"Dgraph" matching MCP servers:

An improved implementation of persistent memory using a local knowledge graph with a customizable --memory-path. This lets Claude remember information about the user across chats.

Self-hosted personal knowledge graph for Claude that persists across sessions, devices, and tools. Built on Neo4j with local semantic embeddings; OAuth 2.1 lets Claude Code, Claude Desktop, and claude.ai web all hit the same graph.

A self-contained, in-memory graph database for AI Agents. Provides semantic code understanding through the Model Context Protocol (MCP).

Enables agents to build and query structured semantic graphs, extracting, traversing and multi-hop reasoning over entity-relation-object triples while producing Cypher and JSON-LD graph output. It also combines BM25 lexical and dense vector retrieval with rank fusion, semantic caching and context reordering for grounded agentic memory.

Enables extraction of subject-predicate-object triples from text and multi-hop reasoning over connected data, producing Cypher and JSON-LD outputs for agent memory, vector search, and retrieval-augmented generation workflows.

Remote MCP server grounding GTM agents in governed, cited company truth, enabling AI agents to use verified context, search, validate content, and generate grounded drafts.

Enables AI agents to navigate, search, and rank notes in an Obsidian vault using graph relationships, providing context-aware access to knowledge without exposing raw file contents.

A knowledge graph MCP server providing persistent, structured memory for AI assistants with multi-agent isolation, tiered search, and index navigation.

Provides AI coding agents with a local knowledge-graph memory, enabling cross-project retrieval via PageRank diffusion and tools to retrieve, write, extract, update, and view recent knowledge over MCP.

An MCP server that gives your agent a persistent project brain: vision, architecture decisions, conventions, roadmaps, and automatic session handoff.

A local-first Graph-RAG system that combines ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q\&A over your Obsidian vault.

Provides a decision memory layer for codebases, enabling AI agents to search, retrieve, and record business decisions with metadata filters and full-text search.

Enables agents to ground claims in enterprise knowledge by hashing source chunks, tracing claims back to their origins, validating clearance boundaries, and maintaining audit trails to support anti-hallucination workflows.

Connects to an embedded Kuzu graph database and provides read-only MCP tools for AI clients to query a knowledge graph.

A high-performance code knowledge graph server implementing MCP, indexing codebases into a structured AST knowledge graph with semantic search, call graph traversal, and HTTP route tracing.

Enables fast, targeted queries against an Obsidian vault knowledge graph using tools like search, neighbor traversal, and pathfinding, without needing to load the full graph into LLM context.

Enables personal AI agents to fuse ambient multimodal perception with continuous episodic memory streams, routing routine reflexive actions at low latency while reserving heavier reasoning for ambiguous plans. Memory records apply Ebbinghaus recency decay with contradiction resolution and user-controlled deletion.

Enables semantic search of the KJV Bible and personal knowledge graph for scripture study, notes, prayers, and memory verses, all running locally with no cloud dependencies.

Enables persistent, intelligent memory across sessions using a weighted, interconnected graph that evolves through conversation.

Enables MCP clients such as Claude Desktop, Cursor, Zed, and Windsurf to recall associative context from a folder of markdown notes, combining vector search entry points with one-hop [[wikilink]] graph expansion and cross-encoder reranking over a single SQLite file. It also appends a zero-token per-turn ledger of asks, files, tools, and decisions that agents can consult across sessions.