MongoDB Lens

MongoDB Lens is a local Model Context Protocol (MCP) server with full featured access to MongoDB databases using natural language via LLMs to perform queries, run aggregations, optimize performance, and more.

Contents

• Quick Start
• Features
• Installation
• Configuration
• Client Setup
• Tutorial
• Disclaimer

Quick Start

• Clone repository
• Install dependencies
• Configure MongoDB Lens
• Set up your MCP Client (e.g. Claude Desktop)
• Start exploring your MongoDB databases with natural language queries

Features

• Tools
• Resources
• Prompts
• Performance Features

Tools

• aggregate-data: Execute aggregation pipelines (with streaming support for large result sets)
• analyze-query-patterns: Analyze queries and suggest optimizations
• analyze-schema: Automatically infer collection schemas
• bulk-operations: Perform multiple operations efficiently
• collation-query: Find documents with language-specific collation rules
• compare-schemas: Compare schemas between two collections
• count-documents: Count documents matching specified criteria
• create-collection: Create new collections with custom options
• create-index: Create new indexes for performance optimization
• create-timeseries: Create time series collections for temporal data
• current-database: Show the current database context
• distinct-values: Extract unique values for any field
• drop-collection: Remove collections from the database
• explain-query: Analyze query execution plans
• export-data: Export query results in JSON or CSV format
• find-documents: Run queries with filters, projections, and sorting (with streaming for large result sets)
• generate-schema-validator: Generate JSON Schema validators
• geo-query: Perform geospatial queries with various operators
• get-stats: Retrieve database or collection statistics
• gridfs-operation: Manage large files with GridFS buckets
• list-collections: Explore collections in the current database
• list-databases: View all accessible MongoDB databases
• map-reduce: Run MapReduce operations for complex data processing
• modify-document: Insert, update, or delete specific documents
• rename-collection: Rename existing collections
• shard-status: View sharding configuration for databases and collections
• text-search: Perform full-text search across text-indexed fields
• transaction: Execute multiple operations in a single ACID transaction
• use-database: Switch to a specific database context
• validate-collection: Check for data inconsistencies
• watch-changes: Monitor real-time changes to collections

Resources

• collection-indexes: Index information for a collection
• collection-schema: Schema information for a collection
• collection-stats: Performance statistics for a collection
• collection-validation: Validation rules for a collection
• collections: List of collections in the current database
• database-triggers: Database change streams and event triggers configuration
• database-users: Database users and roles in the current database
• databases: List of all accessible databases
• performance-metrics: Real-time performance metrics and profiling data
• replica-status: Replica set status and configuration
• server-status: Server status information
• stored-functions: Stored JavaScript functions in the current database

Prompts

• aggregation-builder: Step-by-step creation of aggregation pipelines
• backup-strategy: Customized backup and recovery recommendations
• data-modeling: Expert advice on MongoDB schema design for specific use cases
• database-health-check: Comprehensive database health assessment and recommendations
• index-recommendation: Get personalized index suggestions based on query patterns
• inspector-guide: Get help using MongoDB Lens with MCP Inspector
• migration-guide: Step-by-step MongoDB version migration plans
• mongo-shell: Generate MongoDB shell commands with explanations
• multi-tenant-design: Design MongoDB multi-tenant database architecture
• query-builder: Interactive guidance for constructing MongoDB queries
• query-optimizer: Optimization recommendations for slow queries
• schema-analysis: Detailed collection schema analysis with recommendations
• schema-versioning: Manage schema evolution in MongoDB applications
• security-audit: Database security analysis and improvement recommendations
• sql-to-mongodb: Convert SQL queries to MongoDB aggregation pipelines

Performance Features

• Sanitized Inputs: Security enhancements for query processing
• Connection Resilience: Automatic reconnection with exponential backoff
• Configuration File: Custom configuration via ~/.mongodb-lens.json
• JSONRPC Error Handling: Comprehensive error handling with proper error codes
• Memory Management: Automatic memory monitoring and cleanup for large operations
• Smart Caching: Enhanced caching for schemas, collection lists, and server status
• Streaming Support: Stream large result sets for find-documents and aggregate-data operations

