dbhub and MCP-PostgreSQL-Ops

The bytebase/dbhub tool is a multi-database generalist solution, while call518/MCP-PostgreSQL-Ops is a PostgreSQL specialist offering deeper monitoring and maintenance capabilities—making them complements for users who need both broad database access and advanced PostgreSQL-specific diagnostics.

dbhub
80
Verified
MCP-PostgreSQL-Ops
51
Established
Maintenance 23/25
Adoption 20/25
Maturity 18/25
Community 19/25
Maintenance 13/25
Adoption 10/25
Maturity 9/25
Community 19/25
Stars: 2,287
Forks: 187
Downloads: 71,034
Commits (30d): 32
Language: TypeScript
License: MIT
Stars: 140
Forks: 26
Downloads:
Commits (30d): 0
Language: Python
License: MIT
No risk flags
No Package No Dependents

About dbhub

bytebase/dbhub

Zero-dependency, token-efficient database MCP server for Postgres, MySQL, SQL Server, MariaDB, SQLite.

Implements just two core MCP tools—`execute_sql` and `search_objects`—with optional custom parameterized operations defined in TOML config, minimizing token overhead for AI context windows. Supports stdio, HTTP, and SSE transports for integration with Claude Desktop, VS Code, Cursor, and other MCP clients, plus includes a built-in web workbench for direct database interaction. Enforces safety guardrails including read-only mode, row limits, and query timeouts while enabling secure multi-database connections through SSH tunneling and SSL/TLS.

About MCP-PostgreSQL-Ops

call518/MCP-PostgreSQL-Ops

🔍Professional MCP server for PostgreSQL operations & monitoring: 30+ extension-independent tools for performance analysis, table bloat detection, autovacuum monitoring, schema introspection, and database management. Supports PostgreSQL 12-17.

Implements the Model Context Protocol (MCP) standard to integrate with AI assistants and language models, exposing PostgreSQL operations as callable tools through stdio transport. Leverages optional `pg_stat_statements` and `pg_stat_monitor` extensions for enhanced query analytics while maintaining core functionality on base PostgreSQL installations. Built with Python and containerized for Docker deployment, supporting RDS/Aurora environments with read-only permissions suitable for production use.

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