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runekaagaard/mcp-alchemy

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A MCP (model context protocol) server that gives the LLM access to and knowledge about relational databases like SQLite, Postgresql, MySQL & MariaDB, Oracle, and MS-SQL.

R

MCP

runekaagaard/mcp-alchemy

Added 1 June 2026

Overview

runekaagaard/mcp-alchemy is a Python-based Model Context Protocol (MCP) server that provides LLMs with access to relational databases. It supports SQLite, PostgreSQL, MySQL, MariaDB, Oracle, and MS-SQL, allowing language models to query and interact with database schemas and data.

Best for

Best for
Developers needing to integrate LLMs with existing relational databases in a standardized way

Use cases

  • Query databases using natural language from an MCP-compatible LLM client
  • Expose database schema to AI agents for automated analysis
  • Enable data retrieval and exploration in MCP-driven applications

How to use

Install

uv pip install psycopg2-binary

Tools exposed

  • all_table_names
  • filter_table_names
  • schema_definitions
  • execute_query

Tested with

Claude Desktop

Notes

runekaagaard/mcp-alchemy is a Python-based Model Context Protocol (MCP) server that provides LLMs with access to relational databases. It supports SQLite, PostgreSQL, MySQL, MariaDB, Oracle, and MS-SQL, allowing language models to query and interact with database schemas and data.

405 stars on GitHub. Last updated 2025-08-15. Licensed MPL-2.0.

Use cases

  • Query databases using natural language from an MCP-compatible LLM client
  • Expose database schema to AI agents for automated analysis
  • Enable data retrieval and exploration in MCP-driven applications

Pros

  • Supports a wide range of databases (SQLite, PostgreSQL, MySQL, MariaDB, Oracle, MS-SQL)
  • Built on the MCP standard for interoperability with various LLM clients
  • Written in Python, making it easy to extend or deploy in existing workflows

Cons

  • Requires a compatible MCP client to function
  • May expose sensitive database information if access controls are not properly configured
  • Performance is constrained by database size and query complexity

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Supports a wide range of databases (SQLite, PostgreSQL, MySQL, MariaDB, Oracle, MS-SQL)
  • Built on the MCP standard for interoperability with various LLM clients
  • Written in Python, making it easy to extend or deploy in existing workflows

Cons

  • Requires a compatible MCP client to function
  • May expose sensitive database information if access controls are not properly configured
  • Performance is constrained by database size and query complexity
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