Installation

MongoDB Lens can be installed and run in several ways:

• NPX (Easiest)
• Docker Hub
• Node.js from Source
• Docker from Source
• Installation Verification

Installation: NPX

The easiest way to run MongoDB Lens is using npx without installing anything:

# Using default connection string mongodb://localhost:27017
npx -y mongodb-lens

# Using custom connection string
npx -y mongodb-lens mongodb://your-connection-string

[!TIP]<br> If you encounter permissions errors with npx, try running npx clear-npx-cache prior to running npx -y mongodb-lens (this clears the cache and re-downloads the package).

Installation: Docker Hub

Run MongoDB Lens directly from Docker Hub without building:

# Using default connection string mongodb://localhost:27017
docker run --rm -i --network=host furey/mongodb-lens

# Using "--pull" to keep the Docker image up-to-date
docker run --rm -i --network=host --pull=always furey/mongodb-lens

# Using custom connection string
docker run --rm -i --network=host furey/mongodb-lens mongodb://your-connection-string

Installation: Node.js from Source

1. Navigate to the cloned repository directory:<br>

   cd /path/to/mongodb-lens
   

2. Ensure Node running (suggestion: use Volta):<br> $ node -v >= 22.*
3. Install Node.js dependencies:<br>

   npm ci
   

4. Start the server:<br>

   # Using default connection string mongodb://localhost:27017
   node mongodb-lens.js
   
   # Using custom connection string
   node mongodb-lens.js mongodb://your-connection-string
   

Installation: Docker from Source

1. Navigate to the cloned repository directory:<br>

   cd /path/to/mongodb-lens
   

2. Build the Docker image:<br>

   docker build -t mongodb-lens .
   

3. Run the container:<br>

   # Using default connection string mongodb://localhost:27017
   docker run --rm -i --network=host mongodb-lens
   
   # Using custom connection string
   docker run --rm -i --network=host mongodb-lens mongodb://your-connection-string
   

Installation Verification

To verify the installation, paste and run the following jsonrpc message into the server's stdio:

{"method":"resources/read","params":{"uri":"mongodb://databases"},"jsonrpc":"2.0","id":1}

The server should respond with a list of databases in your MongoDB instance, for example:

{"result":{"contents":[{"uri":"mongodb://databases","text":"Databases (12):\n- admin (180.00 KB)\n- config (108.00 KB)\n- local (40.00 KB)\n- sample_airbnb (51.88 MB)\n- sample_analytics (9.46 MB)\n- sample_geospatial (980.00 KB)\n- sample_guides (40.00 KB)\n- sample_mflix (108.90 MB)\n- sample_restaurants (7.73 MB)\n- sample_supplies (968.00 KB)\n- sample_training (40.85 MB)\n- sample_weatherdata (2.69 MB)"}]},"jsonrpc":"2.0","id":1}

MongoDB Lens is now installed and ready to accept MCP requests.

Shut down the server by sending a SIGINT signal (<kbd>Ctrl</kbd>+<kbd>C</kbd>).

Configuration

• MongoDB Connection String
• Verbose Logging
• Config File

Configuration: MongoDB Connection String

The server accepts a MongoDB connection string as its only argument.

Example NPX usage:

npx -y mongodb-lens mongodb://your-connection-string

MongoDB connection strings have the following format:

mongodb://[username:password@]host[:port][/database][?options]

Example connection strings:

• Local connection:<br> mongodb://localhost:27017
• Connection to mydatabase with credentials from admin database:<br> mongodb://username:password@hostname:27017/mydatabase?authSource=admin
• Connection to mydatabase with various other options:<br> mongodb://hostname:27017/mydatabase?retryWrites=true&w=majority

If no connection string is provided, the server will attempt to connect via local connection.

Configuration: Verbose Logging

To enable verbose logging, set environment variable VERBOSE_LOGGING to true.

Example NPX usage:

VERBOSE_LOGGING=true npx -y mongodb-lens mongodb://your-connection-string

Example Docker Hub usage:

docker run --rm -i --network=host -e VERBOSE_LOGGING='true' furey/mongodb-lens mongodb://your-connection-string

With verbose logging enabled, the server will output additional information to the console.

