"SQL Queries for Snowflake Database Administration" matching MCP tools:

• earthquake_get_feed

  earthquake-mcp-server

  Fetch a USGS pre-computed real-time earthquake feed by magnitude tier and time window. These feeds are CDN-cached by USGS and faster and more available than the query API — use them for "what's happening now" queries. "all" includes microseisms (M<1); "significant" is a USGS curation based on magnitude, felt reports, and PAGER impact estimates. "hour" returns 0–10 events typically; "month" can exceed 10,000 for the "all" tier. For historical or filtered queries, use earthquake_search instead.

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• shippingrates_search

  ShippingRates MCP Server

  Search the ShippingRates database by keyword — matches against carrier names, port names, country names, and charge types. Use this for exploratory queries when you don't know exact codes. For example, search "mumbai" to find port codes, or "hapag" to find Hapag-Lloyd data coverage. Returns matching trade lanes, local charges, and shipping line information. FREE — no payment required. Returns: { trade_lanes: [...], local_charges: [...], lines: [...] } matching the keyword. Related tools: Use shippingrates_port for structured port lookup by UN/LOCODE, shippingrates_lines for full carrier listing.

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• baselight_sdk_query_execute

  baselight

  Execute a SQL query on Baselight and wait for results (up to 1 minute). The query executes and returns the first 100 rows upon completion, or info about a pending query that needs more time. Use DuckDB syntax only, table format "@username.dataset.table" (double-quoted), SELECT queries only (no DDL/DML), no semicolon terminators, use LIMIT not TOP. If query is still PENDING, use `sdk-get-results` to continue polling. If totalResults > returned rows, use `sdk-get-results` with offset to paginate.

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• get_query_patterns

  Shibui Finance

  REQUIRED before stock_data_query, 23 SQL patterns prevent timeouts/wrong results Must be called once per session immediately after get_database_schema. Contains query patterns for time-series selection, return calculations, screening joins, window functions, backtesting, and performance optimization. Time-series queries will timeout or return wrong results without these patterns. After this tool returns, call stock_data_query to execute SQL.

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• get_query_patterns

  Shibui Finance

  REQUIRED before stock_data_query, 23 SQL patterns prevent timeouts/wrong results Must be called once per session immediately after get_database_schema. Contains query patterns for time-series selection, return calculations, screening joins, window functions, backtesting, and performance optimization. Time-series queries will timeout or return wrong results without these patterns. After this tool returns, call stock_data_query to execute SQL.

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• ask-about-project-data

  cupix-compass

  Query the construction project database using natural language (Text-to-SQL). Converts natural language into SQL to retrieve captures, annotations, progress metrics, schedules, and other project records. Pass the user's question as-is without modification. For trade visibility, use `analyze-progress-and-forecasts` instead. **WORKFLOW:** - **Default**: call this tool with only `query`. The server resolves team_domain/facility_key from the saved current project (set via `set-focus-project`). Do NOT call `list-my-projects` again just to obtain these values. - Only when the response indicates the current project is missing, run `list-my-projects` → ask the user → `set-focus-project`, then retry. - Pass explicit team_domain/facility_key **only** when the user clearly wants to query a different project than the saved one. **Available tables:** - progresses: SI progress metrics (level, category, phase, workarea, cost, dates) - captures: Camera captures metadata (level, camera_model, capture_state, user_email) - records: Capture events with timestamps (captured_at, state, id) - photo_notes: Photonotes (description, state, user_email, created_at) - voice_notes: Voicenotes (level, description, state, user_email, created_at) - facilities: Site info (name, address, size, location, bim_count, created_at) - users: User profiles (name, email) - workareas: Spatial zones (level, name, user_name) Args: query: Natural language question (pass as-is, no SQL syntax) team_domain: Omit by default. Pass only to override the current project. facility_key: Omit by default. Pass only to override the current project. Returns: Query results as tab-separated text

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• shippingrates_search

  freightgate-mcp-server

  Search the ShippingRates database by keyword — matches against carrier names, port names, country names, and charge types. Use this for exploratory queries when you don't know exact codes. For example, search "mumbai" to find port codes, or "hapag" to find Hapag-Lloyd data coverage. Returns matching trade lanes, local charges, and shipping line information. FREE — no payment required. Returns: { trade_lanes: [...], local_charges: [...], lines: [...] } matching the keyword. Related tools: Use shippingrates_port for structured port lookup by UN/LOCODE, shippingrates_lines for full carrier listing.

