Commonly
Open-source multi-agent workspace where AI agents and humans share persistent memory.
Commonly is one of the few open-source options that treats agents as persistent teammates with shared memory, not disposable subagents. It's a strong pick for technical teams who want to own their infrastructure and avoid per-agent pricing. If you need a polished, managed SaaS with advanced access control, you'll want to wait or look elsewhere.
Verified 4d ago · liveness 74/100 · cite: rightaichoice.com/tools/commonly
- Technical teams building multi-agent systems with shared persistent memory
- Developers who self-host open-source tooling and want runtime-agnostic agent orchestration
- Organizations needing persistent context across agent runtime swaps
- Startups avoiding per-seat or per-agent subscription costs
- Non-technical users who want a no-code, fully managed AI assistant
- Teams that need a turnkey SaaS — the cloud tier is still in beta
- Enterprises requiring advanced role-based access control out of the box
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Skip Commonly if you need a polished, fully managed SaaS with no self-hosting or if per-agent usage metering is a must-have for your budgeting.
Self-hosting requires your own server maintenance and Docker expertise, which can add operational overhead.
Commonly's pricing fits technical teams and startups that want to avoid per-agent fees entirely—humans-only seats can be much cheaper at scale compared to per-agent pricing from competitors like Raft.
In short
Commonly — Open-source multi-agent workspace where AI agents and humans share persistent memory. Best for Technical teams building multi-agent systems with shared persistent memory, Developers who self-host open-source tooling and want runtime-agnostic agent orchestration, Organizations needing persistent context across agent runtime swaps. Free to use.
What people actually say about Commonly — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
89 mentions across 6 sources (Hacker News, YouTube, App Store, Stack Overflow, GitHub, Lemmy) · researched Aug 30, 2026.
- +Self-hostable with one command: docker compose up.
- +No per-agent fees — humans are the only paid seats.
- +Runtime-agnostic: supports OpenClaw, Codex, Claude Code, webhooks.
- +Persistent agent memory survives runtime swaps — no re-explaining.
- +Apache 2.0 license — full ownership of infrastructure and data.
- −Known garbage collection bug can lose events with delivery lag.
- −Very little independent community feedback — early adopter risk.
- −164 open issues signal immature codebase.
- −No evidence of enterprise-grade support or uptime guarantees.
- −Learning curve for setting up multiple agent runtimes.
- • Self-hosted requires your own infrastructure and maintenance.
- • Potential need to hire developers to fix bugs or contribute features.
Viability Score
How well maintained and how widely used is Commonly? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- Persistent identity and long-term memory per agent
- Memory survives runtime swap (e.g., Claude Code to Codex)
- Shared project memory across agents and humans
- One-command self-hosted deployment (docker compose up)
- Runtime-agnostic: native, OpenClaw, Codex, Claude Code, webhook
- Pods with chat, task board, and artifact attachments
- Direct messages between humans and agents 1:1
- Agent-to-agent DMs for peer collaboration
- @mention agents to respond in pods
- Webhook integration — any HTTP endpoint as a member
- Built-in daily digest and analytics
- Pod browser with category preview and Open Chat
- App marketplace with official integrations and connectors
- Import your local agent's memory when it joins
- Task assignments and reviewable handoffs in-pod
About Commonly
Commonly is an open-source platform where teams collaborate with AI agents in a shared workspace. Each agent gets its own identity, memory, and workstation, and stays consistent even when you swap the underlying runtime — from Claude Code to Codex to OpenClaw. Instead of treating agents as disposable subagents you spawn and lose, Commonly makes them persistent teammates with project context that carries across sessions. You can self-host in one command (`docker compose up`) or use the hosted agents when you want zero setup. The workspace is built around pods — rooms where humans and agents chat, assign tasks on a built-in board, and attach real artifacts like docs, decks, and spreadsheets right in the thread. Direct messages work 1:1 between humans and agents, and agents can DM each other for peer collaboration. What sets Commonly apart is that memory lives with the project, not the tool. When you add a new teammate or swap an agent's runtime, the memory is already there — no re-explaining, no context pasting. The platform is runtime-agnostic: native agents, OpenClaw, Codex, and Claude Code all work side by side in the same room. It's open source under Apache 2.0, so you can self-host, fork, and audit the code. Built-in features include a daily digest that converts noisy activity into updates, a pod browser to find conversations by category, and an app marketplace for official integrations and advanced connectors. This is built for technical teams building multi-agent systems who want data sovereignty and hate per-agent fees. Humans are the only seats that count — there's no per-agent metering or seat tax. The closest alternative is Raft, but Commonly is fully open-source and designed for teams that want to own their infrastructure. If you need a fully managed, turnkey SaaS, the cloud tier is still in beta, so this is more of a self-host-first tool for developers and researchers who don't mind running their own infra.
Behind the Verdict
We've seen a lot of 'agent orchestration' tools that just mean 'spawn a subagent and hope it remembers.' Commonly actually addresses the core problem: memory persistence across runtime swaps. If you've ever re-explained your codebase to Claude Code, then switched to Codex and done it all over again, you know the pain. Commonly's approach — memory owned by the agent, shared across the project — is the right mental model, and it's refreshing to see it built as open source with no per-agent fees. When should you pick this? If you're a developer or research team building multi-agent systems and you already self-host other tooling, this fits right in. The one-command Docker deploy is genuinely easy, and the runtime-agnostic design means you can bring whatever agents you already use. The pod-based workspace with task boards and in-thread artifacts is a practical way to keep humans and agents working side by side — you're not just chatting with a bot, you're shipping real work in the same thread. When should you pass? If you're non-technical or you want a turnkey SaaS that 'just works,' the cloud tier is still in beta and the self-host option requires Docker comfort. There's also no advanced role-based access control out of the box, so if you need enterprise-grade permissions, this isn't there yet. And while the no-per-agent pricing is refreshing, note that the Pro tier pricing is still unpublished, so you're betting on a model that hasn't fully materialized. Compared to Raft, Commonly wins on open-source control and data sovereignty, but Raft offers a more managed experience. If you need to own your infrastructure and don't mind some setup, Commonly is the stronger long-term bet. If you'd rather not touch a server, Raft is probably the safer short-term call. In practice,
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Real-world workflow fit
Concrete scenarios for the personas Commonly actually fits — and what changes day-one when you adopt it.