Configuration: Config File

MongoDB Lens can also be configured via JSON config file: ~/.mongodb-lens.json

Alternatively, set environment variable CONFIG_PATH to the path of your custom config file.

Example NPX usage:

CONFIG_PATH='/path/to/config.json' npx -y mongodb-lens

Example Docker Hub usage:

docker run --rm -i --network=host -v /path/to/config.json:/root/.mongodb-lens.json furey/mongodb-lens

Example configuration file contents:

{
  "mongoUri": "mongodb://username:password@hostname:27017/mydatabase?authSource=admin",
  "connectionOptions": {
    "maxPoolSize": 20,
    "connectTimeoutMS": 30000
  }
}

Client Setup

• Claude Desktop
• MCP Inspector
• Other MCP Clients

Client Setup: Claude Desktop

To use MongoDB Lens with Claude Desktop:

1. Install Claude Desktop
2. Open claude_desktop_config.json (create it if it doesn't exist):
   • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
   • Windows: %APPDATA%\Claude\claude_desktop_config.json
3. Add the MongoDB Lens server configuration as per configuration options
4. Restart Claude Desktop
5. Start a conversation with Claude about your MongoDB data

Claude Desktop Configuration Options

• Option 1: NPX (Recommended)
• Option 2: Docker Hub Image
• Option 3: Local Node.js Installation
• Option 4: Local Docker Image

For each option:

• Replace mongodb://your-connection-string with your MongoDB connection string or omit it to use the default mongodb://localhost:27017.
• Set VERBOSE_LOGGING to true or false.
• To use a custom config file, see Configuration: Config File and adapt option accordingly.

Option 1: NPX (Recommended)

{
  "mcpServers": {
    "mongodb-lens": {
      "command": "/path/to/npx",
      "args": [
        "-y",
        "mongodb-lens",
        "mongodb://your-connection-string"
      ],
      "env": {
        "VERBOSE_LOGGING": "[true|false]"
      }
    }
  }
}

Option 2: Docker Hub Image

{
  "mcpServers": {
    "mongodb-lens": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "--network=host",
        "--pull=always",
        "-e",
        "VERBOSE_LOGGING=[true|false]",
        "furey/mongodb-lens",
        "mongodb://your-connection-string"
      ]
    }
  }
}

Option 3: Local Node.js Installation

{
  "mcpServers": {
    "mongodb-lens": {
      "command": "/path/to/node",
      "args": [
        "/path/to/mongodb-lens.js",
        "mongodb://your-connection-string"
      ],
      "env": {
        "VERBOSE_LOGGING": "[true|false]"
      }
    }
  }
}

Option 4: Local Docker Image

{
  "mcpServers": {
    "mongodb-lens": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "--network=host",
        "-e",
        "VERBOSE_LOGGING=[true|false]",
        "mongodb-lens",
        "mongodb://your-connection-string"
      ]
    }
  }
}

Client Setup: MCP Inspector

MCP Inspector is a tool designed for testing and debugging MCP servers.

Example Node.js from source usage:

1. Navigate to the cloned repository directory:<br>

   cd /path/to/mongodb-lens
   

2. Run Inspector via npx:<br>

   npx -y @modelcontextprotocol/inspector node mongodb-lens.js mongodb://your-connection-string
   

3. Inspector starts a proxy server (default port: 3000) and web app (default port: 5173)
   • To change the default ports:<br>

     CLIENT_PORT=8080 SERVER_PORT=9000 npx -y @modelcontextprotocol/inspector node mongodb-lens.js
     

4. Open Inspector web app: http://localhost:5173
5. Inspector should support the full range of MongoDB Lens capabilities, including autocompletion for collection names and query fields.

For more, see: MCP Inspector

Client Setup: Other MCP Clients

MongoDB Lens should be usable with any MCP-compatible client.