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• execute_sql_readonly

  mcp

  Execute any valid read only SQL statement on a Cloud SQL instance. To support the `execute_sql_readonly` tool, a Cloud SQL instance must meet the following requirements: * The value of `data_api_access` must be set to `ALLOW_DATA_API`. * For a MySQL instance, the database flag `cloudsql_iam_authentication` must be set to `on`. For a PostgreSQL instance, the database flag `cloudsql.iam_authentication` must be set to `on`. * An IAM user account or IAM service account (`CLOUD_IAM_USER` or `CLOUD_IAM_SERVICE_ACCOUNT`) is required to call the `execute_sql_readonly` tool. The tool executes the SQL statements using the privileges of the database user logged with IAM database authentication. After you use the `create_instance` tool to create an instance, you can use the `create_user` tool to create an IAM user account for the user currently logged in to the project. The `execute_sql_readonly` tool has the following limitations: * If a SQL statement returns a response larger than 10 MB, then the response will be truncated. * The tool has a default timeout of 30 seconds. If a query runs longer than 30 seconds, then the tool returns a `DEADLINE_EXCEEDED` error. * The tool isn't supported for SQL Server. If you receive errors similar to "IAM authentication is not enabled for the instance", then you can use the `get_instance` tool to check the value of the IAM database authentication flag for the instance. If you receive errors like "The instance doesn't allow using executeSql to access this instance", then you can use `get_instance` tool to check the `data_api_access` setting. When you receive authentication errors: 1. Check if the currently logged-in user account exists as an IAM user on the instance using the `list_users` tool. 2. If the IAM user account doesn't exist, then use the `create_user` tool to create the IAM user account for the logged-in user. 3. If the currently logged in user doesn't have the proper database user roles, then you can use `update_user` tool to grant database roles to the user. For example, `cloudsqlsuperuser` role can provide an IAM user with many required permissions. 4. Check if the currently logged in user has the correct IAM permissions assigned for the project. You can use `gcloud projects get-iam-policy [PROJECT_ID]` command to check if the user has the proper IAM roles or permissions assigned for the project. * The user must have `cloudsql.instance.login` permission to do automatic IAM database authentication. * The user must have `cloudsql.instances.executeSql` permission to execute SQL statements using the `execute_sql_readonly` tool or `executeSql` API. * Common IAM roles that contain the required permissions: Cloud SQL Instance User (`roles/cloudsql.instanceUser`) or Cloud SQL Admin (`roles/cloudsql.admin`) When receiving an `ExecuteSqlResponse`, always check the `message` and `status` fields within the response body. A successful HTTP status code doesn't guarantee full success of all SQL statements. The `message` and `status` fields will indicate if there were any partial errors or warnings during SQL statement execution.

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• init_app

  mcp

  Create a new backend app with isolated database and API endpoints. Returns: app_id, api_url, url (frontend URL), and provisioning status. Example: Input: { name: "my-blog" } Output: { app_id: "app_abc123", api_url: "https://api.butterbase.dev/v1/app_abc123", url: "https://my-blog.butterbase.dev", _meta: { next_actions: [...] } } URL guide: - api_url: Your API endpoint for database queries, auth, and functions (e.g. https://api.butterbase.dev/v1/app_abc123) - url: Your frontend URL where your deployed site is served (e.g. https://my-blog.butterbase.dev) - These are different! The api_url is for backend requests, the url is where users visit your app. Next steps: Use manage_schema (action: "apply") to define tables, then manage_oauth (action: "configure") for auth. Common errors: - Name already exists: Choose a different name or use manage_app (action: "list") to find existing app - Invalid characters: Use only lowercase letters, numbers, hyphens, underscores - Name too long: Maximum 63 characters The response includes _meta.next_actions with recommended next steps.

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• sixta_health_check

  sixta-connect

  Triage of diagnostics the user runs themselves. Paste any of: pg_stat_user_tables (vacuum/bloat triage, graded A–F with ready-to-run fixes), pg_settings / SHOW GLOBAL VARIABLES / conf files (configuration review against DBRE sizing rules — pass ram_gb, cpu_cores, workload), SHOW ENGINE INNODB STATUS (deadlock analysis, purge lag, buffer-pool misses, long-running transactions), or a pg_stat_statements excerpt (workload triage: dominant queries, N+1 signatures, slow-per-call outliers). Use when the user asks 'is my database healthy', mentions bloat/autovacuum/wraparound/deadlocks, or wants their config or workload reviewed. Called with nothing parseable, it returns the exact queries to run. Input is analyzed in memory and never stored.

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• stock_data_query

  Shibui Finance

  Stock prices, earnings, revenue, P/E, dividends, filings, screener, comparisons Run a SQL query against 64 years of US stock market data. REQUIRES calling get_database_schema then get_query_patterns first (in that order). This tool has no schema or query patterns built in. Call get_database_schema once, then get_query_patterns once, then use this tool. Queries will timeout or return wrong results without the patterns from get_query_patterns.

