Databases MCP Server (Access and SQLite 3)

A simple MCP server to let AI interact with Microsoft Access and SQLite 3 databases. Supports import/export with CSV and Excel files, and store human-readable notes about files.

WARNING: This server has full access to databases, so it can read and modify any data in it. Use with caution to avoid data loss!

Configuration

To use this MCP server with Claude Desktop (or any other MCP host), clone the repo and add the following to your config.json:

{
  "mcpServers": {
    "access-mdb": {
      "command": "uv",
      "args": [
        "run",
        "--with", "fastmcp",
        "--with", "pandas",
        "--with", "sqlalchemy-access",
        "--with", "openpyxl",
        "fastmcp", "run",
        "path/to/repo/server.py"
      ],
    }
  }
}

Dev note: to use with uvx, we need to create a package and publish it to PyPI.

Supported Database Types

• Microsoft Access: .mdb and .accdb files
• SQLite 3: .db, .sqlite, and .sqlite3 files
• In-memory SQLite: When no database path is specified

Available Tools

Database management:

• list: List all active databases available in the server.
• create: Create a new database file (for Microsoft Access, copies the empty.mdb template).
• connect: Connect to an existing database file, or creates an in-memory database if the file is not specified.
• disconnect: Close a database connection. For in-memory databases, this will clear all its data.

Data management:

• query: Execute a SQL query to retrieve data from a database.
• update: Execute a SQL query to insert/update/delete data in a database.
• import_csv: Imports data from a CSV file into a database table.
• export_csv: Exports data from a database table to a CSV file.
• import_excel: Imports data from an Excel file into a database table.

Notes management:

• read_notes: Reads notes from the specified file, or discovers notes in the specified directory.
• write_notes: Writes notes to the specified file, or linked to the specified database.

Note: Excel export is not implemented, use haris-musa/excel-mcp-server instead. The main problem is tracking the index of the rows and columns in the Excel file, to correctly import/export data to the same cells, and/or insert new rows/columns. In addition, merged cells complicate the process, it would be too complex to implement.

Project structure

Main files:

• server.py: MCP server implementation.

Tests:

• test_tools.py: Functions to test individual MCP tools.
• test_mcp.py: Tests all MCP tools in a typical workflow.

Documentation:

• README.md: This file, with general information about the project.
• LICENSE: MIT license.

Scouting scripts, used in the first stages to develop basic functionality:

• scouting_mdb.py: SQLAlchemy and pandas to interact with Microsoft Access databases.
• scouting_csv.py: SQLAlchemy and pandas to interact with CSV files.

TODO

• [x] Add tool to create a new database, copying empty.mdb to the specified path.
• [x] Add the ability to connect to multiple databases at the same time.
• [x] Add tool to list all tables in the database.
• [x] Add tools to import/export data from/to CSV files.
• [x] Add tools to import data from/to Excel files.
• [x] Add prompt to guide AI asking info to the user about the database.
• [x] Store info about files (.AInotes files), to retrieve it later.
• [ ] Add tool to remember imported/exported CSV and Excel files.