pick/transit/put-down (Transportauftrag). mode (CREATE_ONLY | COMPLETE_NOW | RESUME); RESUME needs transportation_order_id, create modes destination_storage_place_id + items (each with source_storage_place_id); optional loading-equipment pair. Args: operation: ``movement``, ``internal_delivery`` or ``transport_order``; foreign parameters are rejected. items: {article_id/article_number, quantity (omit for serial articles), source_storage_place_id?, batch_number?, serial_numbers?}. Full semantics: get_schema(entity="warehouseStockMovement", detail="payload_guide"). Receipts: preview_entity_action purchaseOrder.bookIncomingGoods. Customer shipments: salesOrder.createShipment. Returns plan + approval + 'execution', or diagnostics (ready_for_write=false). when_to_use: corrections, found/lost stock, scrapping, seeding, relocations, inter-warehouse deliveries; after the user explicitly confirms, execute_approved. preconditions: STORABLE articles; exact serial/batch identity; stock available at the source. post_effects: no ERP mutation; the token binds the plan and live stock baseline — drift forces a fresh preview.

  ConnectorOAuth

• create_virtual_dimension_draftA

  Costory: Your Finops MCPA

  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" } }] }

  ConnectorOAuth

• fastero_run_sqlA

  FasteroB

  Run a read-only query against one of this organisation's connected databases — PostgreSQL, MySQL, SQL Server, Redshift, Snowflake, Oracle, BigQuery or Google Sheets — in that connection's own SQL dialect, and return rows. One SELECT, WITH, EXPLAIN or SHOW statement; a statement that could change data is refused. It returns at most 500 rows and about 100 KB: a larger result comes back cut, with truncated: true and totalRows, so prefer a LIMIT or an aggregate. Where a question involves a business number (revenue, churn, active users…), fastero_get_definitions holds this organisation's own expression for it.

  ConnectorAPI key

• list_dataset_idsA

  Google Big QueryA

  List BigQuery dataset IDs and BigLake namespaces in a Google Cloud project. Supports pagination. Use `page_size` to limit results and `page_token` to retrieve next page.

  ConnectorNo auth

• gcpinspectA

  InsideOut (Riley)A

  INSPECTION: Inspect GCP infrastructure for a deployed project ⚠️ **PREREQUISITE**: This tool requires a prior deployment ATTEMPT (successful or failed). Check convostatus for hasDeployAttempt=true before calling. Works even after failed deploys to inspect orphaned resources. Inspect deployed GCP resources after a deployment attempt. Use this tool when the user asks about the status or details of their deployed GCP infrastructure. It fetches temporary read-only credentials securely and queries the GCP API directly. RESPONSE TIERS (default is summary for token efficiency): - Summary (default): Key fields only (~500 tokens). Set detail=false, raw=false or omit both. - Detail: Full metadata for a specific resource. Set detail=true + resource filter. - Raw: Complete unprocessed API response. Set raw=true. REQUIRES: session_id from convoopen response (format: sess_v2_...). Supported services: apigateway, bastion, billing, certificatemanager, cloudarmor, cloudbuild, cloudcdn, clouddeploy, clouddns, cloudfunctions, cloudkms, cloudlogging, cloudmonitoring, cloudrun, cloudsql, compute, firestore, gcs, gke, iam, identityplatform, loadbalancer, memorystore, pubsub, secretmanager, vertexai, vpc For a specific service's actions, call with action="list-actions". METRICS: Use list-metrics to see available Cloud Monitoring metrics for any service (no credentials needed — progressive disclosure). Use get-metrics to retrieve time-series data. Optional filters JSON: {"hours":6,"period":300}. Label breakdowns: Cloud Functions (by status), Load Balancer/API Gateway (by response_code_class), Cloud CDN (by cache_result). Secret Manager get-metrics returns operational health (version count, replication, create time) — no time-series. Bastion is an alias for Compute Engine metrics (SSH connection count not available as a GCP metric). BILLING: Use service=billing to inspect GCP billing. Actions: get-billing-info (check if billing enabled, which billing account), get-budgets (list budget alerts for the project — auto-fetches billing account). Requires roles/billing.viewer IAM role. Required IAM roles: Monitoring Viewer (roles/monitoring.viewer) for metrics, Secret Manager Viewer (roles/secretmanager.viewer) for secret health, Billing Viewer (roles/billing.viewer) for billing. EXAMPLES: - gcpinspect(session_id=..., service="compute", action="list-instances") - gcpinspect(session_id=..., service="gke", action="list-clusters") - gcpinspect(session_id=..., service="cloudsql", action="get-metrics", filters="{\"hours\":6}") - gcpinspect(session_id=..., service="billing", action="get-billing-info")

