Frequently Asked Questions about MCP Server

Q: What is MCP Server?

A: MCP Server is a RAG (Retrieval-Augmented Generation) implementation using GroundX and OpenAI, built with Modern Context Processing (MCP) to enhance how AI models interact with external data.

Q: What are the prerequisites for using MCP Server?

A: You need Python 3.12 or higher, OpenAI API key, GroundX API key, and MCP CLI tools.

Q: How do I install MCP Server?

A: Clone the repository, create a virtual environment, and install the dependencies using uv sync.

Q: How do I configure MCP Server?

A: Copy .env.example to .env and configure your environment variables such as GROUNDX_API_KEY, OPENAI_API_KEY, and BUCKET_ID.

Q: How do I start the MCP Server?

A: Run the inspect server using the command: mcp dev server.py.

Q: How do I ingest documents into MCP Server?

A: Use the ingest_documents function in server.py with the path to your document. For example:

python from server import ingest_documents result = ingest_documents(“path/to/your/document.pdf”) print(result)

Q: How do I perform searches using MCP Server?

A: Use the process_search_query function in server.py with your search query. For example:

python from server import process_search_query response = process_search_query(“your search query here”) print(f"Query: {response.query}“) print(f"Score: {response.score}”) print(f"Result: {response.result}")

Q: Can I customize the search configuration?

A: Yes, you can customize the search configuration using the SearchConfig class. For example:

python from server import process_search_query, SearchConfig

config = SearchConfig( completion_model=“gpt-4”, bucket_id=“custom-bucket-id” ) response = process_search_query(“your query”, config)

Q: What are the main dependencies of MCP Server?

A: The main dependencies are groundx (≥2.3.0), openai (≥1.75.0), mcp[cli] (≥1.6.0), and ipykernel (≥6.29.5).

Q: How can I contribute to MCP Server?

A: Fork the repository, create a feature branch, commit your changes, push to the branch, and open a pull request.

Q: What security measures should I take when using MCP Server?

A: Never commit your .env file containing API keys, use environment variables for sensitive information, regularly rotate your API keys, and monitor API usage for any unauthorized access.

Q: How does UBOS relate to MCP Server?

A: UBOS is a Full-stack AI Agent Development Platform, and MCP Server is an asset available on the UBOS marketplace. UBOS helps orchestrate AI Agents, connect them with enterprise data, and build custom AI Agents with your LLM model and Multi-Agent Systems.