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Analytics Engineering

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> [!info] What it does > Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Fr...

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  • Added September 12, 2026
ai-agentspythongoawsapidocumentation

Works with

  • claude code
  • claude desktop
  • cursor
  • cli
  • api
  • mcp

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Scanned September 12, 2026

npx -y skills add stanfish06/skillquarium --skill analytics-engineering --agent claude-code

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SKILL.md
---
title: neo4j-agent-memory-skill
aliases:
  - neo4j agent memory skill
  - NAMS
tags:
  - skill
  - domain/analytics-engineering
domain: analytics-engineering
status: untried
source: skills/neo4j-agent-memory-skill/SKILL.md
created: 2026-08-23
---

# neo4j-agent-memory-skill

> [!info] What it does
> Authoritative reference for the neo4j-agent-memory Python package — a graph-native memory system for AI agents built on Neo4j — and for the hosted service (NAMS) at memory.neo4jlabs.com. Use this skill whenever the user mentions neo4j-agent-memory, agent memory with Neo4j, context graphs, the POLE+O model, MemoryClient/MemorySettings, the memory MCP server, or any of the framework integrations (LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents, LlamaIndex). Also use when the user mentions the hosted service at memory.neo4jlabs.com, NAMS, the Neo4j Agent Memory Service, the `nams_` API key prefix, or the hosted MCP endpoint. Also use when writing documentation, blog posts, tutorials, PRDs, or code samples for the project, when comparing agent memory approaches, or when positioning graph-native memory against vector-only approaches — even if the user doesn't explicitly name the package.

**Source:** [skills/neo4j-agent-memory-skill/SKILL.md](../../../skills/neo4j-agent-memory-skill/SKILL.md)  ·  **Domain:** [Analytics Engineering & LLM Operations](../../maps/analytics-engineering.md)  ·  **Table:** [skills.base](../../skills.base)  ·  **Index:** [Skills Index](../../index.md)

## Related skills

- [crewai](../../notes/ml-ai/crewai.md) — Role-based multi-agent orchestration framework for building "Crews" of collaborating LLM agents (each with a role, goal, backstory, and optional tools) that execute sequential or...
- [neo4j-graphrag-skill](../../notes/analytics-engineering/neo4j-graphrag-skill.md) — Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (v1.16.0+)
- [neo4j-mcp-skill](../../notes/analytics-engineering/neo4j-mcp-skill.md) — Use when installing, configuring, or troubleshooting the official Neo4j MCP server (neo4j/mcp) — connecting Claude Code, Claude Desktop, Cursor, Windsurf, VS Code, Kiro, or other...

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## Notes

Files in this skill

  • adding-dbt-unit-test.md1 KB
  • answering-natural-language-questions-with-dbt.md1.2 KB
  • building-dbt-semantic-layer.md1.2 KB
  • chdb-datastore.md1.6 KB
  • chdb-sql.md1.7 KB
  • clickhouse-architecture-advisor.md1.1 KB
  • clickhouse-best-practices.md1.2 KB
  • clickhouse-js-node-coding.md1.2 KB
  • clickhouse-js-node-rowbinary.md1.1 KB
  • clickhouse-js-node-troubleshooting.md1.5 KB
  • clickhouse-managed-postgres-rca.md1.3 KB
  • clickstack-otel-collector.md1.5 KB
  • configuring-dbt-mcp-server.md1 KB
  • creating-mermaid-dbt-dag.md985 B
  • dagster-expert.md1.2 KB
  • databricks-agent-bricks.md974 B
  • databricks-ai-functions.md1.1 KB
  • databricks-aibi-dashboards.md1.4 KB
  • databricks-app-design.md2.1 KB
  • databricks-apps-python.md2.4 KB

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