Datapizza
Server MCP per interrogare la documentazione di datapizza-ai realizzato con datapizza-ai
What is Datapizza?
Datapizza is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to server mcp per interrogare la documentazione di datapizza-ai realizzato con datapizza-ai
Server MCP per interrogare la documentazione di datapizza-ai realizzato con datapizza-ai
This server falls under the Data Science & ML category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Server MCP per interrogare la documentazione di datapizza-ai
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx datapizzaConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
How to Set Up and Use Datapizza
The DataPizza MCP server enables AI assistants to search and query the DataPizza AI community's documentation using natural language, leveraging a vector-based semantic search backend built with Qdrant and OpenAI embeddings. It exposes a single primary tool for documentation queries and a status resource endpoint, making it easy to retrieve contextually relevant documentation sections without manual browsing. Developers and data scientists working with the DataPizza AI platform use this server to quickly find answers, tutorials, and references from the official documentation through their AI workflow.
Prerequisites
- Python 3.9+ with pip installed
- An OpenAI API key (OPENAI_API_KEY) for generating embeddings
- A Qdrant instance with URL and API key (QDRANT_URL and QDRANT_API_KEY) — either self-hosted or Qdrant Cloud
- Git to clone the repository
- An MCP client such as Claude Desktop or Claude Code
Clone the repository
Clone the DataPizza MCP server repository to your local machine.
git clone https://github.com/mat1312/mcp-server-datapizza.git
cd mcp-server-datapizzaInstall dependencies
Install the server and its development dependencies using pip.
pip install -e ".[dev]"Configure environment variables
Set the required environment variables for OpenAI embeddings and your Qdrant vector database instance.
export OPENAI_API_KEY=your-openai-api-key
export QDRANT_URL=https://your-qdrant-instance.qdrant.io
export QDRANT_API_KEY=your-qdrant-api-keyStart the server
Launch the DataPizza MCP server. It will connect to Qdrant and be ready to handle documentation queries.
python -m datapizza_mcp.serverConfigure your MCP client
Add the server to your Claude Desktop or other MCP client configuration, providing all required environment variables.
Datapizza Examples
Client configuration
Claude Desktop configuration for the DataPizza MCP server with all required environment variables.
{
"mcpServers": {
"datapizza": {
"command": "python",
"args": ["-m", "datapizza_mcp.server"],
"cwd": "/path/to/mcp-server-datapizza",
"env": {
"OPENAI_API_KEY": "your-openai-api-key",
"QDRANT_URL": "https://your-qdrant-instance.qdrant.io",
"QDRANT_API_KEY": "your-qdrant-api-key",
"COLLECTION_NAME": "datapizza_docs",
"MAX_RESULTS": "5"
}
}
}
}Prompts to try
Example prompts for querying DataPizza AI documentation through Claude.
- "How do I create an AI agent with DataPizza?"
- "What are the available models on the DataPizza platform?"
- "Show me how to use the DataPizza API for text generation"
- "What are the rate limits and pricing for DataPizza AI?"
- "How do I integrate DataPizza with my Python application?"Troubleshooting Datapizza
Qdrant connection error on startup
Verify QDRANT_URL is the correct endpoint for your Qdrant instance (e.g. https://your-cluster.qdrant.io for Qdrant Cloud) and that QDRANT_API_KEY is valid. Test connectivity by accessing the Qdrant dashboard URL in your browser.
OpenAI embedding errors
Confirm your OPENAI_API_KEY is valid and has sufficient credits. The server uses the text-embedding-3-small model by default. If you want to use a different model, set the EMBEDDING_MODEL environment variable.
Query returns empty or irrelevant results
Verify the Qdrant collection specified by COLLECTION_NAME (default: datapizza_docs) exists and has documents indexed. Check the datapizza://status resource endpoint by asking Claude to show the server status to confirm the collection size and configuration.
Frequently Asked Questions about Datapizza
What is Datapizza?
Datapizza is a Model Context Protocol (MCP) server that server mcp per interrogare la documentazione di datapizza-ai realizzato con datapizza-ai It connects AI assistants to external tools and data sources through a standardized interface.
How do I install Datapizza?
Follow the installation instructions on the Datapizza GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with Datapizza?
Datapizza works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is Datapizza free to use?
Yes, Datapizza is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Set Up Datapizza in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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