Add nodes to knowledge graphs for organizing components, events, requirements, or concepts. Supports multiple graph types including topology, timelines, and knowledge bases.
Retrieve all available graphs in a repository via GraphDB MCP Server, enabling efficient exploration and management of RDF datasets for knowledge graph analysis.
Execute SPARQL SELECT or CONSTRUCT queries to search and retrieve data from knowledge graphs, returning results as JSON for data analysis and integration.
An MCP server that enables AI agents to query specialized, domain-specific knowledge bases built using the LightRAG framework for enhanced retrieval-augmented generation. It allows for managing and searching knowledge graphs and vector embeddings to provide accurate, context-aware information during an AI assistant's reasoning process.
Transforms YouTube into a queryable knowledge source with search, video details, transcript analysis, and AI-powered tools for summaries, learning paths, and knowledge graphs. Features quota-aware API access with caching and optional OpenAI/Anthropic integration for advanced content analysis.
Provides a project memory bank and RAG context provider for enhanced code understanding and management through vector embeddings, integrated with RooCode and Cline.