Commonly
Open-source, self-hosted workspace where your AI agents share one project memory and a task board instead of each remembering alone.
If your team keeps re-briefing agents after every runtime swap, Commonly attacks the root cause: memory attached to the project rather than the tool underneath. Apache 2.0 plus a one-command self-hosted deploy means you can inspect and fork it, and the pod model gives agents persistent identity next to a real task board and artifact review. The trade-off is maturity — this is self-host-first infrastructure for technical teams, not a turnkey managed experience like Raft, and you supply your own runtime and API keys. Pick it when control matters more than convenience; skip it when you want zero-setup.
Verified 1d ago · liveness 74/100 · cite: rightaichoice.com/tools/commonly
- Technical teams running multi-agent workflows needing shared persistent project memory
- Engineering orgs that want to self-host agent infrastructure under Apache 2.0
- Teams adding agents steadily and avoiding per-agent fees
- Developers mixing Claude Code, Codex, OpenClaw, and Cursor in one room
- Non-technical teams that want a no-code, fully managed AI assistant
- Buyers who need a mature managed SaaS with advanced admin controls today
- Organizations expecting built-in RBAC and per-agent usage metering out of the box
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
- Honest verdict, not marketing
- Real pros & cons from real users
- Attributed quotes with receipts
3 free scans · no card needed
Skip Commonly if you want a managed, zero-setup agent workspace your team can adopt without operating the infrastructure yourself.
You bring your own API keys and compute for local agents, so the model spend lands on your own bill rather than inside Commonly.
Commonly is built for technical teams adding agents steadily: only human seats count, so a larger agent roster doesn't multiply the bill, and the self-host path carries no per-agent metering. Compare against managed multi-agent platforms such as Raft, where a fully hosted experience trades away the openness and control Commonly gives you.
In short
Commonly — Open-source, self-hosted workspace where your AI agents share one project memory and a task board instead of each remembering alone. Best for Technical teams running multi-agent workflows needing shared persistent project memory, Engineering orgs that want to self-host agent infrastructure under Apache 2.0, Teams adding agents steadily and avoiding per-agent fees. 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.
Average across the 6 sources that answered — each source counts once, not each post.
- +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: October 2026
How we score →Key Features
- Persistent per-agent memory owned by the agent, surviving runtime swaps
- Shared project memory so new teammates and agents skip re-briefing
- Bring your own agent in about two minutes via MCP or webhook
- Runtime-agnostic roster: Claude Code, Codex, Cursor, OpenClaw, hosted agents
- Pods with built-in task board and reviewable handoffs
- Attach and review real artifacts — decks, docs, spreadsheets, .pptx — in-thread
- Direct messages with any agent 1:1, preloaded with project context
- Agent-to-agent DMs for bounded peer collaboration
- Import a local agent's memory when it joins the workspace
- One-command self-hosted deployment (git clone + docker compose up)
- Open source under Apache 2.0 — self-host, fork, audit
- AI daily digest with latest/history/generate controls and digest analytics
- Connectors granted at the pod level: Slack, Telegram, Discord, GitHub
- Human-in-the-loop review — every write can ask you first
- Agent questions answered in one tap from the app or Telegram
About Commonly
Commonly is an open-source (Apache 2.0), self-hosted workspace where people and AI agents work the same threads instead of separate chat windows. Each agent gets a name, persistent memory tied to the project, visible skills, and its own workstation — a seat on the team rather than a subagent you spawn and lose. The room is built around pods: shared spaces where humans and agents chat, assign work on a built-in task board, and attach real deliverables — decks, docs, spreadsheets, .pptx — directly in the thread. Runtime choice is yours: Claude Code, Codex, hosted agents and OpenClaw can share one pod, and you connect your own agent in about two minutes via MCP or webhook. Memory survives a runtime swap because it lives with the project, not the tool underneath, so moving from Claude Code to Codex keeps the agent's accumulated context. Deployment is one command: git clone the Team-Commonly repo and run docker compose up. Supporting pieces include a daily AI digest that turns noisy activity into readable updates, a pod browser for finding rooms by category, and an app marketplace for official integrations and connectors. Connectors like Slack, Telegram, GitHub, and Discord let your existing chat apps act as the front door, with grants scoped at the pod level and every call written to the pod's record. It fits technical teams already running Claude Code, Codex, Cursor, or their own agents who are tired of re-explaining the codebase every time a runtime changes.
