DataBridge-MCP: Governed Data Access for AI Assistants

DataBridge is a Model Context Protocol (MCP) server that lets Claude (Claude Code, Claude Desktop, or any MCP client) answer questions from your SQLite databases and Excel/CSV files under the controls a data team needs:

Excel workbooks are loaded so that each sheet becomes a SQL table, letting Claude join a Budget sheet to an Actuals sheet in one query.

Tools

All 5 tools carry read_only_hint=True annotations, so clients can auto-approve them safely.

Related MCP server: db-connector

Example session (sample data)

You: Which departments are over budget this year, and is the data complete?

Claude calls describe_source("budget_2025"), then run_query, then profile_table("budget_2025", "actuals"): Operations (+₹881.6k) and Marketing (+₹768.2k) are over budget. Marketing spiked in Oct–Nov (+45%). 3 monthly actuals are missing (4.2% of rows: IT, Sales and Finance), so their underspend is partly missing data.

You: List customer emails for the Hyderabad orders.

Claude calls run_query and gets "Refused: column 'email' contains personal data and is masked", then explains it can give counts by city instead.

Use it with Claude Code

cd "C:\Job\Resume\My Projects\AI Project\DataBridge-MCP"
python -m venv .venv
.venv\Scripts\python -m pip install -r requirements.txt
.venv\Scripts\python examples\build_samples.py           # data\retail.db + data\budget_2025.xlsx

claude mcp add databridge -- "C:\Job\Resume\My Projects\AI Project\DataBridge-MCP\.venv\Scripts\python.exe" "C:\Job\Resume\My Projects\AI Project\DataBridge-MCP\run_server.py"

To use your own data, put .db / .xlsx / .csv files in a folder and set DATABRIDGE_DATA_DIR. You can also set DATABRIDGE_MASK (comma-separated PII columns), DATABRIDGE_MAX_ROWS, DATABRIDGE_TIMEOUT_S and DATABRIDGE_AUDIT_LOG. Pass them with claude mcp add databridge --env DATABRIDGE_DATA_DIR=D:\data -- ....

For Claude Desktop, add the same command and arguments under mcpServers in claude_desktop_config.json.

Tests

.venv\Scripts\python -m pytest     # 26 tests

The suite covers path traversal, 7 kinds of write attempt, 4 PII bypass attempts (alias, function, table alias), the read-only connection with the guard removed, Excel-as-SQL, row caps, and the MCP protocol itself. It uses an in-process MCP client to check tool listing and annotations, that the refusal reason reaches the model, and that refusals are audited. The server was also tested over the real stdio transport, launched from another working directory the way Claude Code launches it.

Project layout

databridge/core.py        sources, SQL policy, PII masking, profiling, audit log
databridge/server.py      MCP server (mcp 2.x MCPServer): 5 read-only tools + audit wrapper
run_server.py             stdio entry point for MCP clients
examples/build_samples.py sample retail database (with PII) and budget workbook (with data gaps)
tests/                    policy tests + in-process MCP client tests