# Neo4j Agent Memory Server

> Use this tool when you need to build and query complex knowledge graphs that capture relationships between entities, enabling AI assistants to provide more intelligent and contextual responses. It solves problems of data connectivity and context, allowing for efficient storage and searching of interconnected information. With features like node-based storage, semantic relationships, and word-tokenized search, it provides a flexible and powerful interface for creating and querying persistent knowledge graphs.

Canonical page: https://skillsregistry.net/skills/knowall-ai-mcp-neo4j-agent-memory  
JSON: https://api.skillsregistry.net/v1/skills/knowall-ai-mcp-neo4j-agent-memory

## Description

Neo4j Agent Memory enables AI assistants to build and query persistent knowledge graphs. Store information as nodes, create meaningful relationships between them, and search across your connected data. Unlike simple key-value stores, this graph-based approach captures how information relates, providing rich context for more intelligent responses.

### Key Features:
* **Store facts as nodes** - people, places, organizations, projects, events
* **Connect with semantic relationships** - KNOWS, WORKS_AT, CREATED, MANAGES
* **Word-tokenized search** - finds "John" OR "Smith" when searching "John Smith"
* **Date filtering** - find memories created after specific dates
* **Multi-hop traversal** - explore connections up to 3 levels deep
* **Automatic timestamps** - track when memories were created
* **Flexible schema** - use any label or property you need
* **Relationship properties** - add context like "since: 2023" to connections
* **10 specialized tools** - search, create, update, delete memories and connections
* **LLM-friendly design** - simple atomic operations, AI handles the intelligence

Build persistent, queryable knowledge graphs that grow smarter over time.

## Trust

- **Trust score (0–1):** 0.80
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/knowall-ai/mcp-neo4j-agent-memory)
- **Repository:** <https://github.com/knowall-ai/mcp-neo4j-agent-memory>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "knowall-ai-mcp-neo4j-agent-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/knowall-ai-mcp-neo4j-agent-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/knowall-ai-mcp-neo4j-agent-memory/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt