🗄️数据库 MCP（PostgreSQL / MySQL / Redis）

Explore, query, and inspect SQLite databases with ease. List tables, preview results, and view det…

Explore your Messages SQLite database to browse tables and inspect schemas with ease. Run flexible…

Explore and discover video games from the Internet Game Database. Search titles, view detailed inf…

Sling CLI MCP server for querying any database, running data pipelines and managing replications

MCP server for querying PostgreSQL databases

GibsonAI MCP server: manage your databases with natural language

Manage Supabase projects end to end across database, auth, storage, realtime, and migrations. Moni…

Same functionality, consuming only 1/20 of the context window tokens.

UPDATED 9/1/2025! NEW TOOLS! Use the Redis Stream tools with n8n MCP Client Node for use anywhere!…

Search Japanese company database

An MCP server for Text2SQL: transforms natural language into SQL using graph schema understanding.

MCP server for local SQLite database operations

Connect to your Supabase database to query data and schemas.

MCP server for Trino distributed SQL query engine access

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

Review a GitHub issue or pull request URL as a node-redis maintainer, with a staged assessment of whether the claim is real, practically important, already solvable with supported functionality, correctly scoped, better served by another design, and worth maintainer and contributor effort. Use when assessing issue validity or severity, deciding whether an issue should be prioritized or closed, determining whether a requested feature represents an unmet need rather than a discoverability or usage gap, judging whether a PR is worth bringing to mergeable quality, comparing open PRs or alternative designs, separating code quality from repository readiness, or drafting a concise maintainer assessment. When closure, additional evidence, or code changes should be requested, also produce a polite, concise, complete, copy-paste-ready maintainer comment.

Run the Omnigent server as a Docker compose stack (server + Postgres) on any Docker host — your laptop, a VPS, EC2 by hand, or as the base layer of any container-platform deploy. Invoke when the user wants to build the image, bring up the compose stack, debug the stack on a host they already have, or extend the stack for a new platform.

QA the omo Codex Light edition (lazycodex / packages/omo-codex) itself, in strict isolation so ONLY our plugin is exercised, never the user's real ~/.codex. The first-party method drives the real `codex app-server` against an isolated CODEX_HOME plus a LOCAL mock model (no real API call), and proves a plugin hook fired by asserting hook/started + hook/completed notifications. Also: isolated install verification, per-component hook probes, a tmux TUI smoke, and runtime log observation (RUST_LOG / logs SQLite / /debug-config). Ships tested helper scripts each with a --self-test. Use whenever someone changes anything under packages/omo-codex or wants to QA, smoke-test, verify, or debug the Codex plugin, its hooks/components, the installer/config.toml, the app-server flow, or the Codex TUI. Triggers: codex qa, qa codex, codex-qa, test codex plugin, verify codex hook, codex app-server, lazycodex qa, isolated CODEX_HOME, prove codex hook fired, codex tui test.

Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

Backend development specialist covering API design, database integration, microservices architecture, and modern backend patterns. Use when designing APIs, implementing server logic, authentication, or authorization.

Database specialist covering PostgreSQL, MongoDB, Redis, Oracle, and cloud database platforms (Neon, Supabase, Firestore). Use for schema design, query optimization, indexing strategies, data modeling, or cloud database selection. Cloud vendor guide absorbed from moai-platform-database-cloud.

SQLiteCpp CI workflow patterns. Use for GitHub Actions, AppVeyor, Travis, matrices, or test steps.

Diagnose a slow SQL query and produce a concrete optimization plan. Use when asked to optimize SQL, speed up a slow query, reduce a query's cost/scan, fix a timeout, or review a query plan. Produces an analysis — the likely bottleneck, what the plan is doing wrong (full scans, bad joins, spills), the specific rewrite and index/partition changes, and the expected impact, with the optimized query.

SQLiteCpp change workflow checklists for API, tests, build files, and CHANGELOG updates. Use when adding a method or class, editing build files, or writing a CHANGELOG entry for a PR.

Code generation and conversion for Next.js 16 applications using Cache Components (PPR). Use when the user requests to "convert to use cacheComponents" at project or page level, create new Next.js pages/components with proper caching directives, split pages into cached and dynamic sections with Suspense boundaries, or work with Next.js 16's new caching model including use cache, cacheLife, Suspense, and anonymous Supabase clients for cache-friendly data fetching.

Audit SQL for the cost & performance anti-patterns that burn warehouse credits. Scores warehouse health 0-100 and outputs a prioritized cost-reduction plan for BigQuery, Snowflake, Redshift, and Postgres.

SQLiteCpp coding standards and API rules for core edits, public headers, style, and Doxygen.

Use when writing or reviewing Python code with SQLModel, especially models, sessions, queries, FastAPI integration, relationships, link models, creates, updates, and deletes.

