chat_sql

A governed natural-language → SQL agent for Claude, delivered as an MCP server. Ask a question in plain English; the agent selects the right database, writes dialect-correct SQL, runs it through security-enforcing tools, and returns results — across ClickHouse, Teradata, PostgreSQL/GaussDB, MySQL, SQL Server, DB2, Oracle, and MongoDB.

Its defining feature is that the LLM is treated as untrusted. It is structurally unable to read raw PII, to modify any table it did not create, or to reach a database outside the sanctioned tools — regardless of how it is prompted.

Why it's safe by construction

LLM (untrusted)
   │  MCP over stdio — tool calls only
   ▼
mcp_server.py   ── UNPRIVILEGED face ──────────────────
   • no credentials, cannot import a connector
   • forwards every DB call over a local UNIX socket
   • run_python: no creds, no network (sandboxed)
   │  UNIX socket (0600)
   ▼
dbgateway.py   ── PRIVILEGED broker ───────────────────
   • the only holder of credentials + connectors
   • statement guard → write-guard → PII masking
   • returns sanitized rows only

Full threat model and control matrix: docs/SECURITY.md.

Related MCP server: nl2sql-mcp

Quick start

git clone <your-fork> chat_sql && cd chat_sql
uv venv && uv pip install -r requirements.txt      # install the DB drivers you need

cp database_creds.example.json database_creds.json # add your databases
cp pii_policy.example.yaml pii_policy.yaml          # classify your PII columns
cp .env.example .env                                # set CHATSQL_PII_SALT etc.

Register the MCP server with your client (.mcp.json or ~/.claude/settings.json):

{
  "mcpServers": {
    "chat-sql": {
      "command": "uv",
      "args": ["--directory", "/path/to/chat_sql", "run", "python", "mcp_server.py"]
    }
  }
}

For airtight run_python isolation, install bubblewrap (bwrap) or run the broker as a separate OS user — see docs/SECURITY.md §6.

Configuring databases

Each entry in database_creds.json has a short code (the db_key you pass to tools) and a service that selects the connector:

{
  "pg_demo": {
    "service": "postgres", "alias": "demo analytics",
    "host": "localhost", "port": 5432,
    "user": "…", "password": "…", "database": "analytics", "schema": "public"
  }
}

Supported service values: clickhouse, teradata, mysql, postgres (psql/gaussdb), mssql, db2, oracle, mongo.

Classifying PII

pii_policy.yaml pins which columns are masked and how (hash | redact). The broker also applies name-heuristics (default-deny on identifier-looking columns) and a raw-pattern backstop, so unlisted PII is still caught — but pin known PII explicitly. See pii_policy.example.yaml.

Tools

Database — run_query, run_query_file, export_to_csv, load_file, drop_table, list_databases, explain_query, table_info, search_schema, long_running_queries, kill_query. RAG examples — find_similar_queries, save_query_example, delete_query_example (needs a pgvector DB; set CHATSQL_RAG_DBKEY). Local compute — run_python (sandboxed), notify. Optional groups (off by default; enable with CHATSQL_*_ENABLED=1) — WhatsApp (whatsapp_*, transcribe_audio), email (send_email), Jupyter remote-exec (jupyter_*), wiki/memory (wiki_*).

Use it as a Claude skill

skills/chat-sql/SKILL.md packages the workflow so you can drop it into a .claude/skills/ directory and invoke it by name. See that file for details.

Running the security tests

uv pip install sqlglot pyyaml pytest
python -m pytest tests/ -v

The suite proves every control (PII masking, write-guard, connector isolation, statement guard) with no live database required.

License

MIT — see LICENSE.