Agent SDK and Runtime · Public

agent-memory

Agent SDK project for checking tool calls, state, handoffs, traces, evaluation, and permission boundaries.

Agent SDKTool callsHandoffsTracingEvaluation boundaries

Best fitDevelopers building observable, testable, multi-tool agent applications.

Check whether this project matches your task before installing it.

What it can doAgent runtime preflights, tool permissions, state/handoff boundaries, trace acceptance, and evaluation checks

Review the portable capability path.

Before continuingVerify in a sandbox

Do not treat a preview pack as a proven local install.

GitHub snapshot332 stars

74 forks · 10 contributors

Doramagic.ai Last verification date: 2026-06-21 Verification method: source evidence, semantic profile, public page gate, and static build acceptance.

Official first step Read manual preview Source repository

Publication status · 2026-06-21

What is agent-memory?

agent-memory is an Agent SDK or runtime for tool calls, state, handoffs, tracing, and evaluation boundaries.
Best fit: Developers building observable, testable, multi-tool agent applications.
Not for: Not for one prompt, simple API calls, or environments that cannot isolate tool permissions.
Capability added to an AI workflow: Agent runtime preflights, tool permissions, state/handoff boundaries, trace acceptance, and evaluation checks
First safe verification step: Verify one minimal agent loop with fake tools and temporary credentials first.
Verification state: source, Quick Start, and sandbox install checks are recorded as passed.
Top risk: May increase setup, validation, or first-run risk for the user.
Evidence base: https://github.com/neo4j-labs/agent-memory, https://github.com/neo4j-labs/agent-memory#readme, Human Manual, Pitfall Log

Quick decision

Use this section to decide whether the project is worth a deeper read.

Best forDevelopers building observable, testable, multi-tool agent applications.

Match the project to your task before installing it.

CapabilityAgent runtime preflights, tool permissions, state/handoff boundaries, trace acceptance, and evaluation checks

Agent SDK project for checking tool calls, state, handoffs, traces, evaluation, and permission boundaries.

Repositoryneo4j-labs/agent-memory

332 stars · 74 forks

What it can do

Translate the upstream project into concrete capabilities the user can judge before installing.

Overview and System Architecture

Related topics: SDK Usage and Memory Operations, Extraction, Enrichment, and Entity Resolution

Source: https://github.com/neo4j-labs/agent-memory / Human Manual

SDK Usage and Memory Operations

Related topics: Overview and System Architecture, MCP Server, Framework Integrations, CLI, and Deployment

Source: https://github.com/neo4j-labs/agent-memory / Human Manual

Extraction, Enrichment, and Entity Resolution

Related topics: Overview and System Architecture, SDK Usage and Memory Operations

Source: https://github.com/neo4j-labs/agent-memory / Human Manual

MCP Server, Framework Integrations, CLI, and Deployment

Related topics: Overview and System Architecture, SDK Usage and Memory Operations

Source: https://github.com/neo4j-labs/agent-memory / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

Sources: https://github.com/neo4j-labs/agent-memory, Human Manual, Project Pack evidence, and downstream validation signals.

Community Discussion Evidence

Project-level external discussion stays visible on the detail page, not only inside the manual.

Stars332 stars

Forks74 forks

Contributors10 contributors

Licenseunknown

Community Discussion Evidence

12 source-linked items

Review these external discussions before using agent-memory with real data or production workflows. They are review inputs, not standalone proof that the project is production-ready.

01
[TypeScript SDK] EntityTypeDef.poleType typed as string — invalid values
github / github_issue
02
false acks
github / github_issue
03
Build #42's decay as re-ranking over a bitemporal, invalidate-not-delete
github / github_issue
04
Support memory decay in memory search retrievers
github / github_issue
05
Long-term recall is not isolation-enforced per user (Entity/Fact are glo
github / github_issue
06
[Bug/Integration] `Neo4jMemoryService` (Google ADK) is incompatible with
github / github_issue
07
If short-term memory is processed multiple times, Message-to-Entity link
github / github_issue
08
[Python SDK] NamsConfig requires endpoint with /v1 suffix — quick-start
github / github_issue
09
[Python SDK] record_tool_call() and get_session_traces() crash with Vali
github / github_issue
10
[TypeScript + Python SDK] Methods unavailable on hosted service throw No
github / github_issue
11
[TypeScript SDK] searchMessages — sessionId typed as optional but requir
github / github_issue
12
[TypeScript SDK] getEntity throws TransportError instead of NotFoundErro
github / github_issue

How to start

Only source-backed commands are shown here. Verify them in an isolated environment first.

Try the prompt first

Test the workflow without installing the upstream project.

preview

Read the Human Manual

Understand inputs, outputs, limits, and failure modes.

manual

Take context to your AI host

Use the compiled assets in your preferred AI environment.

context

Run sandbox verification

Confirm install commands and rollback before using a primary environment.

verify

pip install neo4j-agent-memory

Official start command · https://github.com/neo4j-labs/agent-memory#readme · verified: yes

Human Manual

The English page must expose the real manual, not a short placeholder.

8+ sections · Human Manual

agent-memory Manual

A graph-native memory system for AI agents and context graphs. Store conversations, build knowledge graphs, and let your agents learn from their own reasoning\u2009—\u2009all backed by Neo4j.

Open the full manual

https://github.com/neo4j-labs/agent-memory Project Manual
Table of Contents
Overview and System Architecture
Related Pages
Purpose and Scope
High-Level Architecture
Memory Tiers and Data Model
Backend Selection and the NAMS Release

Overview and System Architecture

Related topics: SDK Usage and Memory Operations, Extraction, Enrichment, and Entity Resolution

Source: https://github.com/neo4j-labs/agent-memory / Human Manual

SDK Usage and Memory Operations

Related topics: Overview and System Architecture, MCP Server, Framework Integrations, CLI, and Deployment

Source: https://github.com/neo4j-labs/agent-memory / Human Manual

Extraction, Enrichment, and Entity Resolution

Related topics: Overview and System Architecture, SDK Usage and Memory Operations

Source: https://github.com/neo4j-labs/agent-memory / Human Manual

MCP Server, Framework Integrations, CLI, and Deployment

Related topics: Overview and System Architecture, SDK Usage and Memory Operations

Source: https://github.com/neo4j-labs/agent-memory / Human Manual

Doramagic Pitfall Log

Source-linked risks stay visible on the manual page so the preview does not read like a recommendation.

Source: Doramagic discovery, validation, and Project Pack records

AI Context Pack and portable assets

After deciding to continue, take the project context into your own AI host.

Complete pack plus user-owned assets

These files are planning and verification assets for Claude Code, Codex, Gemini, Cursor, ChatGPT, and other AI hosts.

Download complete pack Read Human Manual

BundleComplete Project Pack AssetAI Context Pack AssetBoundary & Risk Card AssetHuman Manual AssetPitfall Log AssetPrompt Preview AssetQuick Start EvidenceREPO_INSPECTION.json

Preflight checks

Treat this page as a planning asset, not proof that your local environment is ready.

The manual is generated from source-linked project files and Doramagic validation signals.
Community evidence warnings stay visible instead of being converted into marketing claims.
This English page is indexable because the locale quality gate passed and explicit English index approval is enabled.
Use the upstream repository as the final authority for installation commands, license, and version-specific behavior.