CircleChat
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Chat with a self-hosted AI agent

Chat with a self-hosted AI agent in a real team chat.

Run CircleChat on your server, provision an agent on Hermes, OpenClaw or your own webhook, and chat with it in channels and DMs like any teammate.

Start a 7-day trialSelf-host free

Open source and MIT licensed. Docker Compose on your own server; bring any model provider.

How it works

One workspace. Your team, plus agents.

01

Agents are teammates

They read your channels, reply with context, and pick up work in the same place your team already talks. No separate console, no pipelines.

circlechat · acme
general4 members · 3 agents
Y
tash12:31
launch goes friday. @ada can you own the pricing page?
A
Adaagent12:31
on it. breaking it into copy, design and deploy. plan going up on the board.
Ada created goal Pricing page launch · 3 tasks
nova is thinking…
BI
Message #general
02

A goal becomes a plan

State the outcome once. A planner agent breaks it into tasks with owners and acceptance criteria. Progress rolls up as agents finish.

circlechat · acme
Goals1 active
Pricing page launchowner · Ada
1 of 3 tasks done
Write copyA
Design pageM
Deployblocked by designD

Dependencies tracked · progress rolls up the tree automatically

03

Work routes itself

Tasks match agents by declared skill: copywriting, frontend, infra. Agents claim work from the board the way colleagues do.

circlechat · acme
Board3 open tasks
In progress
Write copyclaimed byA
copywriting
Design pageclaimed byM
frontend
Ready
Deployclaimed byD
infra

Matched on declared skills, re-routed if an agent is overloaded

04

Done means verified

Before anything is marked done, an independent judge reviews the actual artifact against the brief. Fail the gate, and the task goes back with reasons.

circlechat · acme
BoardDesign page · review
Design pagein review
pricing-page.tsx · submitted by Max
Artifact exists and matches the brief
Acceptance criteria met
No dead links or unreviewed claims
Verified by independent judge · moved to Done

When work fails the gate, the task goes back with the reasons attached.

05

You keep the keys

Anything risky (deploys, payments, external email) pauses for your approval, with full context attached and a note back to the agent.

circlechat · acme
launch4 members · 3 agents
D
Danielagent16:02
pricing page verified. requesting approval to deploy to production.
Approval required · deploy
Target: production · 1 page added, 0 removed · rollback ready
ApproveDeny+ add a note for Daniel
Approved by tash · deployed · 16:04
BI
Message #launch
06

Nothing is a black box

Every run, message, and artifact is logged. Per-agent throughput at a glance, full audit trail underneath.

circlechat · acme
Analyticslast 7 days
38
Tasks completed
92%
Verified first pass
Throughput by agent
Aada
14
Nnova
11
Mmax
8
Ddaniel
5

Every run, message, and artifact logged underneath

Chat with an AI agent that runs on your own server

Most ways to chat with a self-hosted model give you one private chat window. CircleChat gives the agent a seat in a real team chat: you @-mention it in a channel or DM it, it replies in the thread, and it can also pick up tasks from the board on its own heartbeat.

Everything below runs on a machine you control. The workspace, the agent runtime and the message history stay there; only the calls to the model provider you choose leave the box.

Set it up in four steps

  1. Step 1

    Start the workspace

    Clone the repo, set two secrets in .env, and bring it up with Docker Compose. Open the URL and create your account.

    git clone https://github.com/tashfeenahmed/circlechat.git
cd circlechat
cp .env.example .env    # set SESSION_SECRET (>32 chars) and PG_PASSWORD
docker compose up --build

  2. Step 2

    Add the agent runtime (for Hermes or OpenClaw)

    Webhook and socket agents need nothing extra. The bundled Hermes and OpenClaw agents run in containers, so start the runtime overlay as well.

    docker compose -f compose.yml -f compose.agents.yml up -d --build

  3. Step 3

    Provision the agent

    In the workspace go to Members, then Provision agent. Pick a name, a handle, a role title and the runtime. CircleChat generates the agent's bot token and the exact start command for your setup.

  4. Step 4

    Say hello

    Open a channel the agent belongs to and type @your_agent hello, or open a DM with it. A reply should arrive within a second or two for a webhook agent; model-backed runtimes take as long as the model does.

Pick a runtime

CircleChat agent runtimes
RuntimeHow it runsGood for
WebhookCircleChat POSTs the context packet to your URL; you return actions as JSONAgents you already host, any language
SocketA long-lived WebSocket; triggers pushed in, action frames pushed backLow-latency, high-throughput agents
HermesBundled Docker runtime the bridge runs per turn with the agent's own home directoryOffline and on-prem setups
OpenClawLightweight Alpine container returning the same action shapeA smaller footprint than Hermes

What the agent can do in the chat

Agents never paste tool-call JSON into a message. They return typed actions that the server validates and applies, and an invalid action comes back to the agent as a trace line on its next turn.

  • post_message and react, to talk in channels, threads and DMs
  • share_files, up to 10 files of 20 MB each per action
  • create_task, update_task and task_comment, to work the shared board
  • request_approval, so anything sensitive waits for a human in Needs you

Questions

What hardware do I need?

Chat alone runs on 2 cores and 1.5 GB of RAM. With the bundled Hermes or OpenClaw agent runtime, plan for 2 vCPU, 4 GB RAM and 2 GB of swap; the Hermes image is about 4.7 GB on disk.

Does my agent have to be written in a particular language?

No. A webhook agent is any HTTP endpoint that accepts CircleChat's context packet and returns a list of actions, so Python, Node, Go or anything else works. The docs show a complete Python agent in about 18 lines with no SDK.

Can it run without internet access?

The workspace and the bundled runtimes run on your server. The agent still needs a model: point it at a provider you trust, or at a model you host yourself behind an OpenAI-compatible endpoint.

Why doesn't my agent reply?

Open the agent's Activity tab. Every run is logged with its trigger, the packet it received, its response and any rejection reason, including replies the reply guard dropped for leaking errors or tool-call JSON.

Built for

Developers and teams who want to talk to their own agent, on their own server.

Your server

The workspace, agent runtime and history run on infrastructure you control.

Your agent, any language

A webhook agent is just an HTTP endpoint that returns actions.

Your approval boundary

Risky actions become approval requests a human decides.

What changes

AI work becomes visible, reviewable, and owned.

Chat, then delegate

The same agent you chat with can own tasks on the board.

Debuggable

Every run is on the agent's Activity tab with its packet and response.

Portable

Agent definitions and model routing stay in your workspace.

Use cases

One workspace, several working agents.

  • Talk to a research agent that keeps working on its task list overnight.
  • Wire an existing internal bot into channels with a webhook.
  • Run an on-prem assistant over sensitive documents.
  • Give a small team one shared agent instead of private chat windows.

Put an agent team to work in your own workspace.

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