Best MCP Servers for PostgreSQL in 2026

The landscape right now

There are over 130 PostgreSQL MCP servers indexed on PulseMCP. Most are forks of forks. A few are worth your time.

This is an honest comparison. DataMCP is one of the options listed here and I built it, so take my opinion with that context. I'll cover what each server actually does, what's missing, and who it's for.

Anthropic's reference server (deprecated)

The official @modelcontextprotocol/server-postgres from Anthropic was the first PostgreSQL MCP server most people tried. It shipped as part of the modelcontextprotocol/servers monorepo.

What it did: Read-only access. List tables, inspect schemas, run SELECT queries. You passed your connection string as a CLI argument and it ran via stdio.

Why it's gone: Archived in July 2025 after Datadog Security Labs found an SQL injection vulnerability. The server wrapped queries in read-only transactions but accepted semicolon-delimited statements. You could break out of the transaction and execute arbitrary SQL, including DROP SCHEMA public CASCADE. Not great.

Status: Deprecated on GitHub, NPM, and Docker Hub. Don't use it.

The takeaway isn't that MCP is insecure. It's that passing a raw connection string through a stdio process with no query validation is a bad architecture for database access. Every server below handles this differently.

Postgres MCP Pro (CrystalDBA)

GitHub: crystaldba/postgres-mcp. MIT license. ~2,400 stars.

What it does: Read/write access with configurable permissions. Performance analysis: identifies slow queries, recommends indexes, checks buffer cache hit rates, validates constraints, monitors vacuum health. Think of it as a database advisor that also happens to speak MCP.

Good for: Solo developers who want their AI to help optimize query performance alongside writing SQL. The index tuning recommendations are genuinely useful if you're running into slow queries and don't want to dig through pg_stat_statements yourself.

What's missing: No team features. No audit trail. No per-table permission control. You configure it with a connection string in your MCP config, which means every developer on the team needs the raw credentials. Fine for local dev, not for teams shipping to staging or production.

Setup:

{
  "mcpServers": {
    "postgres-pro": {
      "command": "npx",
      "args": ["-y", "@crystaldba/postgres-mcp", "postgresql://user:pass@host:5432/db"]
    }
  }
}

pgEdge MCP Server

From pgEdge, the distributed PostgreSQL company. Works with any PostgreSQL 14+, not just pgEdge clusters.

What it does: Schema inspection, query execution, and database management through MCP. Supports both stdio and SSE transports. Designed to work with Claude Code, Claude Desktop, Cursor, and other MCP-compatible tools.

Good for: Teams already using pgEdge for distributed Postgres, or anyone who wants a server from a PostgreSQL infrastructure company (vs. a community side project).

What's missing: No built-in permission layer. No audit logging. No multi-tool support with different access scopes. You're trusting the AI with whatever your connection string allows.

DBHub

GitHub: bytebase/dbhub. Multi-database MCP server from Bytebase.

What it does: One server for PostgreSQL, MySQL, SQL Server, MariaDB, and SQLite. Zero npm dependencies. Schema inspection, query execution, table listing. DSN-based configuration.

Good for: Teams with multiple database engines who want a single MCP server instead of configuring one per database type. If you have a PostgreSQL app database and a MySQL legacy system, DBHub covers both.

What's missing: Jack of all trades. PostgreSQL-specific features (advisory locks, JSONB operations, custom types) aren't exposed. No query validation, no permission control, no audit trail.

Setup:

{
  "mcpServers": {
    "dbhub": {
      "command": "npx",
      "args": ["-y", "dbhub", "--dsn", "postgresql://user:pass@host:5432/db"]
    }
  }
}

Nile MCP Server

From Nile, the multi-tenant PostgreSQL platform.

What it does: Database management, tenant management, user auth, credential management, and SQL queries through MCP. Designed for SaaS applications where tenant isolation matters.

Good for: Teams building multi-tenant B2B apps on Nile specifically. The MCP server understands Nile's tenant virtualization, so your AI can work within tenant contexts.

