article

README

MCP Alchemy

Status: Works great and is in daily use without any known bugs.

Status2: I just added the package to PyPI and updated the usage instructions. Please report any issues :)

Let Claude be your database expert! MCP Alchemy connects Claude Desktop directly to your databases, allowing it to:

Help you explore and understand your database structure
Assist in writing and validating SQL queries
Displays relationships between tables
Analyze large datasets and create reports
Claude Desktop Can analyse and create artifacts for very large datasets using claude-local-files.

Works with PostgreSQL, MySQL, MariaDB, SQLite, Oracle, MS SQL Server, CrateDB, Vertica, and a host of other SQLAlchemy-compatible databases.

MCP Alchemy in action

Installation

Ensure you have uv installed:

# Install uv if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | sh

Usage with Claude Desktop

Add to your claude_desktop_config.json. You need to add the appropriate database driver in the --with parameter.

Note: After a new version release there might be a period of up to 600 seconds while the cache clears locally cached causing uv to raise a versioning error. Restarting the MCP client once again solves the error.

SQLite (built into Python)

{
  "mcpServers": {
    "my_sqlite_db": {
      "command": "uvx",
      "args": ["--from", "mcp-alchemy==2025.8.15.91819",
               "--refresh-package", "mcp-alchemy", "mcp-alchemy"],
      "env": {
        "DB_URL": "sqlite:////absolute/path/to/database.db"
      }
    }
  }
}

PostgreSQL

{
  "mcpServers": {
    "my_postgres_db": {
      "command": "uvx",
      "args": ["--from", "mcp-alchemy==2025.8.15.91819", "--with", "psycopg2-binary",
               "--refresh-package", "mcp-alchemy", "mcp-alchemy"],
      "env": {
        "DB_URL": "postgresql://user:password@localhost/dbname"
      }
    }
  }
}

MySQL/MariaDB

{
  "mcpServers": {
    "my_mysql_db": {
      "command": "uvx",
      "args": ["--from", "mcp-alchemy==2025.8.15.91819", "--with", "pymysql",
               "--refresh-package", "mcp-alchemy", "mcp-alchemy"],
      "env": {
        "DB_URL": "mysql+pymysql://user:password@localhost/dbname"
      }
    }
  }
}

Microsoft SQL Server

{
  "mcpServers": {
    "my_mssql_db": {
      "command": "uvx",
      "args": ["--from", "mcp-alchemy==2025.8.15.91819", "--with", "pymssql",
               "--refresh-package", "mcp-alchemy", "mcp-alchemy"],
      "env": {
        "DB_URL": "mssql+pymssql://user:password@localhost/dbname"
      }
    }
  }
}

Oracle

{
  "mcpServers": {
    "my_oracle_db": {
      "command": "uvx",
      "args": ["--from", "mcp-alchemy==2025.8.15.91819", "--with", "oracledb",
               "--refresh-package", "mcp-alchemy", "mcp-alchemy"],
      "env": {
        "DB_URL": "oracle+oracledb://user:password@localhost/dbname"
      }
    }
  }
}

CrateDB

{
  "mcpServers": {
    "my_cratedb": {
      "command": "uvx",
      "args": ["--from", "mcp-alchemy==2025.8.15.91819", "--with", "sqlalchemy-cratedb>=0.42.0.dev1",
               "--refresh-package", "mcp-alchemy", "mcp-alchemy"],
      "env": {
        "DB_URL": "crate://user:password@localhost:4200/?schema=testdrive"
      }
    }
  }
}

For connecting to CrateDB Cloud, use a URL like crate://user:password@example.aks1.westeurope.azure.cratedb.net:4200?ssl=true.

