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Documentation Index

Fetch the complete documentation index at: https://docs.querybear.com/llms.txt

Use this file to discover all available pages before exploring further.

Claude Code is Anthropic’s terminal-based AI coding agent. It speaks MCP natively, so adding QueryBear takes one command — your terminal Claude session can now read your real production database safely.

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Connect

Run this in your terminal: 
claude mcp add --transport http querybear https://mcp.querybear.com/mcp
That’s it. The next time you start claude, it will prompt you to authorize QueryBear via OAuth — opens a browser, you click “Approve”, and it links Claude Code to your QueryBear account.

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Verify

Inside a Claude Code session, ask:
“What QueryBear tools do you have available?”
You should see list_connections, get_schema, and run_query. If you don’t, restart claude and try again.

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Why QueryBear + Claude Code

Claude Code is most useful when it has visibility into the systems you’re working on. For backend work, that almost always includes the database. QueryBear lets Claude Code:
  • Answer “how many rows match X?” without you writing SQL by hand.
  • Generate reports against production data while pair-programming.
  • Verify migrations against real schemas (read-only — it can’t run the migration itself).
  • Debug user-reported issues by looking up the actual row.
…all without giving Claude Code direct database credentials, write access, or visibility into sensitive columns.

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Per-database setup guides

PostgreSQL + Claude Code

Step-by-step Postgres setup, including read-only role SQL.

MySQL + Claude Code

Step-by-step MySQL setup, including read-only user SQL.

SQLite + Claude Code

Local SQLite file setup.

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Tips for using QueryBear in Claude Code

  • Let Claude run get_schema first. It dramatically improves query quality. If you’re debugging, you can also explicitly ask: “call get_schema for the users table first.”
  • Be explicit about which connection. If you have multiple databases connected, name one: “using the production connection, count signups this week.” Saves a list_connections round-trip.
  • Read the audit log. Every query Claude ran is in the QueryBear dashboard under Audit log. Helpful when an answer looks suspicious — you can verify the exact SQL.
  • Block any column you wouldn’t want in Claude’s training data telemetry. Anything Claude sees goes through Anthropic’s API. For PII, set the column blocklist in QueryBear.

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Common workflows

Debugging a user report:
“User id 9182 says they didn’t receive a confirmation email. Check their account status, last login, and any recent email events.”
Claude calls get_schema, finds the relevant tables, joins them, and reports — without you writing the query. Sanity-checking a migration:
“I’m about to add a NOT NULL constraint to users.email_verified_at. How many users currently have NULL there?”
A pre-migration safety check Claude can run in seconds. Generating ad-hoc reports:
“Weekly active users by signup cohort, last 8 weeks, output as a markdown table.”
Claude writes the SQL, runs it, formats the result inline.