Productivity & Collaboration openclawchatmulti-workspaceself-hostedreactnestjspostgresqlredis

Team9 - Collaborative Workspace for AI Agents

A collaborative workspace for AI agents built on OpenClaw, enabling instant messaging, multi-agent management, and document sharing.

FollowAgents review · FARS-2.1
Not recommended
9/ 100 5-point scale 0.5 / 5
1 2 3 4 5 6
1Trust0 / 29 · 0.0/5

Evidence shows the repository provides no permission model, user confirmation mechanism, data flow transparency, sensitive data handling, dependency security audit, external effect control, rollback mechanism, or source attribution. All trust-related criteria are unsupported, hence score 0.

2Reliability3 / 14 · 1.1/5

Self-consistency: README claims a collaborative workspace, but code shows a full client-server app, slight inconsistency but overall consistent, score 1. Dependency availability: package.json lists dependencies but no lockfile or integrity checks, score 1. Failure messages: no documentation or code showing error handling or user-friendly failure messages, score 0.

3Adaptability3 / 18 · 0.8/5

Audience and scenarios: README describes target users and scenarios but lacks detail, score 1. Capability boundaries: no clear definition of agent capabilities, score 0. Trigger precision: no description of trigger mechanisms, score 0. Environment fit: installation requirements provided but no adaptation for different environments, score 1.

4Convention2 / 18 · 0.6/5

Information architecture: README and directory structure exist but lack detailed docs, score 1. Install notes: quick start provided but lacks detailed steps, score 1. Naming stability: version 0.0.1 but no naming conventions, score 0. Examples and FAQ: none, score 0. Known limitations: not mentioned, score 0. License: custom license but not clearly Apache 2.0, score 1. Versioning changelog: none, score 0. Maintenance responsibility: not clear, score 0.

5Effectiveness1 / 13 · 0.4/5

Output usability: no description of output format or usability, score 0. Marginal value: README claims collaborative workspace but no proof of value, score 1. Cost benefit: no cost or benefit analysis, score 0.

6Verifiability0 / 8 · 0.0/5

Claim traceability: README claims not linked to code or tests, score 0. Cross-source corroboration: no other sources, score 0. Fact-inference separation: no distinction between facts and inferences, score 0.

Evidence confidence: Low Reviewed Aug 11, 2026 Reviewed revision fdc1143e9105
Safety controls not found in source: least-privilege scoping, confirmation before acting, data-flow disclosure, sensitive-data handling, dependency security, disclosed external effects, rollback or recovery path, verifiable attribution
Before you use it
  • The repository lacks any security or permission documentation, posing potential security risks.
  • The license is custom; careful review is needed for compliance.
  • No changelog is provided, making it difficult to track changes.
Review evidence [1][2][3][4][5][6][7][8]
See the full review method →

What does this agent do, and when should you use it?

Team9 is a collaborative workspace for AI agents, built on OpenClaw and its ecosystem. The repository provides a full web and desktop application that allows users to create and manage multiple AI agents through a chat-like interface, interacting with them in public channels, private channels, and DMs. It includes zero-config OpenClaw integration, multi-workspace isolation, rich messaging features like threads, @mentions, reactions, and file sharing. The tech stack consists of React, TypeScript, and Tauri on the frontend, and NestJS, PostgreSQL, Drizzle ORM, Socket.io, Redis, and RabbitMQ on the backend. The project is in its early stage, with a roadmap that includes desktop apps, integrations with Google Workspace, Gmail, WhatsApp, Telegram, and Feishu, and an open-source self-hosted deployment plan. Users can run it on the cloud at team9.ai or self-host it.

Team9 runs a web/desktop app that lets users create and manage multiple AI agents (called bots) and add them to channels. The app provides instant messaging with public/private channels and DMs, featuring real-time sync. It includes an OpenClaw App Management and Config Panel, allowing zero-config creation and use of OpenClaw agents. Users can share documents and build knowledge collaboratively within workspaces. The backend handles messaging and real-time events using NestJS and Socket.io, with PostgreSQL for persistence and Redis for caching/queuing. The project also supports multi-workspace isolation for different projects and teams. Deployment involves running git clone, pnpm install, pnpm db:migrate, and pnpm dev commands, requiring Node.js 18+, pnpm 8+, PostgreSQL, and Redis.

  1. Individual developers who want to add AI agents to their personal workflow without complex setup.
  2. Small teams that need to create multiple specialized agents for different projects and manage them in a shared workspace.
  3. Organizations looking for a private team collaboration tool that integrates messaging and AI capabilities.
  4. Remote teams that want to collaborate with AI agents in channels and threads, with a shared audit trail.
  5. Consultants or agencies that require multi-workspace isolation to keep client projects separate.

What are this agent's strengths and limitations?

Pros
  • Zero-config integration with OpenClaw lowers the barrier to setting up AI agents.
  • Offers rich messaging features like threads, mentions, reactions, and file sharing, with real-time sync.
  • Multi-workspace support allows isolating different projects and teams.
  • Provides a cloud option for instant trial without local setup.
Limitations
  • The project is at an early stage; many features (desktop apps, third-party integrations) are not yet implemented, and the roadmap may slip.
  • Self-hosting lacks detailed documentation (e.g., environment variables, database configuration), which may hinder production deployment and maintenance.
  • It depends on the OpenClaw ecosystem, so core functionality may be limited by its compatibility and stability.
  • Requires infrastructure like PostgreSQL, Redis, and RabbitMQ, adding operational overhead.

How do you install or deploy this agent?

For cloud, try instantly at team9.ai. For self-hosting, run:

git clone https://github.com/team9ai/team9.git
cd team9
pnpm install
pnpm db:migrate
pnpm dev

Open http://localhost:5173. Requires Node.js 18+, pnpm 8+, PostgreSQL, and Redis. Note: there is no detailed documentation on database credentials, environment variables, or production deployment, so self-hosting may be incomplete.

How do you use this agent?

After self-hosting, access http://localhost:5173 in your browser. Register or create a workspace, then use the interface to create AI agents (bots), add them to channels, and interact via chat. Files can be shared, and documents can be uploaded for collaborative learning. The cloud version is ready to use without setup.

FAQ

Is Team9 free?
The README does not mention pricing; the cloud service may be free or paid, but the current documentation is unclear. Self-hosting is open source but under a license with additional conditions.
Which AI models can Team9 work with?
It is built on OpenClaw, so it may support models that OpenClaw supports, but specific models are not specified in the README, and model switching is not yet available (on roadmap).
Can I run Team9 locally?
Yes, self-hosting instructions are provided, but you need Node.js, PostgreSQL, and Redis. Note that there is a lack of database configuration and deployment guidance currently.
Does Team9 have mobile support?
The README does not mention mobile apps; it is web-based and (on roadmap) desktop apps.
How many agents can I create?
The README mentions creating multiple agents, but no specific limit is stated.

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