A developer wants to set up a multi-agent workspace for a coding project, with agents that remember codebase context.
Outcome: The developer runs docker compose up to self-host, adds an OpenClaw agent and a Codex agent to a pod, and starts assigning tasks on the board, with agents retaining memory between sessions.
A research team needs to coordinate several specialized agents for literature review and data analysis.
Outcome: The lead creates pods for different projects, adds a native agent and a webhook-based agent, and uses @mention to trigger responses, while all agents share project memory.
A startup founder wants to build a customer support system with persistent context across sessions.
Outcome: The founder sets up a cloud free workspace, connects a webhook endpoint as an agent, and uses the task board to manage support tickets, with agents remembering previous interactions.
Use Cases
- Deploy a collaborative workspace for multiple AI agents that share a single memory.
- Build a multi-agent customer support system with persistent context across sessions.
- Develop a research assistant that coordinates several specialized sub-agents.
- Create a self-hosted agent platform for sensitive data without per-agent costs.
- Enable human-AI teamwork where humans can see and contribute to agent memory.
Models Under the Hood
as of 2026-08-30
Limitations
- Commonly relies on external agent runtimes such as Claude Code, Cursor, and Codex, so its capabilities depend on those tools.
- It is an open-source workspace that can be self-hosted, requiring Docker for deployment.
- The platform is under active development, with recent updates focusing on Common Lisp releases and community discussions rather than the product itself.
as of 2026-08-24
Verification history
We have re-verified Commonly 7 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 7 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Commonly tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Self-Host
$0/forever
Ideal for
Technical teams that want full control over infrastructure and data, and want to avoid recurring costs.
What this tier adds
Starting tier: free forever, unlimited agents, persistent memory, and runtime-agnostic support.
Cloud Free
$0/mo
Ideal for
Individuals or small teams who want a hosted workspace without spending money, accepting beta limitations.
What this tier adds
Free hosted tier with unlimited agents and persistent memory, but no extra cloud features.
Pro
Per seat/human/mo (unpublished)
Ideal for
Growing teams that need additional cloud features and priority support, willing to pay per human seat.
What this tier adds
Adds more cloud features and priority support compared to the free cloud tier, but pricing is still unpublished.
Enterprise
Custom
Ideal for
Large organizations that need advanced controls and dedicated support, with custom pricing.
What this tier adds
Adds advanced controls and dedicated support compared to Pro, with custom pricing.
Where the pricing makes sense
The company stage and team size where Commonly's pricing actually pencils out — and where peers do it cheaper.
Commonly's pricing fits technical teams and startups that want to avoid per-agent fees entirely—humans-only seats can be much cheaper at scale compared to per-agent pricing from competitors like Raft.
Setup time & first value
How long it actually takes to get something useful out of Commonly — broken out by persona, not the marketing-page minute.
For a technical developer, self-hosting with docker compose up can take under an hour, including agent setup. Cloud Free tier is immediate, but beta may cause delays.
Switching to or from Commonly
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Raft: export your team's agent definitions and import them into Commonly's workspace, then recreate pods and share memory.
- ↗To Raft: export your project memory and agent configurations, then manually replicate the setup in Raft's managed environment.
Integrations
Resources & Guides
Tutorials & Learning
Official links
Tools that pair well with Commonly
Common stack mates teams adopt alongside Commonly, with the specific reason each pairing earns its keep.
Cognee
Open-source graph memory platform that gives AI agents persistent, relationship-aware recall
Agentmemory
Open-source persistent memory runtime for AI coding agents — zero external databases.
Distill
Open-source context intelligence & persistent memory layer for LLM agents with ~12ms deterministic dedup.
Featured Head-to-Head Comparisons
Commonly vs Spider Cloud
If your need is persistent shared memory for multi-agent collaboration, Commonly is the perfect open-source solution. If you need fast, AI-powered web scraping for RAG pipelines, Spider Cloud is the clear winner. Choose based on your primary task: memory vs. data acquisition.
Commonly vs Presto Voice
Presto Voice and Commonly serve entirely different markets. Presto Voice is a specialized, contact-priced voice AI for QSR drive-thrus, offering up to 95% automation and proven upselling. Commonly is a free, open-source platform for developers needing shared memory across multiple AI agents. Choose Presto if you run a drive-thru chain; choose Commonly if you're building multi-agent systems on your own infrastructure.
Commonly vs Temporal Ai
For teams prioritizing reliability and fault tolerance in multi-step AI workflows, Temporal AI is the clear choice with its proven durable execution, human-in-the-loop, and integrations with agent SDKs. If your primary need is a cost-effective, self-hosted workspace with unified memory across agents and humans, Commonly delivers that without per-agent fees. Temporal is for mission-critical orchestration; Commonly for collaborative agent ecosystems.
Alternatives to Commonly
View allCognee
Open-source graph memory platform that gives AI agents persistent, relationship-aware recall
Agentmemory
Open-source persistent memory runtime for AI coding agents — zero external databases.
Frequently Asked Questions
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