Universal Mcp — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited Universal Mcp (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
<!-- mcp-name: io.github.Fashad-Ahmed/universal-db-mcp -->
The security-first, Python-native MCP server for database access from AI agents.
Demo: schema discovery, a real query, a blocked DROP, and dry-run mode
Most database MCP servers give AI agents raw SQL access and hope for the best. This server assumes the LLM is untrusted input and applies 8 layers of injection prevention before any query reaches your database — including blocking UNION attacks, stacked statements, time-based injection, and comment bypasses.
Supports: PostgreSQL · SQLite · MySQL · DuckDB (columnar analytics)
No Docker. No cloud account. No database server to install. DuckDB and SQLite run in-process:
# Query a local SQLite database — one command, zero infra
SQLITE_PATH=./myapp.db uvx universal-db-mcp
# Query a local DuckDB file or parquet files
DUCKDB_PATH=./analytics.duckdb uvx universal-db-mcp
# In-memory DuckDB for throwaway analysis
DUCKDB_PATH=:memory: uvx universal-db-mcpAdd to Claude Code in ~/.claude/mcp_servers.json, or to Claude Desktop in ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) / %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"mydb": {
"command": "uvx",
"args": ["universal-db-mcp"],
"env": {
"SQLITE_PATH": "/Users/you/projects/myapp/db.sqlite3",
"ALLOW_DESTRUCTIVE": "false"
}
}
}
}Restart Claude Desktop / Claude Code after saving — that's it.
That's it. Claude Code discovers the tools automatically.
More client configs (Claude Desktop, Cursor, Windsurf, Docker) in examples/.
Read-only by default. Defense-in-depth. Every query validated before it touches the driver.
| Layer | What it does |
|---|---|
| 1 | Driver-level read-only — PostgreSQL session flag, SQLite mode=ro URI, DuckDB read_only=True. Write rejected before SQL parsing. |
| 2 | Keyword blocking — DROP, DELETE, TRUNCATE, ALTER, INSERT, UPDATE, GRANT, EXEC blocked in read-only mode |
| 3 | Injection pattern detection — UNION SELECT, stacked statements, SQL comments (--, /*), xp_, SLEEP(), WAITFOR, BENCHMARK() |
| 4 | Multiple statement rejection — ; separating statements always blocked |
| 5 | Parameter type enforcement — only str, int, float, bool, null accepted as parameters |
| 6 | Result size limits — truncated at MAX_RESULT_ROWS (default 1000) to prevent memory exhaustion |
| 7 | Identifier sanitization — table/column names stripped of metacharacters in internally-generated SQL |
| 8 | DuckDB filesystem blocklist — read_csv(), read_parquet(), glob(), LOAD, INSTALL, httpfs, COPY blocked at adapter level; read_only=True only blocks writes, not file reads |
Full threat model: docs/SECURITY.md
DuckDB runs in-process (no server) and reads Parquet, CSV, JSON natively. Connect AI agents to your analytics data without spinning up a warehouse:
# Query parquet files directly
DUCKDB_PATH=:memory: uvx universal-db-mcpThen in Claude Code:
You: "Load sales.parquet and show me monthly revenue by region"
Claude: [uses query tool → SELECT region, strftime('%Y-%m', date) AS month, SUM(revenue) ...]No separate NL-to-SQL tool needed — Claude already does this. Give it the schema tool and ask in plain English:
You: "Which customers placed more than 5 orders last month?"
Claude: [calls schema() to see table structure, then query() with the
generated SQL — every query still passes through all 8 security
layers before touching your database]Pair with dry_run: true (DRYRUN=true) while prototyping — Claude gets the query plan back without anything executing.
docker build -t universal-db-mcp .
docker run -i --rm \
-e POSTGRES_URI=postgresql://readonly:[email protected]:5432/mydb \
-e ALLOW_DESTRUCTIVE=false \
universal-db-mcpSee examples/docker_mcp_config.json for wiring this into an MCP client.
