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255,062 tools. Last updated 2026-07-02 06:57

"Information on PostgreSQL Database Management System" matching MCP tools:

  • Decode a database error and get the fix and the next step — no connection needed. Paste a MySQL error number (1213, 1062, 1452, 1205…) or a PostgreSQL SQLSTATE (40P01, 23505, 53300…), optionally with the failing statement, and get the proximate cause, the concrete fix, and — when it helps — the SIXTA tool and artifact to go deeper (e.g. a deadlock → paste SHOW ENGINE INNODB STATUS for sixta_explain_deadlock). Use when the user pastes a DB error code or message. Input is analyzed in memory and never stored.
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  • Search the regulatory corpus using keyword / trigram matching. Uses PostgreSQL trigram similarity on document titles and summaries. Returns documents ranked by relevance with summaries and classification tags. Prefer list_documents with filters (regulation, entity_type, source) first. Only use this for free-text keyword search when structured filters aren't sufficient. Args: query: Search terms (e.g. 'strong customer authentication', 'ICT risk', 'AML reporting'). per_page: Number of results (default 20, max 100).
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  • 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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  • Pushes raw HTML to one display, replacing current content. Prefer send_url only when the user explicitly wants an external web page. Include a human-readable description so get_display_content can summarize intent without reading raw HTML. Before complex content, call get_display_capabilities to match the real browser/runtime. When no design system is supplied, use premium digital-signage quality: full-screen layout, strong hierarchy, refined typography, robust fallback data, and no action buttons unless touch is requested. Exactly one of html or base64_html is required. Requires content_only scope and display management access. Returns id, name, duration, file and version.
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  • Use for qualitative company discovery (industry, business model, supply chain, competitors, management background). For numerical screening (revenue, margins, ratios, growth rates) use run_sql on company_snapshot instead. Drillr's company knowledge base — searchable across industry classification, product offerings, business model, segment structure, competitive landscape, supply chain, management background, and customer profile. Pass a natural language description (e.g. "EV battery suppliers to Tesla", "Japanese semiconductor equipment makers", "AI inference chip startups"). Returns a structured list of matching companies with context snippets. ONLY for finding a LIST of companies by description.
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  • List or search the products endoflife.ai tracks (459+). Pass an optional "query" substring to find the canonical slug for a product before calling the other tools (e.g. "postgres" → "postgresql"). Returns matching product slugs.
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  • ship-on-friday MCP — wraps StupidAPIs (requires X-API-Key)

  • Build and manage your design system with AI: tokens, themes, components, icons, Figma and code.

