Exposes a provenance-aware knowledge graph to AI agents over MCP, providing tools like get_fact and search_documents that return precise answers with source citations.
Exposes a Neo4j knowledge-graph index over personal markdown notes to LLM agents via MCP, enabling semantic search, tag navigation, and relationship discovery.
Builds a persistent knowledge graph from notes and conversations, enabling semantic search, entity exploration, and GTD task management from any MCP-compatible AI assistant.
An in-memory knowledge graph MCP server that gives coding agents structural and semantic recall over codebases by indexing Python source, ADR documents, and project configuration, exposing 7 tools for search, traversal, context retrieval, and natural-language Q&A.
Enables fully local retrieval over a personal document corpus via hybrid search, cross-encoder reranking, RAPTOR summaries, and knowledge graph queries, served to AI agents over MCP.