MongoDB Operations Service – FAQ | MCP Marketplace

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Frequently Asked Questions about MongoDB MCP for UBOS

Q: What is MongoDB MCP?

A: MongoDB MCP (Machine Chat Protocol) is a service that allows Large Language Models (LLMs) to interact with MongoDB databases through standard CRUD operations and administrative tasks. It acts as a bridge between AI Agents and your MongoDB data.

Q: What are the requirements to use MongoDB MCP?

A: You need Python 3.10 or above, a running MongoDB database service, and it is recommended to use uv to run the program.

Q: What kind of operations are supported by MongoDB MCP?

A: MongoDB MCP supports listing all databases, listing collections in a database, inserting documents, querying documents with conditions and projections, updating documents (single and bulk), and deleting documents (single and bulk).

Q: How do I configure MongoDB MCP with Cursor?

A: You can add a configuration to your .cursor/mcp.json file, specifying the command, arguments, and environment variables (like MONGODB_URI, MONGODB_DEFAULT_DB, and LOG_LEVEL).

Q: What environment variables can I configure?

A: You can configure MONGODB_URI (MongoDB connection string), MONGODB_DEFAULT_DB (default database name), and LOG_LEVEL (logging level: DEBUG, INFO, WARNING, ERROR, CRITICAL).

Q: How do I run the MongoDB MCP server?

A: You can run the server directly with uvx run mongo-mcp. It uses the stdio transport method, making it suitable for integration with MCP clients that support this transport method.

Q: Where are log files stored?

A: Log files are stored in the logs directory by default. The log level can be controlled through the LOG_LEVEL environment variable.

Q: What is UBOS, and how does MongoDB MCP integrate with it?

A: UBOS is a full-stack AI Agent Development Platform focused on bringing AI Agents to every business department. MongoDB MCP integrates seamlessly, allowing AI Agents within the UBOS platform to access and interact with MongoDB databases.

Q: Can I contribute to the MongoDB MCP project?

A: Yes, contributions via Issues and Pull Requests are welcome. Ensure all tests pass, appropriate test cases are added, and documentation is updated before submitting a PR.

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