HiMarket backend coding standards for Java and Spring Boot. Use whenever modifying or reviewing himarket-server, himarket-dal, himarket-bootstrap, backend Maven POMs, Flyway SQL, controllers, services, DTOs, repositories, validation, logging, exceptions, or backend tests. Read docs/standards/backend before editing.

Use this skill before writing any SQL query. Covers: output shape inference (cardinality clues from the question), efficient schema exploration, iterative CTE-based query building, structured verification loop (row count, NULL audit, fan-out check, sample inspection), error recovery protocol, saving output to result.sql and result.csv, turn budget management, and common benchmark traps.

Secure coding practices for agent-native apps: input validation, SQL injection, XSS, secrets, data scoping, and auth. Use when writing any action, route, or component that touches user data or external input.

Security best practices and vulnerability prevention for Golang. Covers injection (SQL, command, XSS), cryptography, filesystem safety, network security, cookies, secrets management, memory safety, and logging. Apply when writing, reviewing, or auditing Go code for security, or when working on any risky code involving crypto, I/O, secrets management, user input handling, or authentication. Includes configuration of security tools.

用于火山引擎（Volcengine）数据库（MySQL、veDB-MySQL、PostgreSQL、SQL Server、MongoDB、Redis）和公网自建数据库（MySQL和PostgreSQL系列）的元数据管理、数据分析、开发变更、运维诊断、巡检。覆盖实例列表查询、实例下数据库列表查询、表列表查询、表结构查询、数据查询、数据分析与可视化报告（含跨数据源/文件联合分析）、数据治理（资产盘点/数据画像/数据质量/敏感数据识别）、慢查询诊断、死锁与锁等待分析、事务与活跃会话排查、错误日志查询、表空间分析、健康巡检、监控指标查询、变更工单申请等场景。不支持字节云（ByteCloud）数据库，如 ByteRDS / ByteDoc / ByteRedis。

使用 SQL 安全查询当前已选择的数据表

Working on the RomM Python backend (backend/) — a FastAPI app with SQLAlchemy 2.0, Alembic, RQ/Redis, and Socket.IO. Use when adding or changing API endpoints, handlers, ORM models, response schemas, metadata-provider adapters, background tasks, database migrations, or backend tests. Covers the layered architecture, conventions, auth/scopes, the OpenAPI→frontend type pipeline, and the uv/pytest/alembic/trunk workflow. Trigger on any work under backend/.

How to update the bundled SQLite3 amalgamation (sqlite3/sqlite3.c and sqlite3.h) and the Meson wrap. Use when upgrading SQLite, refreshing the vendored amalgamation, or bumping the sqlite3 wrap.

SQLiteCpp release procedure: bump the version across all files, finalize the CHANGELOG, open the Release PR, and tag. Use when cutting a new release, bumping the project version, or tagging.

SQLiteCpp branch naming and creation rules for starting tasks, issues, or features.

Build SQLiteCpp with CMake. Use for CMake builds, tests, options, or build scripts.

This skill should be used when the user asks to "optimize SQL queries", "explore database schemas", "generate migration SQL", "analyze query performance", or "document database structure".

Database design with schema analysis, index optimization, and migration generation for PostgreSQL, MySQL, MongoDB, and DynamoDB. Use when designing schemas, optimizing queries, planning migrations, or analyzing database performance.

Design relational schemas from requirements with normalization, migrations, ERDs, RLS policies, and indexes for PostgreSQL, MySQL, and SQLite. Use when designing new features, reviewing schemas, or adding multi-tenancy.

Backend development with Node.js/Express/Fastify and PostgreSQL. Use when designing REST or GraphQL APIs, optimizing database queries, implementing authentication, building microservices, handling migrations, or reviewing backend code.

Design, build, and operate Kubernetes operators. Use when extending Kubernetes with a custom controller, choosing a framework, designing CRDs, implementing reconciliation loops, or auditing an operator for anti-patterns.

Run EXPLAIN QUERY PLAN against every query in a sqlc-style catalog and diff the plans against a baseline. Detects new full-table SCANs and TEMP B-TREE sort scans introduced by PRs. SQLite/D1-only today; engine extension noted below.

React/Redux frontend development patterns for RedisInsight UI: component folder structure, styled-components, hooks, named exports, barrel files, layout components, and theme usage. Use when editing any file under redisinsight/ui/**, writing or modifying React components, Redux slices, styled-components, custom hooks, or when the user mentions UI, frontend, React, Redux, or styled-components.

Unit/integration testing standards for RedisInsight using Jest and Testing Library: test structure, the `renderComponent` helper, faker for test data, mocking patterns, and `waitFor` instead of fixed time waits. Use when writing or modifying any `*.spec.ts` or `*.spec.tsx` file, when adding component or slice tests, when debugging flaky tests, or when the user mentions jest, testing library, faker, or test patterns.