bq-readonly-mcp
🔍 Read-only BigQuery MCP server with auto-LIMIT, dry-run cost guard, and ADC auth. Safe for LLMs to query your BigQuery — no DML, no surprises, no runaway bills.
✨ Why this exists
LLMs connected to BigQuery can accidentally scan terabytes if the MCP layer lets them run arbitrary SQL. bq-readonly-mcp prevents that by design: every query goes through a strict SELECT/WITH-only validator, gets an automatic LIMIT injected before it runs, and is priced via a dry-run before any bytes are billed. If the estimated cost exceeds the cap (default 1 GB), the query is refused outright — before a single byte hits your bill.
The server runs as a local stdio process under your OS account, uses Application Default Credentials, and exposes zero write operations. There is no INSERT, no UPDATE, no DELETE, no DDL — anywhere in the codebase. The only thing it can do is read, and it does that safely.
🛠️ The 7 tools
| Tool | What it does | Use when… |
|---|---|---|
list_datasets |
List datasets in the project, with optional name filter | Starting exploration, finding what exists |
list_tables |
List tables in a dataset, with optional name filter | Drilling into a specific dataset |
get_table_metadata |
Table type, partitioning, clustering, row count, size | Checking if a table is large before querying |
describe_columns |
Column schema for a table (no data scan) | Understanding the shape of a table cheaply |
get_table |
Full bundle: metadata + columns + 3 sample rows | Onboarding to an unfamiliar table |
run_query |
SELECT-only with auto-LIMIT, dry-run cost guard, and bytes-billed cap |
Running ad-hoc SQL |
estimate_query_cost |
Standalone dry-run — returns estimated bytes and USD cost | Checking query cost before running it |
🚀 Quick start
Recommended — run directly via uvx (no install needed):
uvx bq-readonly-mcp --project your-project-id --location US
From PyPI (persistent install):
uv tool install bq-readonly-mcp
bq-readonly-mcp --project your-project-id --location US
From source:
git clone https://github.com/mariadb-RupeshBiswas/bq-readonly-mcp.git
cd bq-readonly-mcp
uv run bq-readonly-mcp --project your-project-id --location US
For a full walkthrough (five steps from zero), see docs/QUICKSTART.md.
🔐 Authentication
The server uses Application Default Credentials (ADC). Run this once:
gcloud auth application-default login
For non-interactive environments (CI, containers, service accounts), pass a key file:
bq-readonly-mcp --project your-project-id --key-file /path/to/service-account.json
Or set GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json.
🔌 Plug it into your editor
Full walkthroughs for each client — config file paths, JSON snippets, restart steps — are in docs/EDITOR_SETUP.md.
Covered clients: Claude Code, Claude Desktop, Cursor, Windsurf, GitHub Copilot (VS Code), Cline, Continue.dev, Zed, Gemini CLI.
Claude Code — quick example:
claude mcp add --transport stdio bq-readonly -- \
uvx bq-readonly-mcp --project your-project-id --location US
Or add to ~/.claude.json (global) or .mcp.json (project-level):
{
"mcpServers": {
"bq-readonly": {
"command": "uvx",
"args": [
"bq-readonly-mcp",
"--project", "your-project-id",
"--location", "US"
]
}
}
}
Ready-to-paste configs for all supported clients are in mcp-config-examples/.
⚙️ Configuration reference
All flags can also be set via environment variables. CLI flags take precedence over env vars; env vars take precedence over defaults.
| CLI flag | Env var | Default | Description |
|---|---|---|---|
--project |
GCP_PROJECT_ID |
(required) | GCP project to query |
--location |
BIGQUERY_LOCATION |
US |
BigQuery processing location |
--datasets |
BIGQUERY_ALLOWED_DATASETS |
(none — all allowed) | Space-separated dataset allowlist; comma-separated in env var |
--default-limit |
BIGQUERY_DEFAULT_LIMIT |
50 |
Rows injected by auto-LIMIT |
--max-limit |
BIGQUERY_MAX_LIMIT |
10000 |
Hard cap on per-query LIMIT |
--max-bytes-billed |
BIGQUERY_MAX_BYTES_BILLED |
1073741824 (1 GB) |
Per-query bytes-billed cap |
--sample-rows |
BIGQUERY_SAMPLE_ROWS |
3 |
Rows returned by get_table preview |
--key-file |
GOOGLE_APPLICATION_CREDENTIALS |
(uses ADC) | Path to service-account JSON |
🛡️ Safety model
- SELECT/WITH only — The SQL validator strips comments, then rejects any statement that doesn't start with
SELECTorWITH, or that contains DML/DDL keywords (INSERT,UPDATE,DELETE,DROP,CREATE,MERGE, …). - Auto-LIMIT —
LIMIT Nis injected if absent. The caller can raise it up to--max-limit(default 10,000). - Dry-run cost guard — Every
run_querycall first runs a dry-run to estimate cost. Queries exceeding--max-bytes-billedare refused before any bytes are billed. - Dataset allowlist — Optional
--datasetsflag restricts access to named datasets. A startup warning is logged when unset. - Defense in depth —
maximumBytesBilledis also set on the real job as a server-side backstop.
Full details and threat model → SECURITY.md
🚫 What it does NOT do
- Write operations of any kind (INSERT, UPDATE, DELETE, DDL) — by design, forever
- Vector / embedding search — deferred to a future release
- Multi-project queries — one server, one GCP project
- Job history / audit log access — privacy footgun, intentionally omitted
- Storage API (export, streaming reads)
These are intentional omissions. v0.1 focuses on safe, read-only schema exploration and SQL queries.
🤔 vs other BigQuery MCPs
| Feature | bq-readonly-mcp | pvoo/bigquery-mcp ecosystem |
|---|---|---|
| Read-only enforced | ✅ validator + zero write tools | Varies by fork |
| Dry-run cost guard | ✅ refuses over-budget queries | Not standard |
| Auto-LIMIT injection | ✅ default 50, cap 10,000 | Not standard |
| Dataset allowlist | ✅ optional --datasets |
Not standard |
| ADC auth | ✅ | ✅ |
| Vector / embedding search | No (v0.1) | Some forks |
| PyPI package | ✅ bq-readonly-mcp |
Varies |
💻 Development
# Install with dev deps
uv sync --extra dev
# Run unit tests (fast, no BigQuery required)
uv run pytest tests/unit/ -q
# Run integration tests (requires ADC + BigQuery access)
uv run pytest -m integration -q
# Lint
uv run ruff check src tests
# Type check
uv run mypy src
📜 License
MIT — see LICENSE
Metadata
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