Launching today

Kollab
Shared workspace where teams work with agents together
205 followers
Shared workspace where teams work with agents together
205 followers
Kollab is a shared workspace where AI agents become part of your team. Bots bring agents inside your IM like Slack without switching apps, Skills let anyone reuse your best workflows, Connectors link the tools you already use, and Memory keeps context alive across every project. No setup, no busywork.







Kollab
Hey PH 👋
YAN here, one of the makers behind Kollab. We built it so our team could stop bouncing between Slack, GitHub, Notion and half a dozen separate agent tools. One agent, sitting across every channel the team already lives in, with any MCP server wired behind it.
Here's how we use it ourselves. Kollab's hooked into our Slack and Telegram bots, with Notion MCP and GitHub MCP behind them. Inside our work group, anyone (devs or not) can ping the bot to look at code, review a feature, or file an issue. In the community group, users @Kollab to report bugs or ask how something works, and every message routes through Notion MCP straight onto our backend board. Feedback used to get lost in DMs; now it doesn't.
The piece we underestimated most is scheduled tasks. We thought we were shipping a digest job, but a scheduled task on Kollab is really a timed agent. The same cron can call any MCP tool, pull from the knowledge base, run as a specific agent role, and post back to any channel. Ours right now: one drafts a weekly changelog from GitHub issues, one cross-checks our status page against Sentry, one pings the on-call before standup. Same thing under the hood, totally different jobs on top.
When we need more than a quick answer, there's AgentCore. Long-running agent with its own filesystem and a browser built in. We've been using it to stand up small demo sites and internal tools instead of writing throwaway scripts. And since skills are just regular GitHub repos, anything the team keeps repeating turns into a skill the whole org can install by name. We're still early on this part, and it's probably where we'll end up finding the weirdest uses.
Question for PH: if you had one agent sitting across your team's channels with full MCP reach, what's the first scheduled task or skill you'd write? No idea what people will come up with. So far the answers have been all over the map, and two of them are already in our next release.
How do you handle agent coordination across workflows? Building an AI scheduling assistant for TV and curious about your approach to chaining agent tasks.
Kollab
@brian_h4 Great question! In Kollab, each agent can call any MCP server behind the scenes, so chaining tasks is really about connecting the right tools. For example, a scheduled task can pull data from one source, process it, then post results to a channel or update a doc, all in one flow. For something like a TV scheduling assistant, you could set up a skill that coordinates across your content database and team channels. Would love to hear more about what you’re building. Feel free to reach out!
HeyForm
We've been using Kollab internally for a few weeks now.
The biggest win for us is Skills — once someone builds a workflow, the whole team can reuse it instantly. No more explaining the same process over and over. Really changes how we share knowledge across the team.
Kollab
@itsluo That’s awesome to hear! Skills reusability is honestly one of the things we’re most proud of. Someone figures out a workflow once, and the whole team gets it. And it keeps getting better as more skills pile up. Thanks for trying it out 🙌
Kollab
Hi Product Hunt! 👋 I'm Gavin, the CEO and founder of Kollab.
While building my previous SaaS product (Buildin), I realized a fundamental issue: even with deep AI integration, most tools operate on a "SaaS + AI" logic where AI is merely a helpful sidekick. However, with the rapid rise of Claude Code, MCP, and similar breakthroughs, we are officially entering the Agent era.
Yet, the barrier to entry for using Agents at work is still way too high. Terminals, npm installs, MCP configurations, system prompts, memory management... these technical hurdles keep 90% of everyday users out. Even for the tech-savvy who do know how to set them up, their Agent environments remain siloed on local machines, making it incredibly hard to share workflows or best practices across a team.
That’s exactly why we built Kollab. We designed Kollab to be the central hub for team-agent collaboration. We focused on three core pillars to make this happen:
Zero-Barrier Configuration: We made the complexity of MCPs and coding environments completely invisible. Through our Connectors, you can integrate tools like Notion, GitHub, Figma, Linear, and Slack with just a few clicks, allowing your Agents to seamlessly access and act on your actual business data.
The Compounding Power of Team Knowledge: This is what makes Kollab truly special. When any team member creates a new Skill or sets up a workflow, it’s immediately added to your team's shared Skill Marketplace. One person's "aha" moment instantly scales into an organizational capability. No more reinventing the wheel.
Work Where Collaboration Already Happens: You shouldn't have to change your habits to use AI. With Kollab, you can deploy your Agents as Bots directly into Slack or Telegram. Just tag them in your chat, and they’ll take instructions and execute long-running automated tasks right alongside your human teammates.
Internally, our product, engineering, and ops teams are already sharing over 20 active skills for our daily workflows. We firmly believe that Agents shouldn't just be about boosting individual productivity—they should serve as the central nervous system for team collaboration.
We’d love for you to try Kollab and would be incredibly grateful for your honest feedback!
👉 https://kollab.im/product
Kollab
Hey 👋 I'm jiayi, one of the makers behind Kollab.
Kollab is an AI-native workspace. Unlike doc tools with AI added on top, Kollab puts Agents front and center. You give them tasks, they execute, and everything stays in a shared workspace your team can actually use.
Here's a real example. Our team runs a blog. It used to be all manual: track trends, find topics, write drafts, make images, review. Same grind every week.
Now in Kollab:
A scheduled task searches target keywords every morning and drops new topic ideas into the workspace
Another task picks up new topics automatically, writes drafts and generates images
A review task runs a saved Skill to check tone, structure, and SEO
When it's done, the Bot sends a message in our channel so the team knows it's ready for final review
Three scheduled tasks running in the background. Skills defined once, reused every time. We just do the last step: review and publish. What used to take a team days now takes one person a few minutes.
No code. No stitching five tools together. Set up a Skill, set a schedule, let Agents do the work.
Teamwork, done with Kollab.
Lessie AI
Interesting positioning. Feels less like “another agent tool” and more like an orchestration layer across where work already happens. If teams can actually rely on it for day-to-day ops, this could become pretty sticky.
Kollab
@colin_yu_123 Yes! What we need to do is connect all the functions together. Horizontal connection
Kollab
@colin_yu_123 Thanks! That’s exactly how we think about it — not another standalone tool, but a layer that sits where your team already works and orchestrates everything from there. We’ve been using it ourselves daily and yeah, it gets sticky fast 😄
Lessie AI
This feels very practical. Most teams don’t lack tools — they lack something that ties everything together. An agent that sits across channels and actually executes workflows (not just answers) could remove a lot of operational overhead.
Kollab
@alexia_li Thanks Alexia! Spot on — most teams have plenty of tools, what’s missing is something that actually connects them and gets things done. That’s why we built Kollab. Instead of adding another app to the stack, we drop the Agent right into Slack, Telegram, wherever your team already hangs out. It picks up tasks, hits MCP servers, runs the workflow. No extra tabs, no context switching.