What's missing: Nile-specific. If you're running standard PostgreSQL (or Supabase, Neon, RDS), this doesn't apply.

Supabase MCP Server

Official from Supabase.

What it does: Database queries via PostgREST, storage bucket management, user authentication operations, and realtime subscriptions. It's Supabase-as-MCP, not just PostgreSQL-as-MCP.

Good for: Supabase users who want their AI to manage the full Supabase stack, not just the database.

What's missing: Only works with Supabase. If your PostgreSQL is on RDS, Neon, or self-hosted, this isn't relevant. No per-table permission control beyond what Supabase row-level security provides.

DataMCP

Full disclosure: I built this. Bias acknowledged.

What it does: Managed MCP gateway for PostgreSQL. You register a connection, DataMCP encrypts it (AES-256-GCM), extracts your schema, generates AI descriptions for tables and columns, and gives you an MCP URL.

Six MCP tools: query (with configurable read/write/DDL), get_schema (full schema with AI descriptions), get_table_details, get_permissions (AI can self-check before attempting a query), get_schema_changes, resync_schema.

Permission system: Every MCP link has its own scope. Presets: read-only, read-write, full access, or custom per-table. Queries are parsed and validated before execution. If Cursor tries to DELETE from a table the link doesn't allow, the query gets blocked and Cursor gets told why.

Team features: Organizations with Owner/Admin/Member roles. Each team member can have their own MCP link with different permissions. Invite by email, revoke in one click. No shared credentials.

Audit trail: Every query logged with execution time, row count, which MCP link, and whether it was allowed or blocked. 7 days on free, 30 on Pro, 365 on Enterprise.

What's missing: PostgreSQL only (for now). No query performance advisor like CrystalDBA. No multi-database support like DBHub.

Setup:

{
  "mcpServers": {
    "my-db": {
      "url": "https://api.datamcp.app/api/mcp/CONNECTION_ID",
      "headers": {
        "Authorization": "Bearer sk_live_YOUR_API_KEY"
      }
    }
  }
}

Pricing: Free (1 connection, 1 MCP link, 2 members), Pro $19/mo (3 connections, 5 links, custom permissions), Enterprise $49/mo (15 connections, 50 links, 365-day logs).

Quick comparison

| | Permissions | Audit | Teams | Setup | Multi-DB | Price | |---|---|---|---|---|---|---| | Anthropic (deprecated) | None | None | No | stdio | No | Free | | CrystalDBA | Configurable r/w | None | No | stdio | No | Free | | pgEdge | None | None | No | stdio/SSE | No | Free | | DBHub | None | None | No | stdio | Yes | Free | | Nile | Tenant-scoped | None | Nile tenants | stdio/SSE | No | Free | | Supabase | RLS | None | Supabase teams | stdio | No | Free | | DataMCP | Per-table, per-link | Full query log | Orgs + roles | HTTP URL | No | Free / $19 / $49 |

How to choose

You're a solo dev on a personal project: CrystalDBA or DBHub. Free, no account needed, run locally. CrystalDBA if you want performance insights, DBHub if you have multiple database engines.

You're on Supabase or Nile: Use their native MCP servers. They understand your platform's specific features (RLS, tenants) better than generic options.

You have a team, or you care about what AI does with your database: That's where the server-only approach breaks down. With stdio servers, every developer has the raw connection string in their config file. There's no audit trail. There's no way to give the intern read-only and the tech lead read-write. That's the problem DataMCP solves.

You want connection strings out of config files: Only a gateway approach (DataMCP, or building your own reverse proxy) keeps credentials off developer machines entirely. The MCP client gets a URL and a scoped API key, never the database credentials.

The right choice depends on where you are. If you're prototyping alone, a free stdio server is fine. Once there's a team involved, or the database has real data in it, you'll want something between the AI and the database that isn't just "hope it doesn't do anything bad."