mongodb

Quick overview of a MongoDB database - list collections, document counts, and sample schemas. For deep exploration with relationship mapping and recommendations, use the db-explorer agent instead

Export data from a MongoDB collection to a file.

Import data from a JSON or CSV file into a MongoDB collection.

Execute a MongoDB query against the connected database.

Check MongoDB connection status and database info

Deep autonomous database explorer that thoroughly documents a MongoDB database: discovers collections, infers schemas, maps cross-collection relationships, and generates a full report with recommendations. Use when the user wants comprehensive database documentation — not just a quick overview (use the /explore command for that). <example>explore my mongodb database</example> <example>document the schema of all collections</example> <example>what collections exist and how are they related?</example>

Helps plan and execute MongoDB schema migrations, data transformations, and collection restructuring. Use when the user needs to change their data model, migrate data between collections, or transform existing documents. <example>rename the 'userName' field to 'username' across all documents</example> <example>migrate embedded customer data to a separate collection</example> <example>add a default status field to all orders</example>

Interactive MongoDB query optimizer that takes a specific slow query, runs explain plans, diagnoses the root cause, recommends a fix, and verifies the improvement with before/after metrics. Use when the user has a concrete query to optimize — for general indexing strategy and best practices reference, the performance-advisor skill is more appropriate. <example>why is this MongoDB query slow?</example> <example>recommend indexes for my collection</example> <example>analyze the explain plan for this aggregation</example>

Build and optimize MongoDB queries, aggregation pipelines, and CRUD operations. Use when the user asks to query data, filter documents, join collections, aggregate results, update documents, or work with MongoDB data in any way.

Reference guide for MongoDB performance patterns: index strategies (ESR rule, compound, partial, TTL), explain plan interpretation, and performance checklists. Use as background knowledge when advising on indexing or performance. For hands-on optimization of a specific slow query, trigger the query-advisor agent instead.

Analyze MongoDB collection schemas, infer data types, detect inconsistencies, and recommend schema design improvements. Use when the user asks about database structure, data modeling, schema validation, or wants to understand their MongoDB collections.

3 hooks across 3 events