Install
$ agentstack add mcp-rudraraval4-mcp-db-server Open-source listing, not yet scanned by AgentStack. Follow the source repository for install instructions.
Security review
⚠ Flagged1 finding(s); flagged for manual review. · v0.1.0 How review works →
- • Prompt-injection patterns
- • Secret / credential exfiltration
- • Dangerous shell & filesystem operations
- • Untrusted network calls
- • Known-malicious package signatures
- high Destructive filesystem operation.
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
> A production-grade MCP server that lets any LLM client (Claude Desktop, Cursor, …) > query a SQL database in natural language — read-only, AST-validated, and capped.
The LLM writes the SQL. This server never trusts it. Every query is parsed to an abstract syntax tree and forced through a safety gate before it is allowed near a read-only database connection.
Why this exists
Letting an LLM run SQL against your database is powerful and terrifying in equal measure. The hard part isn't generating SQL — clients already do that well. The hard part is guaranteeing the generated SQL can't read what it shouldn't, can't write, and can't run away with your database. That guarantee is this project.
Safety guarantees
Every run_query call must pass the Safety Core before execution:
- Read-only — only
SELECT/WITH … SELECTsurvive; all DML/DDL is rejected at
the AST level (not by keyword regex, so comment and casing tricks don't help).
- Single statement — stacked queries (
SELECT …; DROP …) are rejected. - Table access control — allow-list and deny-list enforced against the parsed tables.
- Row caps — a
LIMITis injected/enforced atMCP_DB_MAX_ROWS. - Statement timeout — long queries are aborted.
- Audit log — every attempt (allowed or blocked) is logged.
These aren't aspirations — each is pinned by an adversarial test in [tests/test_safety.py](tests/testsafety.py) (casing tricks, comment injection, stacked statements, SELECT … INTO, PRAGMA/ATTACH, and more). A second, independent layer is proven in [tests/test_engine.py](tests/testengine.py): even a write that somehow reached the engine is rejected by the read-only connection.
Tools
| Tool | Purpose | |------|---------| | list_tables() | Tables visible under the access policy | | describe_table(name) | Columns, types, keys | | explain_query(sql) | Explains a query (and engine plan) without returning rows | | run_query(sql) | Validated, capped, read-only result set |
Examples
You ask in plain English; the client LLM writes the SQL; the server validates, caps, and runs it read-only. Real output from the bundled demo.db:
"What's total revenue by product category?"
SELECT p.category, ROUND(SUM(oi.quantity * oi.unit_price), 2) AS revenue
FROM products p JOIN order_items oi ON oi.product_id = p.id
GROUP BY p.category ORDER BY revenue DESC;
| category | revenue | |---|---| | Electronics | 85746.19 | | Furniture | 76442.0 | | Apparel | 39219.91 | | Sports | 18746.5 | | Home | 12596.5 | | Stationery | 1663.22 |
"How many orders are there by status?"
SELECT status, COUNT(*) AS orders FROM orders GROUP BY status ORDER BY orders DESC;
| status | orders | |---|---| | completed | 206 | | cancelled | 79 | | shipped | 58 | | pending | 57 |
"Which products have never been ordered?"
SELECT name, category FROM products
WHERE id NOT IN (SELECT DISTINCT product_id FROM order_items);
| name | category | |---|---| | Sticky Notes | Stationery | | Desk Planner | Stationery | | Highlighter Set | Stationery |
"Now delete the orders table." → Query rejected by safety policy: only read-only SELECT queries are allowed.
Quickstart
git clone https://github.com/rudraraval4/mcp-db-server
cd mcp-db-server
pip install -e ".[dev]"
python scripts/seed_db.py # creates demo.db (e-commerce sample data)
Try it in 30 seconds (no MCP client needed)
The bundled mcp-db-demo CLI drives the exact same service the MCP server exposes — so what you see here is what an LLM client gets:
mcp-db-demo tables
mcp-db-demo describe customers
mcp-db-demo query "SELECT country, COUNT(*) FROM customers GROUP BY country ORDER BY 2 DESC"
# the safety layer in action — every one of these is refused:
mcp-db-demo query "UPDATE products SET price = 0"
mcp-db-demo query "SELECT * FROM customers; DROP TABLE customers"
Use it in Claude Desktop
Add the server to your claude_desktop_config.json, then fully restart Claude Desktop.
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"db": {
"command": "mcp-db-server",
"env": {
"MCP_DB_DATABASE_URL": "sqlite:///absolute/path/to/demo.db",
"MCP_DB_MAX_ROWS": "1000"
}
}
}
}
> command must resolve to the installed mcp-db-server executable. If it isn't on > Claude Desktop's PATH, use the absolute path (e.g. inside your virtualenv: > .../.venv/Scripts/mcp-db-server.exe on Windows, .../.venv/bin/mcp-db-server on macOS/Linux).
Then just ask, in plain English:
> "What tables are in the database?" · "Which five customers spent the most?" · > "Delete the orders table" → politely refused.
Configuration
All knobs are environment variables (prefix MCP_DB_):
| Variable | Default | Meaning | |----------|---------|---------| | MCP_DB_DATABASE_URL | sqlite:///./demo.db | SQLAlchemy URL (SQLite or Postgres) | | MCP_DB_MAX_ROWS | 1000 | Hard row cap | | MCP_DB_STATEMENT_TIMEOUT_SECONDS | 10 | Abort slow queries | | MCP_DB_ALLOWED_TABLES | (empty) | Allow-list; if set, only these tables | | MCP_DB_DENIED_TABLES | (empty) | Deny-list | | MCP_DB_AUDIT_LOG_PATH | audit.log | Audit log location |
Architecture
The client LLM does the natural-language → SQL reasoning. The server contributes the thing clients can't safely do themselves: a hard, enforced boundary around what that SQL is allowed to do. Two independent layers stand between a query and your data — the Safety Core (refuses to emit anything but a capped, read-only SELECT) and the engine (refuses to execute a write, regardless).
Project layout
src/mcp_db_server/
config.py # env-driven settings — every safety knob
safety.py # Safety Core: sqlglot AST validation (the heart)
engine.py # SQLAlchemy read-only access + introspection
service.py # shared logic behind both front-ends
server.py # MCP server (FastMCP, stdio)
cli.py # mcp-db-demo: same service, no MCP client needed
formatting.py # result rendering
audit.py # JSONL audit log
scripts/seed_db.py # reproducible demo database
tests/ # 73 tests, 97% coverage
Development
pip install -e ".[dev]"
pytest # 73 tests
pytest --cov=mcp_db_server # coverage
Optional Postgres support: pip install -e ".[postgres]" and point MCP_DB_DATABASE_URL at a postgresql://… URL.
How I built this
A short write-up of the design and the key decision (NL→SQL belongs in the client, not the server) is in [WRITEUP.md](WRITEUP.md).
License
MIT — see [LICENSE](LICENSE).
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: rudraraval4
- Source: rudraraval4/mcp-db-server
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.