oracle-mcp-server
The MCP Oracle DB Context server is designed to enhance AI assistants' interactions with large Oracle databases by efficiently managing and presenting schema information. Its standout features include intelligent caching, targeted schema lookup, and seamless integration with tools like GitHub Copilot. The server supports advanced Oracle database features through both thin and thick connection modes.
What is the purpose of the MCP Oracle DB Context server?
It provides AI models with accurate and relevant database schema information from large Oracle databases, enabling efficient schema lookups and understanding of table relationships.
How does the server handle large databases?
It uses smart schema caching to minimize database queries and efficiently manage schema information.
What are the system requirements for running the server?
Requires Python 3.12 or higher, 4GB+ RAM, 500MB disk space, and a stable connection to an Oracle database server.
Can the server be used with AI assistants?
Yes, it integrates with AI assistants like GitHub Copilot in VSCode, Claude, and ChatGPT that support MCP.
What is the difference between thin and thick mode?
Thin mode is a pure Python implementation, easier to set up, while thick mode offers advanced features and better performance, requiring Oracle Client libraries.