For more, see: MCP Documentation: Example Clients

Tutorial

This following tutorial guides you through setting up a MongoDB container with sample data, then using MongoDB Lens to interact with it through natural language queries:

1. Start Sample Data Container
2. Import Sample Data
3. Connect MongoDB Lens
4. Example Queries

Tutorial: 1. Start Sample Data Container

[!NOTE]<br> This tutorial assumes you have Docker installed and running on your system.

[!IMPORTANT]<br> If Docker is already running a container on port 27017, stop it before proceeding.

1. Initialise sample data container:<br>

   docker run --name mongodb-sampledata -d -p 27017:27017 mongo:6
   

2. Verify the container is running without issue:<br>

   docker ps | grep mongodb-sampledata
   

Tutorial: 2. Import Sample Data

MongoDB provides several sample datasets, which we'll use to explore MongoDB Lens.

1. Download the sample datasets:

   curl -LO https://atlas-education.s3.amazonaws.com/sampledata.archive
   

2. Copy the sample datasets into your sample data container:<br>

   docker cp sampledata.archive mongodb-sampledata:/tmp/
   

3. Restore the sample data into MongoDB:<br>

   docker exec -it mongodb-sampledata mongorestore --archive=/tmp/sampledata.archive
   

This will import several databases:

• sample_airbnb: Airbnb listings and reviews
• sample_analytics: Customer and account data
• sample_geospatial: Geographic data
• sample_mflix: Movie data
• sample_restaurants: Restaurant data
• sample_supplies: Supply chain data
• sample_training: Training data for various applications
• sample_weatherdata: Weather measurements

Tutorial: 3. Connect MongoDB Lens

Download and install MongoDB Lens as per the Quick Start instructions.

Set your MCP Client to connect to MongoDB Lens via: mongodb://localhost:27017

[!TIP]<br> Omitting the connection string from your MCP Client configuration will default the connection string to mongodb://localhost:27017.

Example Claude Desktop configuration:

{
  "mcpServers": {
    "mongodb-lens": {
      "command": "/path/to/npx",
      "args": [
        "-y",
        "mongodb-lens"
      ]
    }
  }
}

Tutorial: 4. Example Queries

With your MCP Client running and connected to MongoDB Lens, try these example queries that demonstrate the capabilities of the various tools, resources, and prompts available through MongoDB Lens:

• Example Queries: Basic Database Operations
• Example Queries: Movie Data Analysis
• Example Queries: Airbnb Data Exploration
• Example Queries: Weather Data Operations
• Example Queries: Geospatial Operations
• Example Queries: Time Series & Change Streams
• Example Queries: Bulk Operations & Data Modeling
• Example Queries: Administrative Operations
• Example Queries: Advanced Features

Example Queries: Basic Database Operations

• "List all available databases"<br> ^{➥ Uses list-databases tool}
• "What's the current database I'm connected to?"<br> ^{➥ Uses current-database tool}
• "Switch to the sample_mflix database"<br> ^{➥ Uses use-database tool}
• "What collections are available in this database?"<br> ^{➥ Uses list-collections tool}
• "Get statistics for the sample_mflix database"<br> ^{➥ Uses get-stats tool with database target}
• "Create the temp_collection collection, then drop it"<br> ^{➥ Uses create-collection & drop-collection tool}

Example Queries: Movie Data Analysis

• "Count how many movies are in the movies collection"<br> ^{➥ Uses count-documents tool}
• "Find the top 5 movies by IMDB rating with a runtime over 120 minutes"<br> ^{➥ Uses find-documents tool with sort and filter}
• "What's the schema of the movies collection?"<br> ^{➥ Uses analyze-schema tool}
• "Find distinct countries where movies were produced"<br> ^{➥ Uses distinct-values tool}
• "Create an index on the title field in the movies collection"<br> ^{➥ Uses create-index tool}
• "Why is my query for movies with over 1000 votes slow? Help me optimize it"<br> ^{➥ Uses query-optimizer prompt}
• "Run an explain on the query {year: 1995}"<br> ^{➥ Uses explain-query tool}
• "Build an aggregation pipeline to show the count of movies by decade and genre"<br> ^{➥ Uses aggregation-builder prompt}
• "Execute this aggregation pipeline: [{$group: {_id: {$floor: {$divide: ['$year', 10]}}, count: {$sum: 1}}}]"<br> ^{➥ Uses aggregate-data tool}
• "Update all movies from 1994 to add a 'classic' field set to true"<br> ^{➥ Uses modify-document tool with update operation}

