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For AI apps

Embeddings, agents and APIs on one Postgres.

Store embeddings next to your data with pgvector, queue embedding jobs with pgmq, and let coding agents build the backend over MCP.

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pgvector built in

Store and search embeddings with pgvector and HNSW indexes, filtered by RLS.

Background jobs

Queue embedding and model jobs in Postgres and process them from your server, with retries and visibility timeouts.

Agent-ready

Every project has an MCP server so Claude Code or Cursor can design schemas and write migrations.

Realtime streaming

Stream tokens and progress to clients over Realtime Broadcast.

Dedicated compute

Vector search is CPU-hungry. Pro and Business run on dedicated VMs with 8 and 16 GB of RAM.

Your data stays yours

Embeddings live in your own Postgres, exportable at any time.

Availability

All plans. Pro or Business recommended for production vector search.

Questions

Which vector index types are supported?

pgvector's IVFFlat and HNSW indexes are both available.

Can I run models on SupaHost?

SupaHost hosts your backend, not models. Call hosted model APIs from your server, or from Postgres with pg_net.

Related

AI coding agents (MCP)Hand a project to Claude Code, Cursor, Codex or VS Code over MCP.Managed PostgresFull PostgreSQL 17 with every Supabase extension, plus Supabase Studio.RealtimeBroadcast, Presence and Postgres Changes with no per-connection fees.

Put every project on one plan.

Every plan starts with a 7-day free trial.

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