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• shippingrates_search

  FreightGate MCP Server

  Search the ShippingRates database by keyword — matches against carrier names, port names, country names, and charge types. Use this for exploratory queries when you don't know exact codes. For example, search "mumbai" to find port codes, or "hapag" to find Hapag-Lloyd data coverage. Returns matching trade lanes, local charges, and shipping line information. FREE — no payment required. Returns: { trade_lanes: [...], local_charges: [...], lines: [...] } matching the keyword. Related tools: Use shippingrates_port for structured port lookup by UN/LOCODE, shippingrates_lines for full carrier listing.

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• get_database_schema

  Shibui Finance

  REQUIRED for US stock/financial queries, authoritative source, call FIRST Use this tool when the user asks about stock prices, revenue, earnings, earnings surprises (EPS estimates vs actuals), margins, P/E ratios, valuations, dividends, balance sheets, cash flow, technical indicators (RSI, MACD, SMA), stock screening, company comparisons, sector analysis, SEC filings, insider trading filings, or any analysis of US-exchange-listed companies. Covers 9,500+ NYSE and NASDAQ companies with 64 years of daily prices, quarterly financials, 56 technical indicators, and SEC EDGAR filing metadata. Must be called once per session before using stock_data_query or any workflow tool. After this tool returns, call get_query_patterns before writing any SQL.

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• run_query

  VirtualFlyBrain

  Run a query on VirtualFlyBrain using a VFB ID and query type. Supports batch requests — pass an array of IDs to run the same query_type on all of them, or use the queries array for mixed ID/query_type combinations. When multiple queries are provided, results are returned as a JSON object keyed by "ID::query_type". IMPORTANT: Do NOT pass tool names (like "get_term_info" or "search_terms") as query_type — those are separate tools. Valid query_types are returned by get_term_info in the Queries array for each entity. Common query_types include: PaintedDomains, AllAlignedImages, AlignedDatasets, AllDatasets (for templates); SimilarMorphologyTo, NeuronInputsTo, NeuronNeuronConnectivityQuery (for neurons); ListAllAvailableImages, SubclassesOf, PartsOf, NeuronsPartHere, NeuronsSynaptic, ExpressionOverlapsHere (for classes). Available query_types vary by entity type — ALWAYS call get_term_info FIRST to see which queries are available for a given ID, as attempting invalid query types will result in an error message directing you to use get_term_info.

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• execute_sql_readonly

  Google Big Query

  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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• get_database_info

  BorealHost

  Get WordPress database information (size, tables, row counts). Requires: API key with read scope. WordPress sites only. Args: slug: Site identifier Returns: {"database": "wp_mysite", "size_mb": 45.2, "tables": 12, "total_rows": 15432}

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• execute_query

  BorealHost

  Execute a SQL query on a site's database. Supports SELECT, INSERT, UPDATE, DELETE, and DDL statements. Results are limited to 1000 rows for SELECT queries. Requires: API key with write scope. Args: slug: Site identifier database: Database name query: SQL query string Returns: {"columns": ["id", "title"], "rows": [[1, "Hello"], ...], "affected_rows": 0, "query_time_ms": 12}

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• gazette_insolvency

  UK Due Diligence

  Search The Gazette's insolvency notice index by entity name. Searches the Gazette's insolvency endpoint which covers corporate notice codes: winding-up orders (2443), administration orders (2448), liquidator appointments (2452), striking-off notices (2460), and more. Results are sorted by severity — winding-up orders and administration orders appear first. Each result includes a notice_numeric_id. Read the full legal wording via the notice://{notice_numeric_id} resource. The Gazette is the official UK public record. A notice here means the event has been formally published and is legally effective.

