Anyquery 是一個 SQL 查詢引擎，讓你能對 40 多種應用程式、檔案和資料庫執行 SQL，包括 GitHub、Notion、Chrome 和 Apple Notes。它建構於 SQLite 之上，並支援 MCP 伺服器，可將 AI 代理連接到跨服務的結構化資料。
Anyquery 是一個通用 SQL 查詢引擎，基於 SQLite 打造，讓開發者和 AI 代理能對 40 多種資料來源（包括 GitHub、Notion、Chrome 瀏覽資料和 Apple Notes）執行標準 SQL 查詢。此技能的核心亮點在於其 Model Context Protocol (MCP) 伺服器支援，這使得相容的 AI 代理（如 Claude Code）能夠直接透過 MCP 協議連接到 Anyquery，進而存取跨服務的結構化資料。安裝方式極為簡便，在 macOS 上可透過 Homebrew (`brew install anyquery`) 一鍵完成。無論是查詢本機檔案、外部資料庫，還是第三方 SaaS 服務，Anyquery 都能將它們統一為 SQL 資料表。對於 AI 代理使用者而言，這項技能提供了一種標準化的方法，讓 AI 能即時查詢、分析與彙整來自不同平台的資料，大幅擴展了代理的資料處理能力。
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/anyquery-universal-sql-engine-mcp-integrationAnyquery 是一個 SQL 查詢引擎，讓你能對 40 多種應用程式、檔案和資料庫執行 SQL，包括 GitHub、Notion、Chrome 和 Apple Notes。它建構於 SQLite 之上，並支援 MCP 伺服器，可將 AI 代理連接到跨服務的結構化資料。
請使用符合您環境的上游安裝或設定路徑：
基本使用或入門須知：
LLM 可以使用模型上下文協議 (MCP) 與 Anyquery 連接。此協議為支援它的 LLM 提供上下文。您可以啟動 MCP 伺服器，方法如下...
從上游文件提取：https://raw.githubusercontent.com/julien040/anyquery/HEAD/README.md
This repo contains 20 individual skills — each has its own dedicated page.
Builds citation networks from Semantic Scholar API and CrossRef DOI metadata. Visualizes paper influence graphs using NetworkX, identifies seminal works, and tracks research lineage across fields.
Exposes Advanced Custom Fields data through the WordPress REST API using register_rest_field and acf_format_value. Handles repeater fields, flexible content layouts, and gallery fields with proper serialization.
An ASE skill built around ACF Extended, the WordPress enhancement suite for Advanced Custom Fields that adds field types, admin improvements, front-end forms, options pages, and developer tooling. It is a practical fit for agents working inside complex WordPress content models and custom field workflows.
Converts Advanced Custom Fields field groups into native Gutenberg blocks using the ACF Block API v2 and @wordpress/scripts build pipeline. Maps ACF repeaters, groups, and flexible content to InnerBlocks and block attributes with server-side rendering via acf_register_block_type().
Activepieces is an open-source, self-hostable workflow automation platform with 200+ integrations. It provides a visual builder for creating automated workflows and exposes all its connectors as MCP servers for AI agent use.
ActivityWatch is a privacy-first, open-source automated time tracker that records application usage, browser activity, and AFK status across Windows, macOS, and Linux. With 16k+ GitHub stars, it provides detailed productivity analytics without sending data to external servers.
act is an open-source CLI tool that runs GitHub Actions workflows locally using Docker, enabling fast feedback on workflow changes without pushing to GitHub. It is a standard tool for local Actions development and testing.
Use AgentClick when an agent should pause before risky commands, plans, drafts, or code changes so a human can inspect, edit, approve, or reject them in a purpose-built browser UI.
Use UX/UI Agent Skills when Claude should generate tokens, component specs, accessibility audits, and framework-specific UI code from a repeatable design workflow.
Use Bats-core when an agent needs to turn fragile shell scripts or command-line workflows into something it can verify repeatedly after edits. The agent writes focused Bash tests for success paths, failure paths, and output contracts, then runs them locally or in CI before a refactor, release, or incident fix goes out.
Use Cognee to ingest project knowledge into graph and vector memory so agents can retrieve durable context across sessions and workflows.
Give a coding agent symbol-aware lookup, cross-file rename, and structural edit tools before it starts making brittle text-only changes.
Give LangGraph agents memory management and search tools so they can store, retrieve, and update durable facts across sessions.
Use SimpleMem to store, compress, index, and retrieve text or multimodal memories for agents through MCP or Python integrations.
Keep Claude Code sessions grounded in prior decisions, project context, and daily handoff notes instead of starting from zero every time.
Store embeddings beside application data in Postgres, create vector indexes, and query nearest neighbors for semantic search, RAG, recommendations, or agent memory retrieval.
Find the open PR for the current branch, gather unresolved review comments, and drive a focused comment-resolution workflow with gh-authenticated context.
Use VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.
Use Zep as an external context layer for agents that need to store events, assemble temporal graph context, and retrieve relevant memory before model calls.
Calls Adobe Firefly
Extract frames or short clips from videos using ffmpeg.
Summarize or transcribe URLs, YouTube/videos, podcasts, articles, transcripts, PDFs, and local files.
Use when testing, fixing, or extending the OpenClaw Control UI GUI with Vitest + Playwright end-to-end checks, mocked Gateway WebSocket flows, mocked dashboard runs, screenshots/videos, or agent-verifiable browser proof.
Obra superpowers agent skills.
See, Understand, Act on video and audio. See- ingest from local files, URLs, RTSP/live feeds, or live record desktop; return realtime context and playable stream links. Understand- extract frames, build visual/semantic/temporal indexes, and search moments with timestamps and auto-clips. Act- transcode and normalize (codec, fps, resolution, aspect ratio), perform timeline edits (subtitles, text/image overlays, branding, audio overlays, dubbing, translation), generate media assets (image, audio...
End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.