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Sql Review Agent

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Enables reviewing BigQuery SQL queries for performance issues, cost estimation, and suggested rewrites via an MCP interface.

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Описание

Enables reviewing BigQuery SQL queries for performance issues, cost estimation, and suggested rewrites via an MCP interface.

README

An agentic AI system that reviews BigQuery SQL queries before you run them — catching performance issues, estimating cost, and suggesting rewrites.


What it does

Paste a BigQuery SQL query and the agent:

  1. Static analysis — instantly flags SELECT *, missing partition filters, cartesian joins
  2. Schema fetch — reads partition keys, clustering fields, and row counts from BigQuery
  3. Cost estimate — dry-runs the query to get bytes scanned without executing it
  4. Rewrite — returns improved SQL with a plain-English explanation
  5. Severity ratingnone / low / medium / high / critical

Architecture

The agent is modelled as a LangGraph state machine:

Agent graph

  • call_llm — sends messages + tools to Claude/Gemini
  • run_tools — dispatches get_table_schema, dry_run_sql, write_report
  • route — conditional edge: loop back if tool calls remain, stop when write_report is called

Three trigger modes

Mode How
CLI python agent.py --sql "SELECT * FROM ..."
Web UI python server.py → open localhost:5001
MCP Any MCP-compatible client (Claude Code, Cursor, Zed, OpenClaw)

Setup

git clone https://github.com/ARAVINDHRAJA123/sql-review-agent.git
cd sql-review-agent
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txt

export GCP_PROJECT=your-project
export BQ_LOCATION=asia-south1
export GEMINI_API_KEY=your-key     # free tier: aistudio.google.com
# or: export ANTHROPIC_API_KEY=your-key

gcloud auth application-default login

MCP (Claude Code)

claude mcp add -s user sql-review -- \
  /path/to/venv/bin/python /path/to/mcp_server.py

Tools available in any MCP client:

  • review_sql — full agentic review (LLM + BQ)
  • quick_check — instant static analysis, no LLM needed

CLI usage

python agent.py --sql "SELECT * FROM \`project.dataset.table\`"
python agent.py --file query.sql --verbose

Web UI

Web UI

python server.py
# open http://localhost:5001

Tests

pytest
pytest tests/test_tools.py -v

Project structure

sql-review-agent/
├── agent.py          ← raw tool-use loop (Claude + Gemini)
├── graph_agent.py    ← LangGraph state machine (drop-in replacement)
├── mcp_server.py     ← FastMCP server (review_sql + quick_check tools)
├── server.py         ← Flask web UI + JSON API
├── tools/
│   ├── bq_tools.py   ← dry_run, schema, metadata, read-only guard
│   └── sql_tools.py  ← static analysis, table extraction
├── tests/
│   ├── test_tools.py ← 24 unit tests
│   └── test_agent.py ← 7 unit tests
└── docs/
    ├── architecture_graph.svg  ← state machine diagram
    └── web_ui.png              ← Flask UI screenshot

Stack

Python · BigQuery · Claude API · Gemini API · LangGraph · FastMCP · Flask · pytest

from github.com/ARAVINDHRAJA123/sql-review-agent

Установка Sql Review Agent

У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.

▸ github.com/ARAVINDHRAJA123/sql-review-agent

FAQ

Sql Review Agent MCP бесплатный?

Да, Sql Review Agent MCP бесплатный — установка в пару кликов через Unyly без оплаты.

Нужен ли API-ключ для Sql Review Agent?

Нет, Sql Review Agent работает без API-ключей и переменных окружения.

Sql Review Agent — hosted или self-hosted?

Доступен hosted-вариант: Unyly запускает сервер в облаке, локальная установка не обязательна.

Как установить Sql Review Agent в Claude Desktop, Claude Code или Cursor?

Открой Sql Review Agent на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.

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