Are There Open-Source AI Agents for AI Agent Deployment and Memory? (2
Yes. As of Aug 8, 2026, out of 194 AI agents for agent deployment and memory in the KanonAgent index, 50 are judged open-source (every judgement requires a source quote); this page covers the top 8 by real traction.
Yes—8 open-source agents in the index directly support building, deploying, and running stateful AI agents with memory. Open-source here means code-first toolkits and frameworks that avoid vendor lock-in while providing long-term context handling and orchestration layers.
Updated 2026-08-08 · 8 products · live data from KanonAgent
1. ai-memory66 upvotes
ai-memory supplies long-term memory and seamless handoff between AI coding agents so context survives vendor switches.
2. sim20 upvotes
sim acts as the central layer to build, deploy, and orchestrate fleets of AI agents across tasks.
3. letta24.1k upvotes
letta provides a platform for stateful agents that retain memory, learn, and self-improve over long-running jobs.
4. adk-python21.0k upvotes
adk-python is Google's open-source Python toolkit for code-first building, evaluation, and deployment of agents.
5. Upsonic7.9k upvotes
Upsonic delivers a full-stack Python framework for rapid autonomous agent development and deployment.
6. ag24.8k upvotes
ag2 (AutoGen) offers an open-source AgentOS for building collaborative, scalable multi-agent systems.
7. agents-cli2.3k upvotes
agents-cli turns coding assistants into experts at building, evaluating, and deploying agents on Google Cloud.
8. phantom1.5k upvotes
phantom runs as an AI co-worker with persistent memory and secure credential handling for ongoing tasks.
How to choose
Prioritize letta or ai-memory when long-term context retention across sessions is the bottleneck. Choose adk-python, ag2, or agents-cli when you need production-grade deployment pipelines and evaluation tooling. Watch for hidden operational costs around memory storage and orchestration scale; most are free but require self-hosted infrastructure. Avoid near-miss agents that only add generic tools without addressing deployment or memory continuity.
What the data says
Computed from our index over the 8 products on this page; judgement fields are left blank where we cannot read them (methodology).
AutonomyL3 × 1 · L2 × 3 (4/8 judged)
Prerequisitesopen source × 8 · self-hostable × 4
Common integrationsSlack × 4 · MCP (Model Context Protocol) × 2
In the index since2026-07-13 — 2026-07-25
Ranked by real traction from our index — not editorial picks, and no paid placement. Every judgement field requires a source quote; where we cannot read it, we leave it blank. Full criteria, thresholds and known limits: methodology.
FAQ
Which ones emphasize memory persistence over pure deployment?
letta, ai-memory, and phantom focus most directly on stateful memory and context handoff.
Are any of these production-ready without extra hosting?
adk-python, ag2, and Upsonic are code-first and run locally or on your own infrastructure; sim and agents-cli target cloud deployment.
How do I avoid context bloat when scaling these?
Ratel and letta explicitly manage tool access and memory to prevent token overload during long deployments.