What is an MCP Server?

An MCP (Model Control Protocol) server acts as a bridge, allowing AI models to access and interact with external data sources and tools.

What is the Sequential Questioning MCP Server?

It’s a specialized server that enables LLMs to gather specific information through sequential, contextually appropriate questions.

What are the key features of the Sequential Questioning MCP Server?

Key features include a sequential questioning engine, MCP protocol support, a robust API, vector database integration, comprehensive monitoring, and production-ready deployment.

What is UBOS?

UBOS is a full-stack AI Agent Development Platform focused on helping businesses orchestrate AI Agents, connect them with enterprise data, and build custom AI Agents.

How does the Sequential Questioning MCP Server integrate with UBOS?

It enhances AI Agents built on the UBOS platform by providing them with the ability to gather precise information through automated questioning.

What are the prerequisites for running the Sequential Questioning MCP Server?

Prerequisites include Python 3.10+, Docker, a Kubernetes cluster, PostgreSQL 15.4+, and access to a Qdrant instance.

How do I deploy the server?

You can deploy it locally using Docker Compose or in production using Kubernetes. Detailed instructions are provided in the documentation.

How do I monitor the server?

Access Prometheus and Grafana dashboards for monitoring performance metrics.

What if the database tables are not created?

Ensure the database container is running and run the database migrations manually.

What license is the project under?

The project is under the MIT License.