mcp-ragdocs
MCP-Ragdocs is a server that facilitates semantic search through documentation using a vector database like Qdrant. It supports adding and querying documents using natural language, providing flexibility and ease of retrieval from various documentation sources.
What is the purpose of MCP-Ragdocs?
MCP-Ragdocs is designed to facilitate semantic search and retrieval of documentation using a vector database, making it easier to manage and search through large sets of documentation.
What are the system requirements for MCP-Ragdocs?
You need Node.js 16 or higher, Qdrant (local or cloud), and an embedding provider like Ollama or OpenAI.
How do I add documentation to MCP-Ragdocs?
You can add documentation from URLs or local files using the 'add_documentation' tool.
Can I use MCP-Ragdocs with Qdrant Cloud?
Yes, MCP-Ragdocs can be configured to work with Qdrant Cloud by setting the appropriate environment variables.
What embedding providers are supported?
MCP-Ragdocs supports Ollama and OpenAI as embedding providers.