Allows AI to interact with Microsoft Access databases, supporting data import and export via CSV files.
A simple MCP server to let AI interact with Microsoft Access 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!
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.
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 import/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.
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:
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.BigQuery database integration with schema inspection and query capabilities
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