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neo4j-agent-memory-skill
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.
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You do not need every option. Choose the path your AI client supports. The stable page stays the same; versioned files are immutable.
1. Native installer
This listing has no registered native installer command. Use the complete package or source fallback below, depending on what your client supports.
Do not guess an installer command or replace an existing version without reviewing the diff.
2. Complete package recommended
Download the ZIP when available. It includes SKILL.md plus the references, security notes and version metadata.
No complete ProSkills package is published for this listing yet.3. Prompt-only
Copy the prompt above when the agent can read the stable page or when you want to adopt the workflow without installing a skill.
Need only the instruction file?
Download SKILL.md only if your client requires a single file. The complete ZIP is safer for a full installation because it preserves the references and release context.
No path installs or executes anything by itself. Your agent still needs access to the project files. Before updating, compare the installed version and review the diff.
// RATINGS
Not yet listed on ClawHub or SkillsMP
// README
neo4j-agent-memory-skill
Skill for building graph-native agent memory backed by Neo4j using the neo4j-agent-memory Python package and the hosted Neo4j Agent Memory Service (NAMS) at memory.neo4jlabs.com.
Covers:
MemoryClient/MemorySettings— core API for storing and retrieving memories- Short-term memory — conversation history stored as
:Messagenodes - Long-term memory — structured knowledge using the POLE+O entity model (Person, Object, Location, Event + Organisation)
- Reasoning traces — storing agent thought chains for auditability and re-use
- NAMS hosted service — API key setup (
nams_prefix), endpoints, rate limits - Memory MCP server — exposing memory as MCP tools for any MCP-compatible agent
- Framework integrations: LangChain, PydanticAI, CrewAI, AWS Strands, Google ADK, Microsoft Agent Framework, OpenAI Agents SDK, LlamaIndex
- Graph schema — memory graph structure, Cypher queries for inspection
- Comparing graph-native memory vs vector-only approaches
Version / compatibility:
neo4j-agent-memoryPython package (latest)- Neo4j 5.x / 2025.x or NAMS hosted service
Not covered:
- General Neo4j vector search →
neo4j-vector-index-skill - GraphRAG pipelines →
neo4j-graphrag-skill - MCP server setup (general) →
neo4j-mcp-skill
Install:
pip install neo4j-agent-memory
npx skills add https://github.com/neo4j-contrib/neo4j-skills --skill neo4j-agent-memory-skill
Or paste this link into your coding assistant: https://github.com/neo4j-contrib/neo4j-skills/tree/main/neo4j-agent-memory-skill
// HOW IT'S BUILT
KEY FILES