Neo4j Long-Term Memory MCP Server

An MCP server that provides persistent cross-session memory and a knowledge graph (GraphRAG) backed by Neo4j.

Features

Memory Store

• Store, search, and recall text memories with semantic similarity via vector indexes
• Tagging, category filtering, importance ranking
• Deduplication by embedding similarity

Knowledge Graph

• Typed entity nodes: Person, Organization, Technology, Concept, Event, Location, Metric
• Typed relationships: CAUSES, ENABLES, PREVENTS, REQUIRES, USES, PRODUCES, COMPETES_WITH, etc.
• Claim tracking with confidence scoring and status (supported/disputed/unverified/retracted)
• Document management with provenance tracking
• Community detection and summarization
• Contradiction detection between relationships
• Hierarchy support (IS_A edges)
• Path finding and common neighbor discovery
• Confidence decay and graph pruning
• Session-level diffs

Prerequisites

• Python 3.10+
• Neo4j 5.11+ (required for vector index support)

Configuration

Env Variable	Default	Description
HOST_PORT	4398	MCP server port
HOST_ADDRESS	0.0.0.0	MCP server bind address
NEO4J_URI	bolt://localhost:7687	Neo4j connection URI
NEO4J_USER	neo4j	Neo4j username
NEO4J_PASSWORD	research_pass	Neo4j password
NEO4J_DATABASE	neo4j	Neo4j database name
EMBEDDING_DIMENSIONS	384	Vector embedding dimensions

MCP Tools

All public methods from AsyncLongTermMemory and KnowledgeGraph are exposed as MCP tools:

Memory

Tool	Description
memory_store	Store a new memory
memory_find_similar	Find semantically similar memories
memory_recall	Recall memories with filters
memory_stats	Get graph element counts

Entities

Tool	Description
graph_upsert_entity	Insert or update a typed entity
graph_find_entities	Semantic entity search

Relationships

Tool	Description
graph_store_relationship	Store a typed relationship
graph_get_relationships	Multi-hop relationship traversal
graph_store_hierarchy	Create IS_A edge
graph_store_contradiction	Flag conflicting relationships
graph_find_contradictions	Find contradiction edges

Claims

Tool	Description
graph_store_claim	Store a claim with entity links
graph_find_claims	Semantic claim search
graph_update_claim_status	Change claim status

Documents

Tool	Description
graph_store_document	Store/update a document node
graph_find_documents	Semantic document search
graph_link_document_to_entity	Link document to entity
graph_get_provenance	Get source documents for entities

Communities

Tool	Description
graph_get_communities	Get community summaries

Recency

Tool	Description
graph_recent_entities	Recently confirmed entities
graph_recent_relationships	Recently created/confirmed edges
graph_session_diff	Changes from a specific session

Graph Analysis

Tool	Description
graph_find_paths	Shortest path between entities
graph_find_common_neighbors	Entities connected to N named entities
graph_recall_context	Build structured context from graph

Maintenance

Tool	Description
graph_decay_confidence	Exponentially decay edge confidence
graph_prune	Remove stale/low-confidence elements

Running

# Install dependencies
pip install -r requirements.txt

# Start the MCP server
python server.py

Project Structure

├── server.py                     # MCP server entry point with tool wrappers
├── tools/
│   └── long_term_memory.py       # Async Neo4j-backed memory + knowledge graph
├── requirements.txt
├── Makefile
└── README.md