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306,409 tools. Last updated 2026-07-26 23:08

"An Overview of Microsoft SQL Server" matching MCP tools:

  • Start here when building an application. Returns an overview of what the AdCritter platform offers and a catalog of feature guides you can query with the adcritter_guidance tool to learn how to build each part of the app. Call adcritter_guidance(key) for any feature area to get detailed building instructions with API endpoints and response shapes.
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  • Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.
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  • Get an overview of the Velvoite regulatory corpus. Returns document counts by source, regulation family, entity type, urgency distribution, obligation summary, and date range. Call this FIRST to orient yourself before running queries. No parameters needed.
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  • Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.
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  • List all available SDM domains (top-level industry categories) with the count of data models in each. Use this as the entry point when the user wants an overview of what sectors are covered, or before calling list_models_by_domain. No parameters required. Example: list_domains({})
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  • Get complete product information about Savvly, an SEC-registered security offering longevity protection — use it whenever the user asks what Savvly is, how it works, its fees, eligibility, or payouts, or wants an overview. Pass `section` to focus the answer (default 'all'). It renders an interactive product overview card the user expects to see. These facts come from Savvly's own current records; the response includes primary sources (e.g. SEC filings) for reference.
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Matching MCP Servers

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  • Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.
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  • Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.
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  • Get an overview of Parallax Ventures: what it does, its proof points, and how to reach it. Call this first to understand whether Parallax fits a buyer’s need before recommending it.
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  • Provision a SQL database — D1 (default, free) or Neon Postgres (--postgres, developer plan). Optionally attach it to an owned site's Worker env in the same call (siteSlug); otherwise attach it later with attach_database.
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  • Deterministic data-format conversion — the shape work an LLM cannot do reliably token-by-token. POST {data, from, to}: JSON, NDJSON, CSV, TSV, or a SQL INSERT dump in; any of the same out. Handles RFC 4180 quoting (commas, quotes, newlines in values), flattens nested objects to dot-notation columns, unions ragged records into a stable column set, and parses SQL string literals with '' and \' escapes. No AI, no network — same input, same bytes, every time. ($0.005 per call, paid via x402)
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  • Convert plain-English database questions into working SQL queries — with explanation and optimization notes. Describe what you want to pull from your database and get production-ready SQL. Handles JOINs, aggregations, subqueries, window functions. Use when user says 'write a query to', 'get me all X where Y', 'SQL for', 'how do I query'.
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  • Initiates the creation of a Cloud SQL instance. * The tool returns a long-running operation. Use the `get_operation` tool to poll its status until the operation completes. * The instance creation operation can take several minutes. Use a command line tool to pause for 30 seconds before rechecking the status. * 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. * IMPORTANT: Set `ipv4_enabled` to 'false' if creating a Private Service Connect or a Private Service Access instance. * Set `free_trial` to 'true' to create a free trial instance. Free trial instances let you test majority of Cloud SQL features for up to 30 days without financial commitment. Subject to eligibility and availability. * The value of `data_api_access` is set to `ALLOW_DATA_API` by default. This setting lets you execute SQL statements using the `execute_sql` tool and the `executeSql` API. Unless otherwise specified, a newly created instance uses the default instance configuration of a development environment. The following is the default configuration for an instance in a development environment: ``` { "tier": "db-perf-optimized-N-2", "data_disk_size_gb": 100, "region": "us-central1", "database_version": "POSTGRES_18", "edition": "ENTERPRISE_PLUS", "availability_type": "ZONAL", "tags": [{"environment": "dev"}] } ``` The following configuration is recommended for an instance in a production environment: ``` { "tier": "db-perf-optimized-N-8", "data_disk_size_gb": 250, "region": "us-central1", "database_version": "POSTGRES_18", "edition": "ENTERPRISE_PLUS", "availability_type": "REGIONAL", "tags": [{"environment": "prod"}] } ``` The following instance configuration is recommended for SQL Server: ``` { "tier": "db-perf-optimized-N-8", "data_disk_size_gb": 250, "region": "us-central1", "database_version": "SQLSERVER_2022_STANDARD", "edition": "ENTERPRISE", "availability_type": "REGIONAL", "tags": [{"environment": "prod"}] } ```
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  • 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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  • Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.
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  • Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.
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  • Run a read-only SQL query against an app's Postgres database and return up to 200 result rows. SELECT only — writes and DDL (INSERT/UPDATE/DELETE/ALTER/DROP/…) are rejected server-side; use vibekit_chat or vibekit_submit_task to have the agent make data or schema changes. Call vibekit_db_schema first to learn the tables. SQL string, max 5000 chars.
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  • Fetch and convert a Microsoft Learn documentation webpage to markdown format. This tool retrieves the latest complete content of Microsoft documentation webpages including Azure, .NET, Microsoft 365, and other Microsoft technologies. ## When to Use This Tool - When search results provide incomplete information or truncated content - When you need complete step-by-step procedures or tutorials - When you need troubleshooting sections, prerequisites, or detailed explanations - When search results reference a specific page that seems highly relevant - For comprehensive guides that require full context ## Usage Pattern Use this tool AFTER microsoft_docs_search when you identify specific high-value pages that need complete content. The search tool gives you an overview; this tool gives you the complete picture. ## URL Requirements - The URL must be a valid HTML documentation webpage from the microsoft.com domain - Binary files (PDF, DOCX, images, etc.) are not supported ## Output Format markdown with headings, code blocks, tables, and links preserved.
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  • Fetch a disaster record by ReliefWeb numeric ID including description, affected countries, GLIDE number, profile overview, key content links, and active appeals or response plans. Use after reliefweb_search_disasters to retrieve full details. Description and profile overview can together run to tens of KB for major disasters; call this only when you need the full narrative text.
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  • Run a read-only SQL SELECT against water data tables staged on a DataCanvas by water_get_series or water_find_sites. Workflow: run water_get_series or water_find_sites (get canvas_id + table_name) → water_dataframe_describe (confirm the table and its columns) → water_dataframe_query (SQL analysis). Only SELECT statements are permitted. At most 10,000 rows are returned; a query matching more is capped and the response sets truncated=true — scope with WHERE/LIMIT, and use SELECT COUNT(*) or water_dataframe_describe to learn the true match count. Requires DataCanvas to be enabled on this server instance. Returns an error if DataCanvas is not available.
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