mongodb-mcp-setup은(는) 무엇을 하나요?
사용자가 MongoDB MCP 서버의 주요 설정 옵션을 구성할 수 있도록 안내합니다. 이 스킬은 사용자가 MongoDB MCP 서버를 설치했지만 필요한 환경 변수를 구성하지 않았거나, MongoDB/Atlas 연결에 대해 문의하면서 자격 증명이 설정되지 않은 경우에 사용합니다.
MongoDB MCP 서버의 주요 설정 옵션을 안내합니다. 사용자가 MongoDB MCP 서버를 설치했지만 필요한 환경 변수를 구성하지 않았거나, MongoDB/Atlas 연결에 대해 문의하면서 자격 증명이 설정되지 않은 경우 이 스킬을 사용하세요.
이 스킬은 MongoDB MCP 서버를 구성하는 과정을 사용자에게 안내합니다. 주로 환경 변수(예: MONGODB_URI)가 설정되지 않은 경우, 또는 MongoDB Atlas 연결에 필요한 자격 증명을 요청하는 상황에서 사용됩니다. Claude Code, Cursor, Codex 등 다양한 AI 에이전트 플랫폼에서 이 스킬을 호출하여 MongoDB MCP 서버의 설치 확인, 연결 문자열 생성, 환경 변수 설정 방법 등을 단계별로 안내합니다. 이 스킬은 SKILL.md 파일에 정의된 설정 지침을 기반으로 사용자가 MongoDB 데이터베이스에 연결하고 상호작용할 수 있도록 돕는 것을 목표로 합니다.
npx skills add https://github.com/mongodb/agent-skills/tree/main/skills/mongodb-mcp-setupInstalled? Explore more 생산성 & 협업 skills: steipete/gemini, steipete/gh-issues, steipete/skill-creator · View all 6 →
사용자가 MongoDB MCP 서버의 주요 설정 옵션을 구성할 수 있도록 안내합니다. 이 스킬은 사용자가 MongoDB MCP 서버를 설치했지만 필요한 환경 변수를 구성하지 않았거나, MongoDB/Atlas 연결에 대해 문의하면서 자격 증명이 설정되지 않은 경우에 사용합니다.
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.