How does this skill handle large datasets?

The skill encourages cost-effective patterns such as using schema queries before full analysis and caching results to minimize database load.

Does this skill support write operations like insert or delete?

No, this skill is configured for read-only access to ensure data safety and prevent accidental modifications to your databases.

What configuration is required to use this MongoDB skill?

You must set the MONGODB_URI environment variable in your shell with a valid connection string (mongodb://...) before activation.

Can Claude analyze complex database schemas with this tool?

Yes, by using the get_collection_schema tool, Claude can understand the structure of your documents to help you write better queries.

MongoDB Explorer & Query Tool

Name: MongoDB Explorer & Query Tool
Author: Microck

byMicrock

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Gestión de Bases de Datos

Enables read-only exploration, schema inspection, and data retrieval from MongoDB databases via MCP integration.

Acerca de

This skill integrates MongoDB MCP capabilities into Claude, allowing developers to interact with NoSQL databases directly through a secure, read-only interface. It streamlines development workflows by providing specialized tools to list databases, inspect collection schemas, and perform data analysis without switching contexts. It is ideal for debugging, verifying data structures, and understanding complex document relationships during the development lifecycle while maintaining database integrity through its query-only configuration.

Características Principales

Automated database and collection discovery
Support for complex aggregation pipelines
81 GitHub stars
Deep schema inspection for document structures
Performance-optimized local result caching
Read-only data querying and retrieval

Casos de Uso

Generating schema documentation for existing MongoDB collections
Verifying data structures and field types before writing application logic
Performing rapid data analysis and record searching for debugging purposes

Acerca de

Características Principales

Automated database and collection discovery
Support for complex aggregation pipelines
81 GitHub stars
Deep schema inspection for document structures
Performance-optimized local result caching
Read-only data querying and retrieval

Casos de Uso

Generating schema documentation for existing MongoDB collections
Verifying data structures and field types before writing application logic
Performing rapid data analysis and record searching for debugging purposes