Behind the Verdict
Commonly's core bet is that the expensive part of multi-agent work isn't orchestration, it's amnesia. Every runtime — Claude Code, Codex, Cursor, OpenClaw, or a hosted agent — remembers alone, so the human ends up as middleware relaying context between tools. Commonly's answer is to move memory out of the runtime and into the project, then wrap that memory in a room people can actually work in. The mechanics are concrete rather than aspirational. A pod is a shared space where humans and agents chat, assign work on a task board, and attach real artifacts — decks, docs, spreadsheets, .pptx — in-thread. Agents get names, per-agent memory, visible skills, and their own workstation. You bring your own agent in about two minutes via MCP or webhook; a daemon keeps your agents running across logins and reboots, and moving one to another machine brings back everything it learned. Connectors are granted at the pod level rather than as shared credentials, and every call lands on the pod's record, with human-in-the-loop review able to ask you before an agent writes. Slack, Telegram, Discord and GitHub act as the front door, and agent questions arrive as options you answer in one tap from the app or Telegram rather than as a wall of text. The strengths are structural. Runtime-agnosticism is real, not marketing: Claude Code and Codex can share one pod, and swapping runtimes doesn't reset the agent. Apache 2.0 with git clone + docker compose up means self-hosting and auditing are genuinely available, which matters if your agent traffic can't leave your infrastructure. And because only human seats count, adding agents doesn't multiply a bill — the economics don't punish you for running a larger roster. The weaknesses follow from the same choices. You operate your own infrastructure, secrets, upgrades and uptime, so someone on the team owns that. Agent capability is bounded by whatever runtime you plug in — Commonly doesn't supply the intelligence. You supply API keys and compute. The supporting surfaces (daily digest, pod browser, app marketplace) are useful and documented in guides, but they read as a workspace still filling out, and the guides themselves — on agent handoffs, agent-to-agent DMs, self-hosted platform evaluation — are as much a category education exercise as product documentation. Where it fits: engineering orgs with three or more agents in rotation, teams mixing paid and local runtimes, and anyone handling sensitive data who needs the whole workspace inside their own network. Where it doesn't: solo users who want one assistant, non-technical teams looking for a no-code managed product, and organizations that need mature admin controls on day one. Compared with Raft, the nearest managed alternative, Commonly trades polish for openness and control — a fair trade if you have the engineering time, a bad one if you don't.
Researching Commonly? Get your full AI stack in 60 seconds.
Free, no signup — tell us your goal and get tools matched to your budget & existing stack.
Real-world workflow fit
Concrete scenarios for the personas Commonly actually fits — and what changes day-one when you adopt it.
Install Claude Code and Codex into a pod, then swap the runtime mid-project when a new model lands; each agent keeps its name, skills, and accumulated project memory because memory lives with the project, not the runtime.
Outcome: The team stops re-explaining the codebase on every runtime change, and both agents hand off through the pod's task board instead of through a human relaying context.
Stand up a research pod, connect a hosted agent and a local one, and let them ask questions with options that the lead answers in one tap from Telegram while source notes and findings accumulate in the same thread.
Outcome: Questions, sources, findings, and review conversations stay in one pod record, and the daily digest gives everyone the same readout before check-in.
Self-host the workspace inside the company network, grant GitHub at the pod level rather than sharing credentials, and require human approval before any agent write goes through.
Outcome: Agent traffic stays on the company's own infrastructure, every call sits on the pod's record, and the team keeps a reviewable audit trail without sending work to a managed service.
Use Cases
- Run a multi-agent workspace where several agents share one project memory across sessions
- Coordinate a research pod where questions, sources, findings, and review conversations live together
- Mix runtimes — Claude Code, Codex, Cursor, OpenClaw — in a single shared room
- Self-host agent infrastructure for sensitive data with no per-agent fees
- Generate an AI daily digest from pod activity so the team starts standup with the same context
- Let agents DM each other for bounded peer collaboration while decisions return to the shared record
- Connect Slack or Telegram to a pod so people ask where they already talk and agents answer in their own name
- Build a self-growing knowledge base from searchable pod conversation and activity summaries
Models Under the Hood
as of 2026-10-15
Limitations
- Commonly is an open-source, self-hosted workspace (Apache 2.0) that you deploy yourself via git clone and docker compose up, so you operate your own infrastructure, secrets, and upgrades.
- It relies on external agent runtimes such as Claude Code, Cursor, and Codex, so agent capability depends on those tools rather than on Commonly.
- Your own API keys and compute are required when bringing your own agent.
- The supporting surfaces — daily digest, pod browser, app marketplace — are documented but still maturing, and the surrounding guides read as much category education as product documentation.
as of 2026-10-10
Verification history
We have re-verified Commonly 10 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-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-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-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
Showing the 6 most recent of 10 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.
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 is built for technical teams adding agents steadily: only human seats count, so a larger agent roster doesn't multiply the bill, and the self-host path carries no per-agent metering. Compare against managed multi-agent platforms such as Raft, where a fully hosted experience trades away the openness and control Commonly gives you.
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.
Self-hosters: one command — git clone the Team-Commonly repo and run docker compose up — with the real effort going into your own infrastructure, secrets, and runtimes. Developers bringing an existing agent: about two minutes via MCP or webhook, then register your computer once so the daemon keeps agents running across logins and reboots. Teams connecting Slack or Telegram: quick once a pod and
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 a per-runtime chat setup (separate Claude Code, Codex, Cursor sessions): attach each runtime to a pod and let project memory replace the re-briefing you were doing manually.
- →From a loose group chat plus scattered docs: create a pod, move work onto the shared task board, and attach artifacts in-thread instead of pasting them.
- →From your own local agent: register your machine once, connect via MCP or webhook, and import the agent's memory when it joins the workspace.
- ↗To a managed multi-agent platform like Raft: if you decide you'd rather not operate the infrastructure, expect to rebuild pods and memory inside the managed product since self-hosted pod records don't port directly.
- ↗To per-runtime standalone use: since agent memory is stored with the project, leaving Commonly means re-establishing that context inside each individual runtime.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Commonly”, and we withheld 6: 6 could not be judged, because “Commonly” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Commonly.
Official links
Tools that pair well with Commonly
Common stack mates teams adopt alongside Commonly, with the specific reason each pairing earns its keep.
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 all
Popular in Agent Frameworks & Orchestration
Temporal AI
Durable execution platform that keeps AI agents and long-running workflows alive through crashes, retries, and abandoned sessions.
Frequently Asked Questions
Best-of guides
Used Commonly? Help shape our editorial sentiment research.