# PostgreSQL
POSTGRES_URI=postgresql://readonly:pass@localhost/mydb uvx universal-db-mcp
# SQLite (local file, zero infra)
SQLITE_PATH=./db.sqlite3 uvx universal-db-mcp
# MySQL
MYSQL_URI=mysql://readonly:pass@localhost/mydb uvx universal-db-mcp
# DuckDB (columnar, in-process analytics)
DUCKDB_PATH=./analytics.duckdb uvx universal-db-mcp
# Multiple databases simultaneously
POSTGRES_URI=... SQLITE_PATH=... uvx universal-db-mcp| Tool | Description |
|---|---|
query | Execute SQL — read-only by default, all 8 security layers apply |
schema | Inspect tables and columns — no config needed |
explain | Get query execution plan without running the query |
health | Check connection status, DB version, and pool metrics |
list_databases | Show all configured databases and connection state |
query_history | Inspect the last 100 executed queries |
snapshot_schema | Capture current schema for drift detection |
schema_diff | Compare current schema against the last snapshot |
v1.1.0: dry-run mode (DRYRUN=true), table allowlists (WHITELISTED_TABLES), query complexity warnings, structured audit logs, and a --check CLI flag for connectivity validation. See CHANGELOG.md.
# ── PostgreSQL ─────────────────────────────────────
POSTGRES_URI=postgresql://user:pass@host:5432/db
POSTGRES_READONLY=true # default: true
# ── SQLite ─────────────────────────────────────────
SQLITE_PATH=/path/to/database.db
SQLITE_READONLY=true # default: true
# ── MySQL ──────────────────────────────────────────
MYSQL_URI=mysql://user:pass@host:3306/db
MYSQL_READONLY=true # default: true
# ── DuckDB ─────────────────────────────────────────
DUCKDB_PATH=/path/to/analytics.duckdb # or :memory:
DUCKDB_READONLY=true # default: true
# ── Security ───────────────────────────────────────
ALLOW_DESTRUCTIVE=false # default: false — blocks INSERT/UPDATE/DELETE/DROP
MAX_RESULT_ROWS=1000 # truncate large results
ENABLE_LOGGING=true # log queries to stderr
QUERY_TIMEOUT=30 # seconds
RATE_LIMIT_RPM=60 # requests per minuteAlways use a dedicated read-only account. Never give the MCP server credentials that can modify data.
PostgreSQL:
CREATE USER mcp_agent WITH PASSWORD 'strong_random_password';
GRANT CONNECT ON DATABASE mydb TO mcp_agent;
GRANT USAGE ON SCHEMA public TO mcp_agent;
GRANT SELECT ON ALL TABLES IN SCHEMA public TO mcp_agent;MySQL:
CREATE USER 'mcp_agent'@'localhost' IDENTIFIED BY 'strong_random_password';
GRANT SELECT ON mydb.* TO 'mcp_agent'@'localhost';
FLUSH PRIVILEGES;git clone <repo-url>
cd universal-db-mcp
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"
# Run tests (67+ passing, no external DB required for SQLite + DuckDB)
pytest
# Security tests only
pytest tests/test_security.py -v
# With coverage
pytest --cov=src/universal_db_mcp --cov-report=term-missingsrc/universal_db_mcp/
├── server.py # FastMCP server — 5 tools
├── config.py # Env-var config via Pydantic
├── adapters/
│ ├── base.py # Abstract adapter + result dataclasses
│ ├── postgresql.py # asyncpg, connection pool, read-only via init callback
│ ├── sqlite.py # aiosqlite, read-only via file URI mode=ro
│ ├── mysql.py # aiomysql, DictCursor
│ └── duckdb.py # duckdb, thread-pool executor, lock-guarded
└── security/
└── sanitizer.py # SQLSanitizer — 8-layer injection prevention
docs/
└── SECURITY.md # Full security architecture and threat model| This project | Google MCP Toolbox | |
|---|---|---|
| Runtime | Python — pip install / uvx | Go binary / Docker |
| Local DBs | SQLite + DuckDB zero-infra | No SQLite |
| Analytics | DuckDB in-process | No columnar adapter |
| Auth model | Read-only by default + env vars | IAM / GCP-native |
| SQL injection | 8-layer sanitizer + parameterized | Auth-focused |
| Extend | Python ecosystem, any pip package | Go plugins |
| Vendor | Neutral | Google Cloud funnel |
Different tools for different jobs. Use this when you want Python-native, local-first, security-hardened access without cloud dependencies.
MIT — LICENSE
Security Notice: This server provides AI agents with database access. Always use read-only credentials, review docs/SECURITY.md before production deployment, and never commit .env files.
~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.