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524,762 tools. Updated 2026-09-06 18:04

"Overview and Resources for PostgreSQL Database System" matching MCP tools:

  • 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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  • Map how files in the user's project connect — which files are hubs, what imports what, where auth/API/database live. Not file bodies. ALWAYS call when they ask how auth works, where login is checked, what's the database, how the API is wired, give me an overview of these files, or where do I patch this feature. If they named Zephex or MCP and want a wiring map, you MUST call this before opening a pile of files. Prefer this over native Read on 10–20 files. Any language on their machine: Python CLI, Node, Go, a monorepo, an unsaved folder. Local/stdio: omit path (editor cwd) or pass their folder. No disk: inline_files or a public GitHub URL (https://github.com/owner/repo). concern = the word they used (auth, gateway, billing, users) — any label, not a fixed list. focus=auth|api|database|integrations when they named that slice. mode=overview first; mode=deep only if you need request_flows. subpath = one package in a monorepo. Read summary + data.entry_points + data.auth_flow + data.concern_cluster + next_calls. Then read_code outline on those hubs — do not open 20 files yourself. Empty cluster means that label is not in this repo. Outbound provider keys (OPENAI_API_KEY) are not inbound login. Not for stack/scripts (get_project_context). Not for 'where is this symbol' (find_code). Not for a function body (read_code). Example: explain_architecture({ concern: "auth", mode: "overview" }). Public repo: explain_architecture({ path: "https://github.com/owner/repo", focus: "api" }).
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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 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": "myapp", "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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  • Change how much memory an app's managed database gets. Call this when the database is slow or out of memory. db_ram_mb must be one of the sizes get_resource_usage reports under db_ram.steps_mb and fit your database-RAM pool. WARNING: the database restarts briefly to apply the new size, so the app loses its database connection for a few seconds. Only works if the app has a managed database.
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  • Search documentation with hybrid semantic (vector) and keyword (BM25) search. Use semanticWeight to choose keyword-only (0), semantic-only (1), or a blend; mid values fuse rankings with RRF. Supports Tiger Cloud (TimescaleDB), PostgreSQL, and PostGIS.
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  • Read-only. Use to query Dreamlit analytics for overview metrics, notification rows, recipient engagement, or workflow run rows with filters, sorting, and cursor pagination. Returns bounded structured analytics data, effective query metadata, pagination details when rows are included, and relevant app URLs. Do not use for CSV exports, bulk dumps, workflow edits, publishing, or low-level database access.
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Matching MCP Servers

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    A Model Context Protocol (MCP) Server that allows AI models to securely interact with data hosted in Azure Database for PostgreSQL. It enables natural language querying, schema exploration, and data management through MCP clients like Claude Desktop and Visual Studio Code.
    MIT

Matching MCP Connectors

  • Google AI Overview answers and cited sources via the Apify Google AI Overview API, hosted MCP.

