About
Neo4j Agent Memory gives AI assistants persistent, graph-based memory using Neo4j. Store information as interconnected nodes — people, places, organizations, projects, events — and create meaningful relationships between them with semantic predicates like KNOWS, WORKS_AT, CREATED, or MANAGES. Key features: - Store facts as labeled nodes with flexible schemas and custom properties - Build directional relationships with optional metadata (e.g., "since: 2023") - Search memory content with word-tokenized matching (querying "John Smith" finds "John" OR "Smith") - Traverse connections up to 3 levels deep to surface related information - Filter and retrieve memories by creation date with automatic timestamp tracking - Connect to any Neo4j instance including Neo4j Enterprise Edition with multi-database support - 10 specialized tools for CRUD operations and intelligent graph exploration without embedding complex logic in the tools themselves
README
[](https://smithery.ai/server/@knowall-ai/mcp-neo4j-agent-memory)
Neo4j Agent Memory MCP Server
A specialized MCP server that bridges Neo4j graph database with AI agents, providing memory-focused tools for storing, recalling, and connecting information in a knowledge graph.
Quick Start 🚀
You can run this MCP server directly using npx:
npx @knowall-ai/mcp-neo4j-agent-memory
Or add it to your Claude Desktop configuration:
{
"mcpServers": {
"neo4j-memory": {
"command": "npx",
"args": ["@knowall-ai/mcp-neo4j-agent-memory"],
"env": {
"NEO4J_URI": "bolt://localhost:7687",
"NEO4J_USERNAME": "neo4j",
"NEO4J_PASSWORD": "your-password",
"NEO4J_DATABASE": "neo4j"
}
}
}
}
Features
Philosophy: LLM-Driven Intelligence
Unlike traditional approaches that embed complex logic in tools, this server provides simple, atomic operations and lets the LLM handle all the intelligence:
Search Behavior
Thesearch_memories tool uses word tokenization:
This approach makes the system more powerful and adaptable, as improvements in LLM capabilities directly translate to better memory management.
Neo4j Enterprise Support
This server now supports connecting to specific databases in Neo4j Enterprise Edition. By default, it connects to the "neo4j" database, but you can specify a different database using the NEO4J_DATABASE environment variable.
Memory Tools
search_memories: Search and retrieve memories from the knowledge graphsince_date parameter (ISO format)
- Control relationship depth and result limits
- Sort by any field (created_at, name, etc.)create_memory: Create a new memory in the knowledge graphcreate_connection: Create relationships between memoriesupdate_memory: Update properties of existing memoriesupdate_connection: Update relationship propertiesdelete_memory: Remove memories and all their connectionsdelete_connection: Remove specific relationshipslist_memory_labels: List all unique memory labels in useget_guidance: Get help on using the memory tools effectivelyPrerequisites
1. Neo4j Database (v4.4+ or v5.x) - Install Neo4j Community or En
Related MCP Servers
AI Research Assistant
hamid-vakilzadeh
AI Research Assistant provides comprehensive access to millions of academic papers through the Semantic Scholar and arXiv databases. This MCP server enables AI coding assistants to perform intelligent literature searches, citation network analysis, and paper content extraction without requiring an API key. Key features include: - Advanced paper search with multi-filter support by year ranges, citation thresholds, field of study, and publication type - Title matching with confidence scoring for finding specific papers - Batch operations supporting up to 500 papers per request - Citation analysis and network exploration for understanding research relationships - Full-text PDF extraction from arXiv and Wiley open-access content (Wiley TDM token required for institutional access) - Rate limits of 100 requests per 5 minutes with options to request higher limits through Semantic Scholar
Linkup
LinkupPlatform
Linkup is a real-time web search and content extraction service that enables AI assistants to search the web and retrieve information from trusted sources. It provides source-backed answers with citations, making it ideal for fact-checking, news gathering, and research tasks. Key features of Linkup: - Real-time web search using natural language queries to find current information, news, and data - Page fetching to extract and read content from any webpage URL - Search depth modes: Standard for direct-answer queries and Deep for complex research across multiple sources - Source-backed results with citations and context from relevant, trustworthy websites - JavaScript rendering support for accessing dynamic content on JavaScript-heavy pages
Math-MCP
EthanHenrickson
Math-MCP is a computation server that enables Large Language Models (LLMs) to perform accurate numerical calculations through the Model Context Protocol. It provides precise mathematical operations via a simple API to overcome LLM limitations in arithmetic and statistical reasoning. Key features of Math-MCP: - Basic arithmetic operations: addition, subtraction, multiplication, division, modulo, and bulk summation - Statistical analysis functions: mean, median, mode, minimum, and maximum calculations - Rounding utilities: floor, ceiling, and nearest integer rounding - Trigonometric functions: sine, cosine, tangent, and their inverses with degrees and radians conversion support