  ConnectorNo auth

• gcpinspectA

  InsideOut (Riley)A

  INSPECTION: Inspect GCP infrastructure for a deployed project ⚠️ **PREREQUISITE**: This tool requires a prior deployment ATTEMPT (successful or failed). Check convostatus for hasDeployAttempt=true before calling. Works even after failed deploys to inspect orphaned resources. Inspect deployed GCP resources after a deployment attempt. Use this tool when the user asks about the status or details of their deployed GCP infrastructure. It fetches temporary read-only credentials securely and queries the GCP API directly. RESPONSE TIERS (default is summary for token efficiency): - Summary (default): Key fields only (~500 tokens). Set detail=false, raw=false or omit both. - Detail: Full metadata for a specific resource. Set detail=true + resource filter. - Raw: Complete unprocessed API response. Set raw=true. REQUIRES: session_id from convoopen response (format: sess_v2_...). Supported services: apigateway, bastion, billing, certificatemanager, cloudarmor, cloudbuild, cloudcdn, clouddeploy, clouddns, cloudfunctions, cloudkms, cloudlogging, cloudmonitoring, cloudrun, cloudsql, compute, firestore, gcs, gke, iam, identityplatform, loadbalancer, memorystore, pubsub, secretmanager, vertexai, vpc For a specific service's actions, call with action="list-actions". METRICS: Use list-metrics to see available Cloud Monitoring metrics for any service (no credentials needed — progressive disclosure). Use get-metrics to retrieve time-series data. Optional filters JSON: {"hours":6,"period":300}. Label breakdowns: Cloud Functions (by status), Load Balancer/API Gateway (by response_code_class), Cloud CDN (by cache_result). Secret Manager get-metrics returns operational health (version count, replication, create time) — no time-series. Bastion is an alias for Compute Engine metrics (SSH connection count not available as a GCP metric). BILLING: Use service=billing to inspect GCP billing. Actions: get-billing-info (check if billing enabled, which billing account), get-budgets (list budget alerts for the project — auto-fetches billing account). Requires roles/billing.viewer IAM role. Required IAM roles: Monitoring Viewer (roles/monitoring.viewer) for metrics, Secret Manager Viewer (roles/secretmanager.viewer) for secret health, Billing Viewer (roles/billing.viewer) for billing. EXAMPLES: - gcpinspect(session_id=..., service="compute", action="list-instances") - gcpinspect(session_id=..., service="gke", action="list-clusters") - gcpinspect(session_id=..., service="cloudsql", action="get-metrics", filters="{\"hours\":6}") - gcpinspect(session_id=..., service="billing", action="get-billing-info")

  ConnectorNo auth

• get_solana_market_statusA

  TWZRD Agent IntelligenceB

  Health probe for the Solana Market API data backend. Call this to gate or degrade gracefully BEFORE the other get_solana_market_* tools: it does a short-timeout hit on the data service and reports whether it is reachable, so an agent can tell "market has no data" from "service is down" without failing a real query. Free discovery tool. When the market data service exposes /status, the response includes prod_key_configured, data_first_available, and an actionable note describing what to configure for full on-chain visibility.

  ConnectorNo auth

• build_go_liveA

  SuperoB

  PERMANENT deploy: promote a published version to a PERMANENT public URL at <service>.supero.live (managed Cloud Run) — unlike build_deploy(target='cloud_ephemeral'), which is a ~30-min throwaway. If version_uuid/file_id are omitted, the latest published version for the project is used. Returns public_url + poll_url; poll with build_deploy_status until live, then build_smoke_test the public_url. build_teardown removes it. Requires a domain- or project-admin API key + platform cloud-deploy enablement.

