dbgorilla

MCP SERVER + CI BOT

Production context while your agent codes. A CI backstop before it merges.

DBGorilla's MCP server lets your coding agent see your production database while it writes: schema, indexes, query stats, live contention, and how they change. The DBGorilla CI bot sees all of that plus your code, and reviews everything in the pull request that touches the database. The shape and behaviour of your database, never your rows.

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Free forever · No credit card · 30 days of Pro included

cursor · dbgorilla mcpCORRECTED

IN THE EDITOR · AGENT PROPOSED

CREATE INDEX idx_events_created_at ON events (created_at);

MCP SERVER REPLIED

CREATE INDEX CONCURRENTLY idx_events_tenant_created
    ON events (tenant_id, created_at DESC);

Every read of this table filters on tenant_id first. An index on created_at alone scans 41.2M rows and discards 99.7% of them.

pull request · dbgorilla ciAPPROVED

ON THE PULL REQUEST · CI BOT CHECKED

Index matches production access patterns. CONCURRENTLY: no lock on events during the build. Nothing else in this diff touches the database.

✓ Tested on clone·3.8s40ms

Same source of truth at both ends. The thing that said it was fine is the thing that checks it.

What each half actually sees.

The MCP server, while your agent codes

The schema of every table, and how it has drifted since

The queries that actually run, with their production stats

Live sessions, lock contention, infrastructure metrics

EXPLAIN against production, plan only, never executed

Experiments on an ephemeral clone with production statistics

The CI bot, before it merges

Everything the MCP server sees. It is the same server.

Plus the pull request diff, line by line

Plus the rest of your codebase, beyond the diff

DDL and generated SQL are verified on a clone before it comments

The lock a migration takes, at the table's live size

Two commands and a login.

zsh · ~/acme-api
$ brew install dbgorilla/tap/dbgorilla
$ dbgorilla login
signed in
$ dbgorilla doctor
api auth mcp key cursor vs code

Collector runs in your network. Docker, Kubernetes, RDS/Aurora or native Postgres.

What you'll see in the first ten minutes.

01

Your slowest queries, ranked.

Read from your real pg_stat_statements and query plans, not a synthetic benchmark.

02

What changed, and why.

Plan regressions, lock risk on migrations, bloat and stale statistics: each with the cause, in English.

03

The fix, tested on a clone.

Every recommendation is validated against a production-shaped copy before it reaches you.

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Free forever · No credit card · 30 days of Pro included

“I just ran a benchmarked query with the indexes applied and 🤯 157x faster.”
CTO, no-code application platform

What “free forever” means here.

  • 1 cluster, single host
  • EXPLAIN plan analyzer
  • 50 Gorilla Credits a month
  • Schema linter
  • One-shot index suggestions
  • 7-day retention
  • MCP server (Claude Code, Cursor, VS Code)
  • Community support

Every new account also gets 30 days of Pro. When it ends, the free tier keeps working.

Point it at one database and see.

Get started free

Free forever · No credit card · 30 days of Pro included