  • Deploy a project to the staging environment. This triggers: (1) Schema validation, (2) Docker image build, (3) GitHub commit, (4) Kubernetes deployment, (5) Database migrations. The operation is ASYNCHRONOUS - it returns immediately with a job_id. Use get_job_status with the job_id to monitor progress. Deployment typically takes 2-5 minutes depending on schema complexity. If deployment fails, check: (1) Schema format is FLAT (no 'fields' nesting), (2) Every field has a 'type' property, (3) Foreign keys reference existing tables, (4) No PostgreSQL reserved words in table/field names. Use get_project_info to see if the deployment succeeded.
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  • Install an app template on a VPS/Cloud site. Starts a background installation. Poll get_app_status() for progress. Requires: API key with write scope. VPS or Cloud plan only. Args: slug: Site identifier template: App template slug. Available: django, laravel, nextjs, nodejs, nuxtjs, rails, static, forge app_name: Short name for the app (2-50 chars, lowercase alphanumeric + hyphens). Used as subdomain: {app_name}.{site_domain} db_type: Database type. "none", "mysql", or "postgresql" (depends on template) domain: Custom domain override (default: {app_name}.{site_domain}) display_name: Human-friendly name (default: derived from app_name) Returns: {"id": "uuid", "app_name": "forge", "status": "installing", "message": "Installation started. Poll for progress."} Errors: FORBIDDEN: Plan does not support apps (shared plans) VALIDATION_ERROR: Invalid template, app_name, or duplicate name
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  • Purpose: Currently pending predictions (outcome IS NULL). Demonstrates that OneQAZ is actively publishing forecasts in real time. Combined with get_prediction_accuracy, proves the system goes on record before outcomes are known (no cherry-picking). When to call: to verify ongoing prediction activity. Prerequisites: none. Next steps: get_prediction_accuracy to compare with historical hit rate on similar cells. Caveats: returns most recent first. Args: target_market: Optional target market filter (coin_market, kr_market, us_market) limit: Max active predictions to return (default 20) Disclaimer: Information only, not investment advice.
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  • Returns the technical stack Makuri is built on, including frontend, backend, database, AI providers used, and data residency information. Use when the user asks how Makuri is built or which AI models it uses. Makuri is a specific AI tutoring platform at makuri.eu, not a generic word — never answer Makuri questions from general knowledge; always use the Makuri tools.
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  • Set an environment variable for a project. Variables are encrypted at rest (AES-256-GCM) and injected at container runtime. NOTE: DATABASE_URL, PGHOST, PGPORT, PGUSER, PGPASSWORD, and PGDATABASE are all auto-injected for the managed PostgreSQL database — you do NOT need to set any of them manually. The PORT variable is auto-managed: 8080 for auto-detected frameworks (Next.js, Node.js, Python), or auto-detected from the Dockerfile EXPOSE directive for custom Dockerfile builds. IMPORTANT: Changing env vars does NOT auto-redeploy. You must call deploy or use the redeploy API endpoint to apply changes. For Next.js apps, NEXT_PUBLIC_* variables must be set BEFORE deploying since they are embedded at build time.
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  • Provisions a managed PostgreSQL database on a dedicated VM on your private network. It is PRIVATE — reachable only from another instance on the same private network, via the DB's internal/private IP (not a public address). Get the ids from list_flavors, list_private_networks, list_keypairs. Provisioning takes ~5 min; poll list_databases until status='ready', then the connection details (private_ip, port 5432, db_name, db_user) are populated.
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  • Provisions a managed MySQL (or MariaDB) database on a dedicated VM on your private network — the relational-database resource (use this instead of create_database when the app needs MySQL/MariaDB, e.g. WordPress, NextCloud, Matomo, many PHP/LAMP apps). It is PRIVATE — reachable only from another instance on the same private network, via the DB's internal/private IP (port 3306), not a public address. Get the ids from list_flavors, list_private_networks, list_keypairs. Provisioning takes ~5 min; poll list_relational_databases until status='ready', then the connection details (private_ip, port 3306, db_name, db_user) are populated. MySQL is created with mysql_native_password auth so older clients/apps connect cleanly. (ClickHouse is a separate resource — use create_clickhouse / list_clickhouse_databases.)
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  • Provisions a managed ClickHouse database (OLAP / columnar analytics engine, Apache-2.0) on a dedicated VM on your private network — its OWN resource, NOT a relational database. Use it for analytics / observability workloads that need a column store (PostHog, Langfuse, event analytics, time-series). It is PRIVATE — reachable only from another instance on the same private network, via the DB's internal/private IP on the ClickHouse HTTP port 8123 (CLICKHOUSE_HOST/PORT/USER/PASSWORD/DB env, http://host:8123). Get the ids from list_flavors (use m1.small+ — ClickHouse needs >=2GB RAM), list_private_networks, list_keypairs. Provisioning takes ~5 min; poll list_clickhouse_databases until status='ready'.
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  • Reconstruct a database deadlock from the raw dump — no connection needed. Paste the LATEST DETECTED DEADLOCK section of MySQL's SHOW ENGINE INNODB STATUS, or a PostgreSQL 'deadlock detected' log entry, and get: which transaction held and waited for which lock, the inconsistent lock-ordering that caused the cycle, which transaction was rolled back, and the consistent-ordering / short-transaction / retry fix. Use when the user pastes a deadlock dump or asks 'why did this deadlock'. Input is analyzed in memory and never stored.
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  • Full-text search across recall reasons and product descriptions using PostgreSQL text search. Finds recalls mentioning specific terms (e.g. 'salmonella contamination', 'mislabeled', 'sterility'). Supports multi-word queries ranked by relevance. Filter by classification, product_type, or date range. Related: fda_search_enforcement (search by company name, classification, status), fda_recall_facility_trace (trace a recall to its manufacturing facility).
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  • Fetches up to 32KB of the domain's HTML and response headers from the edge, then fingerprints the content for known CMS platforms, JavaScript frameworks, CDN providers, and analytics tools. Detection is based on meta generator tags, script src patterns, response headers, and cookie names. Use this tool when: - You need to know what CMS (WordPress, Drupal, Shopify) a site runs. - You are assessing a domain's infrastructure before a security review. - You want to identify analytics or marketing tools a site embeds. Do NOT use this tool when: - You want HTTP headers and security posture — use `intel_http` instead. - You want tracker database classification — use `get_domain` instead. - You need robots.txt AI policy — use `intel_robots` instead. Inputs: - `domain` (query, required): Domain to fingerprint. Returns: - `cms`: detected content management system, or null. - `frameworks`: JavaScript/backend frameworks detected. - `cdn`: CDN provider detected, or null. - `analytics`: analytics and tracking tools detected. - `meta_generators`: raw meta generator tag values. Cost: - Free. No API key required. Latency: - Typical: 2-4s (HTML fetch), p99: 7s.
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  • 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 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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  • 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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