  Connector

  Destructive

  No auth

• create_google_structured_snippet_extensionA

  Metadata MCP ConnectorA

  Add a labeled list of offerings (structured snippet) shown beneath a Google Ads ad — a category header plus 3-10 short items, e.g. header "Brands" with values "Nest", "Nexus", "Chromebook", or header "Services" with "Hosting", "DNS", "CDN". Helps searchers self-qualify before clicking. ALSO KNOWN AS: structured snippet, snippet, category list, offering list, header values, product list, service list KEYWORDS: structured snippet, snippet, header, values, brands, services, products, courses, destinations, list, category, google ads, extension WHEN TO USE: - "Add a structured snippet listing our service tiers" - "Create a snippet under 'Brands' with Nest, Nexus, Chromebook" - "Register a list of supported integrations as a snippet extension" - "Show our product categories below our Google Ads" WHEN NOT TO USE: - Want a single phrase (e.g. "Free Shipping") → use create_google_callout_extension - Want clickable links to subpages → use create_google_sitelink_extension - Want a pricing table (with amounts) → use create_google_price_extension - Same snippet for Microsoft Ads / Bing → use create_microsoft_structured_snippet_extension INPUTS: - header: snippet category title (1-25 chars). The Google-Ads vocabulary requires picking one of Google's predefined header names ("Brands", "Models", "Service catalog", "Insurance coverage", etc.) — pass the chosen header string here. - values: 3-10 items, each 1-25 chars. EXAMPLE: create_google_structured_snippet_extension( header="Brands", values=["Nest", "Nexus", "Chromebook"], )

  ConnectorAPI key

• manage_booking_resourcesA

  IgnixB

  Set up who or what is booked (the People & rooms of Appointments in the app): each one has its weekly opening hours, days off and spots (how many customers at the same time, e.g. 1 for a person, 6 for a class). "create" needs name and hours; "update" changes only what you pass (hours and timeOff are replaced as a whole when given: read the current ones in get_booking_settings first); "delete" removes it and takes it off every service (its Google calendar is NOT deleted). When Google Calendar is connected, a new one gets its own Google calendar automatically. Which services each one does is set on the service (manage_booking_services, resourceIds). Hours are in the business time zone. Confirm deletions with the user.

  Connector

  Destructive

  OAuth

• execute_sql_readonlyA

  Google Big QueryA

  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). IMPORTANT: For predictive and analytical tasks (forecasting, anomaly detection, key driver / root cause analysis, classification, churn prediction, or text generation), ALWAYS execute computation in-warehouse using BigQuery native AI/ML functions (`AI.FORECAST`, `AI.DETECT_ANOMALIES`, `AI.KEY_DRIVERS`, `AI.CLASSIFY`, `AI.GENERATE`) rather than exporting raw rows to a local Python sandbox. In-warehouse execution scales to billions of rows, preserves governance, and eliminates data egress latency. 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 -- 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) -- Detect anomalies in time series data using AI.DETECT_ANOMALIES SELECT * FROM AI.DETECT_ANOMALIES( TABLE `project.dataset.historical_metrics`, TABLE `project.dataset.recent_metrics`, data_col => 'num_requests', timestamp_col => 'timestamp' ) -- Identify key drivers of metric changes using AI.KEY_DRIVERS SELECT * FROM AI.KEY_DRIVERS( TABLE `project.dataset.sales_summary`, metric_col => 'total_revenue', dimension_cols => ['region', 'product_category'], interest_label_col => 'is_current_quarter' ) -- Classify text into categories using AI.CLASSIFY SELECT ticket_id, AI.CLASSIFY(ticket_text, ['Billing', 'Technical Support', 'Feature Request']) AS category FROM `project.dataset.support_tickets` -- Generate text or summaries using AI.GENERATE SELECT review_id, AI.GENERATE(CONCAT('Summarize this customer review: ', review_text)).result AS summary FROM `project.dataset.reviews` ``` 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. Query Execution Behavior: * If the query completes within the synchronous timeout (default 20 seconds or custom `timeout_ms`), the tool returns `job_complete: true` and the result rows directly. For fast queries, `job_id` may be omitted as no persistent background job is created; no further action or polling is needed. * If the query takes longer than `timeout_ms`, the tool returns `job_complete: false` and a `job_id`. In this case, use the `get_query_results` tool with `job_id` to poll until `job_complete: true`, or use `cancel_job` to abort the running query. * You can optionally specify `timeout_ms` to configure the maximum synchronous wait time in milliseconds (defaults to 20,000 ms), and `job_timeout_ms` to enforce a hard server-side timeout after which BigQuery automatically terminates the job.

