mongo-mcp
MongodbMcpLlmJavascriptTypescriptNode.jsCloudPythonGoRubyR
Server Information
š Overview:
ā Key Points:
šÆ Conclusion:
The "mongo-mcp" repository offers a solution for integrating LLMs with MongoDB, streamlining database interactions through natural language. The provided documentation and sample prompts enable developers to quickly set up and test the solution for their applications.
This report summarizes the content of a GitHub webpage for the "mongo-mcp" repository owned by QuantGeekDev. The repository hosts a MongoDB server implementation designed for the Model Context Protocol (MCP), enabling Large Language Models (LLMs) to interact with MongoDB databases for data querying, schema inspection, and data management via natural language.
ā Key Points:
- The project implements a MongoDB server for MCP.
- It allows LLMs to interact with MongoDB databases.
- The system supports collection schema inspection.
- The system supports document querying and filtering.
- The system supports document operations (insert, update, delete).
- The system supports index management.
- The project is licensed under the MIT License.
- It is installable via Smithery.
- It includes a demo video and example prompts for users.
- The "mongo-mcp" repository provides a MongoDB server tailored for interaction with LLMs through the MCP.
- The system's main goal is to facilitate database operations using natural language processing.
- Technologies used: Node.js 18+
- Installation: Can be installed manually or via Smithery. Smithery one-liner `npx -y @smithery/cli install mongo-mcp --client claude`
- Local Test Sandbox configuration and setup is provided including a sample `docker-compose.yml` file and seed script.
- Sample prompts are included for showcasing querying tools, index tools and document operations.
- Available Query tools: `find`, `listCollections`, `insertOne`, `updateOne`, `deleteOne`.
- Available Index Tools: `createIndex`, `dropIndex`, `indexes`.
š Main Findings:
š Details:
šÆ Conclusion:
The "mongo-mcp" repository offers a solution for integrating LLMs with MongoDB, streamlining database interactions through natural language. The provided documentation and sample prompts enable developers to quickly set up and test the solution for their applications.
Server Features
Collection schema inspection
Collection schema inspection
Document querying and filtering
Document querying and filtering
Index management
Index management
Document operations
Document operations (insert, update, delete)
Provider Information
Quantgeekdev
cloud Provider
Quick Actions
MCP Configuration
Available Tools
findlistCollectionsinsertOneupdateOnedeleteOnecreateIndexdropIndexindexes