Инструменты

In-process analytical SQL database. Its CLI queries CSV, Parquet and JSON files directly with SQL, no import or server needed, so agents can sample and aggregate large files. Officially maintained.

Google's open-source database MCP server with ready-made query and SQL tools for dozens of sources, including PostgreSQL, MySQL, BigQuery, Spanner and MongoDB. Define controlled custom queries in tools.yaml.

Data analysis plugin: writes queries in each SQL dialect, explores datasets, runs statistical tests, charts with Python and builds interactive HTML dashboards, then reviews methods and conclusions before sharing. Connects to Snowflake, BigQuery and other warehouses. Official from Anthropic.

Anthropic's official data skill that guides agents to write, translate and optimize SQL across Snowflake, BigQuery, Databricks, PostgreSQL and other warehouse dialects, including CTEs, window functions and analytical aggregations.

Manages BigQuery datasets, tables and jobs with the bq and gcloud CLIs, runs SQL queries and loads data, with references for client libraries, MCP and Terraform. Google's official skill; requires a Google Cloud project.

Command-line framework for warehouse modeling and ELT transformations: write models in SQL and let dbt handle dependencies, data tests and documentation. v2 is rewritten in Rust as a single binary. Maintained by dbt Labs; needs a data warehouse connection.

PostgreSQL command-line client with smart autocompletion and syntax highlighting. Compatible with psql environment variables, and -c runs a statement and exits, so agents can query databases non-interactively.

MySQL terminal client with smart autocompletion and syntax highlighting, also compatible with MariaDB and TiDB. Supports --execute and batch mode with CSV or table output, so agents can run SQL directly.

Publishes SQLite databases as browsable, queryable web pages and JSON APIs, with SQL queries, metadata and plugins, and deploys to Cloud Run and other platforms with datasette publish. Great for data exploration and data journalism. Needs Python 3.10+.

Universal psql-style SQL command line: one tool to connect to PostgreSQL, MySQL, SQLite, SQL Server, Oracle and dozens of other SQL and NoSQL databases, with support for copying data between databases.

Linter and formatter for 20+ SQL dialects that auto-fixes most issues and handles Jinja templating and dbt projects (dbt needs a plugin), suited to warehouse code review and CI.

Query cloud resources and SaaS APIs live with SQL: plugins map AWS, Azure, GCP, GitHub, Kubernetes and other services to tables you can select from directly, no ETL needed. A single binary with Postgres built in.

Creates, edits and validates reproducible Python and SQL Jupyter notebooks: organizes cells as reports or tutorials, checks conclusions against actual output and reruns top to bottom before handoff. Maintained by OpenAI in the Data Analytics plugin of openai/plugins.

One server connecting PostgreSQL, MySQL, MariaDB, SQL Server, Oracle and SQLite, exposing just two tools by default to save context, with read-only mode and SSH tunneling. From Bytebase.

Framework for writing data transformation models in SQL or Python, with a Terraform-like plan/apply flow, virtual data environments, unit tests and table diffs, and transpilation across 10+ SQL dialects. A Linux Foundation project and an alternative to dbt.

A CLI and Python library by Simon Willison: imports JSON and CSV straight into SQLite with automatic table creation, runs in-memory SQL queries over files, and supports full-text search and table transformations.

Gives agents controlled access to MySQL: list databases and tables, inspect schemas and sample data, and run SQL, with multi-database mode, SSL and SSH tunnels. Configure your own database user, ideally with least privilege.

Runs SQL queries against ClickHouse and browses databases and table schemas, read-only by default; can also enable embedded chDB to query data directly in files and URLs. Maintained by ClickHouse.

dbt Labs' official plugin marketplace with dbt and dbt-migration plugins: write models and unit tests, build semantic-layer metrics, govern with dbt Mesh, debug failed jobs, and handle version upgrades and cross-platform migrations. Most skills need an existing dbt project.

dbt Labs' official skills: write and edit dbt models, add unit tests and docs, set up the MetricFlow semantic layer, debug failed jobs, and handle dbt version upgrades and cross-platform migrations. Most skills need dbt installed and an existing project.

Helps agents write geospatial SQL for PostGIS, DuckDB, BigQuery and Snowflake: inspect schemas and keep query costs in check, then render results as interactive maps to review and correct. Needs Python and your own database or warehouse; maps use Dekart, which can run locally in Docker.

Official DuckDB skills: query local or S3 CSV, Parquet, Excel and JSON files with SQL or plain language, attach databases, convert formats, analyze spatial data and look up documentation. Needs the DuckDB CLI; tested only on macOS and Linux.

Lets agents read dbt project models, lineage and Semantic Layer metrics, run build, run and test commands, and call the dbt platform Discovery and Admin APIs. Maintained by dbt Labs; Semantic Layer and platform tools need a dbt platform account.

Official ClickHouse skills: best practices for schema design, primary keys, JOINs and inserts ranked by impact, advice on real-time architecture decisions, in-process SQL and pandas-compatible analysis with chDB, and local and cloud deployment workflows.