Example Queries: Airbnb Data Exploration

• "Switch to sample_airbnb database"<br> ^{➥ Uses use-database tool}
• "Get collection statistics for the listingsAndReviews collection"<br> ^{➥ Uses get-stats tool with collection target}
• "What's the validation rules for the listingsAndReviews collection?"<br> ^{➥ Uses collection-validation resource}
• "Show me the indexes on the listingsAndReviews collection"<br> ^{➥ Uses collection-indexes resource}
• "Find listings with more than 5 bedrooms in Manhattan, limited to 10 results"<br> ^{➥ Uses find-documents tool}
• "Get distinct property types in the listings"<br> ^{➥ Uses distinct-values tool}
• "Help me create a query filter to find superhosts with pool amenities"<br> ^{➥ Uses query-builder prompt}
• "Export the top 20 highest-rated listings in Brooklyn as CSV with name, price, and rating"<br> ^{➥ Uses export-data tool}
• "Is my schema optimized for querying by neighborhood? Analyze and give recommendations"<br> ^{➥ Uses schema-analysis prompt}
• "Rename the reviews collection to guest_reviews"<br> ^{➥ Uses rename-collection tool}

Example Queries: Weather Data Operations

• "Switch to sample_weatherdata database"<br> ^{➥ Uses use-database tool}
• "What's in the schema of the data collection?"<br> ^{➥ Uses collection-schema resource}
• "Find the highest recorded temperatures with a callLetters of 'SHIP'"<br> ^{➥ Uses find-documents tool}
• "Validate the data collection for inconsistencies"<br> ^{➥ Uses validate-collection tool}
• "Insert a new weather record for today"<br> ^{➥ Uses modify-document tool with insert operation}
• "Create a new collection called weather_summary"<br> ^{➥ Uses create-collection tool}
• "Create index recommendation for queries that filter by callLetters and sort by date"<br> ^{➥ Uses index-recommendation prompt}
• "Show me how to write a MapReduce operation to get average temperatures by day"<br> ^{➥ Uses mongo-shell prompt}
• "Run this MapReduce to calculate average pressure by location"<br> ^{➥ Uses map-reduce tool}
• "Delete all weather readings below -50 degrees"<br> ^{➥ Uses modify-document tool with delete operation}

Example Queries: Geospatial Operations

• "Switch to sample_geospatial database"<br> ^{➥ Uses use-database tool}
• "Find all shipwrecks within 5km of the coast of Florida"<br> ^{➥ Uses geo-query tool with near operator}
• "Show me restaurants that fall within the downtown Manhattan polygon"<br> ^{➥ Uses geo-query tool with geoWithin operator}
• "Which bike routes intersect with Central Park?"<br> ^{➥ Uses geo-query tool with geoIntersects operator}
• "Create a geospatial index on the location field of the neighborhoods collection"<br> ^{➥ Uses create-index tool with 2dsphere index type}
• "Analyze the schema of the shipwrecks collection to understand its geospatial data structure"<br> ^{➥ Uses analyze-schema tool}

Example Queries: Time Series & Change Streams

• "Create a new time series collection for sensor readings with 'timestamp' as the time field"<br> ^{➥ Uses create-timeseries tool}
• "Watch for changes in the orders collection for the next 30 seconds"<br> ^{➥ Uses watch-changes tool}
• "Monitor all insert operations on the users collection for 15 seconds"<br> ^{➥ Uses watch-changes tool with specific operations}
• "Create a time series collection for IoT device data with hourly granularity"<br> ^{➥ Uses create-timeseries tool with granularity option}
• "Create a time series collection that automatically deletes data older than 30 days"<br> ^{➥ Uses create-timeseries tool with expireAfterSeconds option}

