dbhub and db-mcp-server

These are competitors offering overlapping functionality—both provide MCP servers for database access to AI assistants—though the first has substantially more adoption and production maturity based on its stars and downloads, while the second appears less maintained and undistributed.

dbhub
80
Verified
db-mcp-server
50
Established
Maintenance 23/25
Adoption 20/25
Maturity 18/25
Community 19/25
Maintenance 10/25
Adoption 10/25
Maturity 9/25
Community 21/25
Stars: 2,287
Forks: 187
Downloads: 71,034
Commits (30d): 32
Language: TypeScript
License: MIT
Stars: 351
Forks: 62
Downloads:
Commits (30d): 0
Language: Go
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 db-mcp-server

FreePeak/db-mcp-server

A powerful multi-database server implementing the Model Context Protocol (MCP) to provide AI assistants with structured access to databases.

Supports MySQL, PostgreSQL, SQLite, and Oracle databases with automatic tool generation for each connection—query execution, transactions, schema exploration, and performance analysis all exposed as distinct MCP tools. Built in Go using Clean Architecture patterns and compatible with OpenAI Agents SDK, it offers flexible deployment via stdio (IDE integration), SSE, or Docker with optional lazy-loading for managing 10+ concurrent database connections.

Scores updated daily from GitHub, PyPI, and npm data. How scores work