Vertica

{
  "mcpServers": {
    "my_vertica_db": {
      "command": "uvx",
      "args": ["--from", "mcp-alchemy==2025.8.15.91819", "--with", "vertica-python",
               "--refresh-package", "mcp-alchemy", "mcp-alchemy"],
      "env": {
        "DB_URL": "vertica+vertica_python://user:password@localhost:5433/dbname",
        "DB_ENGINE_OPTIONS": "{\"connect_args\": {\"ssl\": false}}"
      }
    }
  }
}

Environment Variables

DB_URL: SQLAlchemy database URL (required)
CLAUDE_LOCAL_FILES_PATH: Directory for full result sets (optional)
EXECUTE_QUERY_MAX_CHARS: Maximum output length (optional, default 4000)
DB_ENGINE_OPTIONS: JSON string containing additional SQLAlchemy engine options (optional)

Connection Pooling

MCP Alchemy uses connection pooling optimized for long-running MCP servers. The default settings are:

pool_pre_ping=True: Tests connections before use to handle database timeouts and network issues
pool_size=1: Maintains 1 persistent connection (MCP servers typically handle one request at a time)
max_overflow=2: Allows up to 2 additional connections for burst capacity
pool_recycle=3600: Refreshes connections older than 1 hour (prevents timeout issues)
isolation_level='AUTOCOMMIT': Ensures each query commits automatically

These defaults work well for most databases, but you can override them via DB_ENGINE_OPTIONS:

{
  "DB_ENGINE_OPTIONS": "{\"pool_size\": 5, \"max_overflow\": 10, \"pool_recycle\": 1800}"
}

For databases with aggressive timeout settings (like MySQL's 8-hour default), the combination of pool_pre_ping and pool_recycle ensures reliable connections.

API

Tools

all_table_names
- Return all table names in the database
- No input required
- Returns comma-separated list of tables
```
users, orders, products, categories
```
filter_table_names
- Find tables matching a substring
- Input: q (string)
- Returns matching table names
```
Input: "user"
Returns: "users, user_roles, user_permissions"
```
schema_definitions
- Get detailed schema for specified tables
- Input: table_names (string[])
- Returns table definitions including:
  - Column names and types
  - Primary keys
  - Foreign key relationships
  - Nullable flags
```
users:
    id: INTEGER, primary key, autoincrement
    email: VARCHAR(255), nullable
    created_at: DATETIME
    
    Relationships:
      id -> orders.user_id
```
execute_query
- Execute SQL query with vertical output format
- Inputs:
  - query (string): SQL query
  - params (object, optional): Query parameters
- Returns results in clean vertical format:
```
1. row
id: 123
name: John Doe
created_at: 2024-03-15T14:30:00
email: NULL

Result: 1 rows
```
- Features:
  - Smart truncation of large results
  - Full result set access via claude-local-files integration
  - Clean NULL value display
  - ISO formatted dates
  - Clear row separation

Claude Local Files

When claude-local-files is configured:

Access complete result sets beyond Claude's context window
Generate detailed reports and visualizations
Perform deep analysis on large datasets
Export results for further processing

The integration automatically activates when CLAUDE_LOCAL_FILES_PATH is set.

Developing

First clone the github repository, install the dependencies and your database driver(s) of choice:

git clone git@github.com:runekaagaard/mcp-alchemy.git
cd mcp-alchemy
uv sync
uv pip install psycopg2-binary

Then set this in claude_desktop_config.json:

...
"command": "uv",
"args": ["run", "--directory", "/path/to/mcp-alchemy", "-m", "mcp_alchemy.server", "main"],
...

My Other LLM Projects

MCP Redmine - Let Claude Desktop manage your Redmine projects and issues.
MCP Notmuch Sendmail - Email assistant for Claude Desktop using notmuch.
Diffpilot - Multi-column git diff viewer with file grouping and tagging.
Claude Local Files - Access local files in Claude Desktop artifacts.

MCP Directory Listings

MCP Alchemy is listed in the following MCP directory sites and repositories:

Contributing

Contributions are warmly welcomed! Whether it's bug reports, feature requests, documentation improvements, or code contributions - all input is valuable. Feel free to:

Open an issue to report bugs or suggest features
Submit pull requests with improvements
Enhance documentation or share your usage examples
Ask questions and share your experiences

The goal is to make database interaction with Claude even better, and your insights and contributions help achieve that.

License

Mozilla Public License Version 2.0

mcp-alchemy