Example Queries: Bulk Operations & Data Modeling

• "Switch to sample_training database"<br> ^{➥ Uses use-database tool}
• "Execute a bulk operation to update multiple post documents to add 'edited' flags"<br> ^{➥ Uses bulk-operations tool}
• "How should I model a social media application in MongoDB?"<br> ^{➥ Uses data-modeling prompt}
• "Perform a bulk insertion of new product records in the supplies database"<br> ^{➥ Uses bulk-operations tool}
• "Show me how to use MongoDB Lens with the MCP Inspector"<br> ^{➥ Uses inspector-guide prompt}
• "What's the optimal data model for a multi-tenant SaaS application with heavy analytical queries?"<br> ^{➥ Uses data-modeling prompt}

Example Queries: Administrative Operations

• "Switch to the admin database"<br> ^{➥ Uses use-database tool}
• "Show me the server status"<br> ^{➥ Uses server-status resource}
• "Display the replica set configuration"<br> ^{➥ Uses replica-status resource}
• "List all users in the database"<br> ^{➥ Uses database-users resource}
• "Get any stored JavaScript functions"<br> ^{➥ Uses stored-functions resource}
• "Perform a security audit on my MongoDB deployment"<br> ^{➥ Uses security-audit prompt}
• "What's a good backup strategy for my MongoDB instance?"<br> ^{➥ Uses backup-strategy prompt}
• "How would I migrate from MongoDB 4.4 to 6.0?"<br> ^{➥ Uses migration-guide prompt}

Example Queries: Schema Management & Analysis

• "Compare schemas between the users and customers collections"<br> ^{➥ Uses new compare-schemas tool to identify differences}
• "Generate a JSON Schema validator for the profiles collection with moderate strictness"<br> ^{➥ Uses new generate-schema-validator tool}
• "Analyze query patterns for the orders collection"<br> ^{➥ Uses new analyze-query-patterns tool}
• "What fields are missing in the new customers collection compared to the old one?"<br> ^{➥ Uses compare-schemas to analyze migration gaps}
• "Are my indexes being used effectively for my queries?"<br> ^{➥ Uses analyze-query-patterns to identify optimization opportunities}

Example Queries: Advanced Features

• "Switch to sample_mflix database"<br> ^{➥ Uses use-database tool}
• "Search for movies containing the phrase 'space odyssey' using text search"<br> ^{➥ Uses text-search tool}
• "Find users named 'müller' using German collation rules"<br> ^{➥ Uses collation-query tool}
• "List all files in the images GridFS bucket"<br> ^{➥ Uses gridfs-operation tool with list operation}
• "Get detailed information about the 'profile.jpg' file in GridFS"<br> ^{➥ Uses gridfs-operation tool with info operation}
• "Delete the 'old_backup.zip' file from the files GridFS bucket"<br> ^{➥ Uses gridfs-operation tool with delete operation}
• "Check the sharding status of the sample_analytics database"<br> ^{➥ Uses shard-status tool with database target}
• "View the sharding distribution for the customers collection"<br> ^{➥ Uses shard-status tool with collection target}
• "Execute a transaction that transfers $100 from account A to account B"<br> ^{➥ Uses transaction tool}
• "Get real-time performance metrics for my MongoDB server"<br> ^{➥ Uses performance-metrics resource}
• "Show me the current event triggers in my database"<br> ^{➥ Uses database-triggers resource}
• "Convert this SQL query to MongoDB: SELECT * FROM users WHERE age > 30 ORDER BY name"<br> ^{➥ Uses sql-to-mongodb prompt}
• "Perform a comprehensive health check on my database"<br> ^{➥ Uses database-health-check prompt}
• "Help me design a multi-tenant architecture for my SaaS application"<br> ^{➥ Uses multi-tenant-design prompt}
• "I need to add user address fields to my schema. How should I version and migrate?"<br> ^{➥ Uses schema-versioning prompt}

Disclaimer

MongoDB Lens:

• is licensed under the MIT License.
• is not affiliated with or endorsed by MongoDB, Inc.
• is written with the assistance of AI and may contain errors.
• is intended for educational and experimental purposes only.
• is provided as-is with no warranty or support—use at your own risk.