mongodb-mcp-setup 是做什麼的？
引導使用者設定關鍵的 MongoDB MCP 伺服器選項。當使用者已安裝 MongoDB MCP 伺服器但尚未設定必要的環境變數，或他們詢問如何連接到 MongoDB/Atlas 但尚未設定憑證時，請使用此技能。
引導使用者設定關鍵的 MongoDB MCP 伺服器選項。當使用者已安裝 MongoDB MCP 伺服器但尚未設定必要的環境變數，或他們詢問如何連接到 MongoDB/Atlas 但尚未設定憑證時，請使用此技能。
此技能旨在協助使用者設定 MongoDB MCP 伺服器的必要環境變數，以建立與 MongoDB 或 MongoDB Atlas 的連線。當使用者已安裝伺服器但缺少連線憑證時，此技能會提供逐步引導，包括設定諸如 `MONGODB_URI` 等環境變數。這對於使用 Cursor、Claude Code 或 Codex 等 AI 代理工具的開發者特別有幫助，因為這些工具需要正確的憑證才能與 MongoDB 資料庫互動。透過自動化設定過程，此技能可減少手動配置錯誤，並確保 MCP 伺服器能順利與 MongoDB 服務連接，從而加速開發工作流程。
npx skills add https://github.com/mongodb/agent-skills/tree/main/skills/mongodb-mcp-setupInstalled? Explore more 生產力與協作 skills: steipete/gemini, steipete/gh-issues, steipete/skill-creator · View all 6 →
引導使用者設定關鍵的 MongoDB MCP 伺服器選項。當使用者已安裝 MongoDB MCP 伺服器但尚未設定必要的環境變數，或他們詢問如何連接到 MongoDB/Atlas 但尚未設定憑證時，請使用此技能。
This repo contains 5 individual skills — each has its own dedicated page.
Optimize MongoDB client connection configuration (pools, timeouts, patterns) for any supported driver language. Use this skill when working/updating/reviewing on functions that instantiate or configure a MongoDB client (eg, when calling `connect()`), configuring connection pools, troubleshooting connection errors (ECONNREFUSED, timeouts, pool exhaustion), optimizing performance issues related to connections. This includes scenarios like building serverless functions with MongoDB, creating API endpoints that use MongoDB, optimizing high-traffic MongoDB applications, creating long-running tasks and concurrency, or debugging connection-related failures.
Generate read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.
Help with MongoDB query optimization and indexing. Use only when the user asks for optimization or performance: "How do I optimize this query?", "How do I index this?", "Why is this query slow?", "Can you fix my slow queries?", "What are the slow queries on my cluster?", etc. Do not invoke for general MongoDB query writing unless user asks for performance or index help. Prefer indexing as optimization strategy. Use MongoDB MCP when available.
MongoDB schema design patterns and anti-patterns. Use when designing data models, reviewing schemas, migrating from SQL, or troubleshooting performance issues caused by schema problems. Triggers on "design schema", "embed vs reference", "MongoDB data model", "schema review", "unbounded arrays", "one-to-many", "tree structure", "16MB limit", "schema validation", "JSON Schema", "time series", "schema migration", "polymorphic", "TTL", "data lifecycle", "archive", "index explosion", "unnecessary indexes", "approximation pattern", "document versioning".
Guides MongoDB users through implementing and optimizing Atlas Search (full-text), Vector Search (semantic), and Hybrid Search solutions. Use this skill when users need to build search functionality for text-based queries (autocomplete, fuzzy matching, faceted search), semantic similarity (embeddings, RAG applications), or combined approaches. Also use when users need text containment, substring matching ('contains', 'includes', 'appears in'), case-insensitive or multi-field text search, or filtering across many fields with variable combinations. Provides workflows for selecting the right search type, creating indexes, constructing queries, and optimizing performance using the MongoDB MCP server.
Gemini CLI one-shot prompts, summaries, generation, skills, hooks, MCP, or Gemma routing.
Fetch GitHub issues, select candidates, spawn background fix agents, open PRs, and optionally process PR review comments.
Create, edit, audit, tidy, validate, or restructure AgentSkills and SKILL.md files.
Search, install, update, sync, or publish agent skills with the ClawHub CLI and registry.
Delegate coding work to Codex, Claude Code, or OpenCode as background workers; not simple edits or read-only code lookup.
List, configure, authenticate, call, and inspect MCP servers/tools with mcporter over HTTP or stdio.