Databases MCP Server (Access and SQLite 3)
Enables AI to interact with Microsoft Access (.mdb, .accdb) and SQLite 3 databases, including read-only support for Access 97 databases. Supports executing SQL queries, importing/export data from CSV and Excel files, and storing notes about database files.
README
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:
.mdband.accdbfiles- Supports both modern Access formats (via ACE ODBC driver)
- Supports legacy Access 97 databases (via access-parser library - read-only)
- SQLite 3:
.db,.sqlite, and.sqlite3files - In-memory SQLite: When no database path is specified
Access 97 Support
Access 97 (.mdb) databases are supported in read-only mode using the access-parser library. This allows:
- Reading data from Access 97 databases without needing ODBC drivers
- Basic SELECT queries to retrieve data
- No external dependencies (pure Python implementation)
Limitations:
- Access 97 databases are read-only (no INSERT, UPDATE, DELETE operations)
- Only basic SELECT queries are supported (no complex JOINs or subqueries)
- Parameterized queries are not supported for Access 97 databases
The server automatically detects Access 97 format and falls back to access-parser when needed.
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:
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.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。