  ConnectorNo auth

• get_page_performanceA

  rankparse-mcpA

  Google PageSpeed Insights report for a URL: Lighthouse performance/accessibility/SEO scores and Core Web Vitals (LCP, CLS, INP, FCP, TTFB), with lab and field (CrUX) data. Defaults to mobile; pass strategy=desktop for the desktop profile. Subject to a per-user daily cap (50/day) and a service-wide daily cap; successful responses are cached for 24h.

  ConnectorNo auth

• list_metricsA

  Costory: Your Finops MCPA

  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…" }

  ConnectorOAuth

• gdrive_delete_fileA

  Local MCPB

  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.

  Connector

  Destructive

  OAuth

• connect_googleA

  Pollen — Managed Agent-Readiness LayerA

  Start (or restart) connecting the merchant's Google Merchant Center to Pollen. Returns an authUrl that the HUMAN must open in a browser to grant Google consent - an agent cannot click it. After they approve, call get_google_connect_status to see where the flow landed (it may pause on an account picker or Terms-of-Service acceptance; resume with pick_google_account / accept_google_terms). Once active, Pollen publishes the enriched catalog automatically.

  ConnectorOAuth

• accept_google_termsA

  Pollen — Managed Agent-Readiness LayerA

  Resume a greenfield Google connect paused on Terms-of-Service acceptance (status tos_required). Only call this after the merchant has confirmed they accept the Google Merchant Center ToS (termsUrl from get_google_connect_status). Creates their Merchant Center account and finishes the handshake.

  ConnectorOAuth

• search_api_referenceA

  docs-mcpA

  Search Redpanda API reference documentation by keyword. Returns up to 20 matching endpoints, schemas, or topics with URL, title, and text excerpts. SCOPING (important for accurate results): - api="all" or omit: Search across ALL APIs at once - useful when unsure which API contains the endpoint - api="admin": Search only cluster management (brokers, partitions, configs, users, maintenance) - api="cloud-controlplane": Search only Cloud resource management (clusters, networks, namespaces) - api="cloud-dataplane": Search only Cloud data operations (topics, ACLs, connectors) - api="http-proxy": Search only HTTP Proxy (produce, consume, offsets over HTTP) - api="schema-registry": Search only Schema Registry (register, retrieve, compatibility) WHEN TO USE WHICH: - User asks "broker endpoints" → api="admin" (brokers are cluster management) - User asks "create topic API" → api="all" (topics exist in admin AND cloud-dataplane) - User asks "Cloud cluster API" → api="cloud-controlplane" - User asks about Redpanda APIs generally → api="all" or omit For general Redpanda questions (not API-specific), use ask_redpanda_question instead.

  ConnectorOAuth

• data_describeA

  AMZ VaultA

  Without arguments: list every warehouse dataset available to data_query. With dataset_key: its columns, column descriptions, and a sample row.

  ConnectorOAuth

• list_tablesA

  Strasmore market dataA

  List every table in the Strasmore US market-data warehouse (equities, options, corporate actions, fundamentals, SEC filings, news, macro) with a one-line description, the column its history window filters on, and whether this no-key access can read it. Call this first.

  ConnectorNo auth

• propose_servicesA

  ShearQuery — Barber & Beauty Industry DataA

  Draft adding or removing services, using ids from my_service_options, plus custom services Google does not list. Every service not named stays on the listing. Creates a DRAFT only — nothing on Google changes. Show the owner the draft this returns, word for word, and publish it with publish_change only after they say yes.

  ConnectorNo auth