dbmcp

Name: dbmcp Review
Item: dbmcp
Rating: 2.9
Author: Aaron Matthews

Connector Data & Analytics Usable

Works inClaude Code Claude Cowork Claude Chat

Usable Scanned — metadata only

Enables safe, controlled database access for AI agents without exposing sensitive data or risking accidental writes.

Database MCP server for MySQL, MariaDB, PostgreSQL, and SQLite - with builtin PII redaction and write-prevention

Ask Claude to query your database and summarize customer trends without exposing sensitive personal data
Generate SQL reports from PostgreSQL or MySQL while Claude automatically masks email addresses and phone numbers
Analyze production data safely by letting Claude read databases in read-only mode to prevent accidental modifications

29 starsMIT (commercial OK)Free

Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Why it matters

Enables safe, controlled database access for AI agents without exposing sensitive data or risking accidental writes. Built-in PII redaction and write-prevention reduce compliance risk and operational overhead.

Best for

Data analytics teams and consultants needing secure database integration with Claude while protecting customer data.

Works in

Claude Code Claude Cowork Claude Chat

Source

https://github.com/haymon-ai/dbmcp

By haymon-ai

How to Get It

Option 1: Claude Desktop AppOpen the Customize panel in the sidebar → browse connectors → search and add. Works in Claude Code, Claude Cowork, and Claude Chat.

Option 2: Paste into Claude CodeCopy the command below and paste it into a Claude Code conversation. Claude will run it for you.

Command

claude mcp add dbmcp -- npx -y dbmcp

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.

First thing to try

Once it’s connected, paste this into Claude:

Query my database and summarize customer trends without exposing sensitive personal data

CostFree

Trust Signals Auto-scanned

Stars29Contributors2Last updated2026-07-01LicenseMIT (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-07-25 · scanner v1

Data & Access

Data processingPrompts sent to Anthropic API. Enterprise/Team plans exclude training.

Community Pulse New

No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 29 GitHub stars; 2 contributors; last commit 24d ago; license MIT.

Things to check

Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation Scores

Evaluation

Ease of Use

3/5

Versatility

2/5

Reliability

3/5

Security

4/5

Overall score2.90 / 5.00 UsableEvaluatedJul 2026

Scored from trust signals (evidence-eval-v1): 29 GitHub stars; 2 contributors; last commit 24d ago; license MIT.

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