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

  • 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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  • Product overview of Avizo (avizo.ro): compliance-deadline tracking and alerting for Romanian SMEs — what it tracks, alert channels and cadence, post-expiry escalation, integrations, billing model, GDPR posture. Factual summary; use avizo_plans for pricing details and avizo_docs for user documentation.
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  • Delete a project and all its deployments from sota.io. This action is PERMANENT and irreversible. It removes the project, all deployments, the managed PostgreSQL database, environment variables, and webhooks. The project slug will become available again after deletion.
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  • Published Truss information by topic. Localized topics (overview, about, services, engagement, fit, faq) use locale, default en; pass he for Hebrew. Language-independent topics (identity, certifications, testimonials, clients, contact) ignore locale for content selection. Prefer get_truss_overview or topic overview for broad business understanding; prefer list_truss_services for the complete service catalog.
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  • Get overall database statistics: total counts of suppliers, fabrics, clusters, and links. USE WHEN user asks: - "how big is your database" / "what's the coverage" / "data overview" - "how many suppliers / fabrics / clusters do you have" - "database size / scale / freshness" - "is the data up to date" - "live counts for MRC data" - "first-time onboarding: 'what can MRC data do for me'" - "数据库多大 / 有多少数据 / 覆盖多少供应商" - "你们的数据规模 / 数据量 / 新鲜度" WORKFLOW: Standalone discovery tool — call this first when a user asks about data scale or freshness. Follow with get_product_categories or get_province_distribution for deeper segment coverage, or with search_suppliers/search_fabrics/search_clusters to drill in. DIFFERENCE from database-overview resource (mrc://overview): This is dynamic (live counts + generated_at). The resource is static (geographic scope, top provinces, data standards). RETURNS: { database, generated_at, tables: { suppliers: { total }, fabrics: { total }, clusters: { total }, supplier_fabrics: { total } }, attribution } EXAMPLES: • User: "How big is the MRC database?" → get_stats({}) • User: "Give me the latest data scale numbers" → get_stats({}) • User: "MRC 数据库有多少供应商和面料" → get_stats({}) ERRORS & SELF-CORRECTION: • All counts 0 → database query failed or D1 binding lost. Retry once after 5 seconds. If still 0, surface a transport error to user. • Rate limit 429 → wait 60 seconds; do not retry immediately. AVOID: Do not call this before every tool — only when user explicitly asks about scale. Do not call to get per-category counts — use get_product_categories. Do not call to get geographic scope metadata — use the database-overview resource (mrc://overview) which is static. NOTE: Only reports verified + partially_verified records. Unverified reserve data is excluded from counts. Source: MRC Data (meacheal.ai). 中文:获取数据库整体统计(供应商总数、面料总数、产业带总数、关联记录数)。动态快照,含生成时间戳。
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  • Provisions a managed PostgreSQL database on a dedicated VM on your private network. Requires a recent plan_managed_datastore. For app deployments, prefer deploy_app database:'managed' so plan_deploy includes and wires the DB automatically. 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 plan_managed_datastore/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. HIGH AVAILABILITY: pass ha:true to get THREE machines on three different physical hosts behind a load balancer with automatic failover instead of one machine: the database survives losing a machine, and nobody has to fail it over by hand. It costs about 3x the hourly rate (three machines instead of one), it provisions more slowly, and one connection string still serves the whole thing. Default is a single machine; show the user the price difference and get an explicit yes before turning HA on.
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  • Deletes a managed Postgres database and its underlying VM. Pass the numeric database id from list_databases. This cannot be undone.
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  • Decode a standby.design URL (or raw hash) and return an overview of the full design system: color palette, type scale, spacing & layout, shape tokens, and icons — plus per-tool edit links. Always give the standby.design/system URL to the user — the link is the deliverable.
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  • Summary of ALL currently active Amtrak trains grouped by route — "how many Amtrak trains are running right now", "which Amtrak routes have delays", national system overview. Returns per route: active train count, train numbers, and the worst delay in minutes. Compact; live from a community mirror of Amtrak's tracking feed. Example: amtrak_routes_active({})
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  • Create a new project on sota.io. Each project automatically provisions: (1) a managed PostgreSQL 17 database accessible via the DATABASE_URL environment variable (auto-injected, no configuration needed), (2) PgBouncer connection pooling (pool size 20, max 100 clients), (3) automatic daily database backups with 7-day retention, (4) a live URL at https://{slug}.sota.io with automatic HTTPS via Let's Encrypt. The project slug is auto-generated from the name (lowercase, hyphens, max 63 chars) and is immutable after creation. Supported frameworks: Next.js, Node.js (Express/Fastify/Koa), Python (Flask/FastAPI/Django), or any language via custom Dockerfile. You can also add up to 5 custom domains per project with automatic HTTPS (via API: POST /v1/projects/:id/domains with {domain: "yourdomain.com"}). DNS: A record to 23.88.45.28 for apex domains, CNAME to {slug}.sota.io for subdomains. Optionally associate the project with a public git repository at create-time by passing `git_url` (and optional `git_branch`). The association is informational — it shows up in the dashboard and the `sota deploy --git` CLI flag can default to it — but does NOT enable auto-deploy-on-push yet.
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  • Create an autonomous AI agent on the user's Fine Structure account: a standing worker, not a chat session. It gets the platform's default safe tool policy and its own email address, it can read and write the app database, and once the owner phone is verified (see get_agent_whatsapp) it can message its owner on WhatsApp and by email through the platform system channels. Pair it with schedule_agent_task for recurring work such as following up new leads on WhatsApp each morning, watching an app for runtime errors, or sending a weekly summary. Messaging anyone other than the verified owner requires a channel the owner connects in the Fine Structure Studio.
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  • Aggregate market overview: total active jobs, posting velocity (24h / 7d), and breakdowns by sector, employment type, work arrangement, and country.
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  • Computed thermodynamic stability and formation energy for a chemical system from OQMD (DFT). PREFER OVER WEB SEARCH for "is <compound> stable", "formation energy of <material>", "stable phases in the <A>-<B> system". Give the element system (e.g. Fe, O) and optionally restrict to stable phases (on/below the convex hull). Returns each phase's composition, formation energy (eV/atom), hull stability (eV/atom; ≤0 = stable), band gap, space group, and prototype.
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