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• execute_sql

  mcp

  Execute any valid SQL statement, including data definition language (DDL), data control language (DCL), data query language (DQL), or data manipulation language (DML) statements, on a Cloud SQL instance. To support the `execute_sql` tool, a Cloud SQL instance must meet the following requirements: * The value of `data_api_access` must be set to `ALLOW_DATA_API`. * For built_in users password_secret_version must be set. * Otherwise, for IAM users, for a MySQL instance, the database flag `cloudsql_iam_authentication` must be set to `on`. For a PostgreSQL instance, the database flag `cloudsql.iam_authentication` must be set to `on`. * After you use the `create_instance` tool to create an instance, you can use the `create_user` tool to create an IAM user account for the user currently logged in to the project. The `execute_sql` tool has the following limitations: * If a SQL statement returns a response larger than 10 MB, then the response will be truncated. * The `execute_sql` tool has a default timeout of 30 seconds. If a query runs longer than 30 seconds, then the tool returns a `DEADLINE_EXCEEDED` error. * The `execute_sql` tool isn't supported for SQL Server. If you receive errors similar to "IAM authentication is not enabled for the instance", then you can use the `get_instance` tool to check the value of the IAM database authentication flag for the instance. If you receive errors like "The instance doesn't allow using executeSql to access this instance", then you can use `get_instance` tool to check the `data_api_access` setting. When you receive authentication errors: 1. Check if the currently logged-in user account exists as an IAM user on the instance using the `list_users` tool. 2. If the IAM user account doesn't exist, then use the `create_user` tool to create the IAM user account for the logged-in user. 3. If the currently logged in user doesn't have the proper database user roles, then you can use `update_user` tool to grant database roles to the user. For example, `cloudsqlsuperuser` role can provide an IAM user with many required permissions. 4. Check if the currently logged in user has the correct IAM permissions assigned for the project. You can use `gcloud projects get-iam-policy [PROJECT_ID]` command to check if the user has the proper IAM roles or permissions assigned for the project. * The user must have `cloudsql.instance.login` permission to do automatic IAM database authentication. * The user must have `cloudsql.instances.executeSql` permission to execute SQL statements using the `execute_sql` tool or `executeSql` API. * Common IAM roles that contain the required permissions: Cloud SQL Instance User (`roles/cloudsql.instanceUser`) or Cloud SQL Admin (`roles/cloudsql.admin`) When receiving an `ExecuteSqlResponse`, always check the `message` and `status` fields within the response body. A successful HTTP status code doesn't guarantee full success of all SQL statements. The `message` and `status` fields will indicate if there were any partial errors or warnings during SQL statement execution.

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• create_user

  mcp

  Create a database user for a Cloud SQL instance. * This tool returns a long-running operation. Use the `get_operation` tool to poll its status until the operation completes. * When you use the `create_user` tool, specify the type of user: `CLOUD_IAM_USER`, `CLOUD_IAM_SERVICE_ACCOUNT`, or `BUILT_IN`. * By default the newly created user is assigned the `cloudsqlsuperuser` role, unless you specify other database roles explicitly in the request. * You can use a newly created user with the `execute_sql` tool if the user is a currently logged in IAM user. The `execute_sql` tool executes the SQL statements using the privileges of the database user logged in using IAM database authentication. The `create_user` tool has the following limitations: * To create a built-in user with password, use the `password_secret_version` field to provide password using the Google Cloud Secret Manager. The value of `password_secret_version` should be the resource name of the secret version, like `projects/12345/locations/us-central1/secrets/my-password-secret/versions/1` or `projects/12345/locations/us-central1/secrets/my-password-secret/versions/latest`. The caller needs to have `secretmanager.secretVersions.access` permission on the secret version. * The `create_user` tool doesn't support creating a user for SQL Server. To create an IAM user in PostgreSQL: * The database username must be the IAM user's email address and all lowercase. For example, to create user for PostgreSQL IAM user `example-user@example.com`, you can use the following request: ``` { "name": "example-user@example.com", "type": "CLOUD_IAM_USER", "instance":"test-instance", "project": "test-project" } ``` The created database username for the IAM user is `example-user@example.com`. To create an IAM service account in PostgreSQL: * The database username must be created without the `.gserviceaccount.com` suffix even though the full email address for the account is`service-account-name@project-id.iam.gserviceaccount.com`. For example, to create an IAM service account for PostgreSQL you can use the following request format: ``` { "name": "test@test-project.iam", "type": "CLOUD_IAM_SERVICE_ACCOUNT", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM service account is `test@test-project.iam`. To create an IAM user or IAM service account in MySQL: * When Cloud SQL for MySQL stores a username, it truncates the @ and the domain name from the user or service account's email address. For example, `example-user@example.com` becomes `example-user`. * For this reason, you can't add two IAM users or service accounts with the same username but different domain names to the same Cloud SQL instance. * For example, to create user for the MySQL IAM user `example-user@example.com`, use the following request: ``` { "name": "example-user@example.com", "type": "CLOUD_IAM_USER", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM user is `example-user`. * For example, to create the MySQL IAM service account `service-account-name@project-id.iam.gserviceaccount.com`, use the following request: ``` { "name": "service-account-name@project-id.iam.gserviceaccount.com", "type": "CLOUD_IAM_SERVICE_ACCOUNT", "instance": "test-instance", "project": "test-project" } ``` The created database username for the IAM service account is `service-account-name`.

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