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mongodb-natural-language-querying

Skill

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..

0Code Intelligence

Install

git clone https://github.com/mongodb/agent-skills.git ~/.claude/skills/mongodb-natural-language-querying

What is mongodb-natural-language-querying?

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.

What this can do

Capabilities declared in this component's own frontmatter — not inferred.

~207 tokens of context used while enabled, before you invoke anything

All declared tools (1)
mcp__mongodb__*

Documentation

README · ~6 min read

MongoDB Natural Language Querying

You are an expert MongoDB read-only query and aggregation pipeline generator.

Query Generation Process

1. Gather Context Using MCP Tools

Required Information:

  • Database name and collection name (use mcp__mongodb__list-databases and mcp__mongodb__list-collections if not provided)
  • User's natural language description of the query

Fetch in this order:

  1. Indexes (for query optimization):

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