CCCC

Local-first Multi-agent Collaboration Kernel

A lightweight multi-agent framework with infrastructure-grade reliability.

Chat-native, prompt-driven, and bi-directional by design.

Run multiple coding agents as a durable, coordinated system — not a pile of disconnected terminal sessions.

Three commands to go. Zero infrastructure, production-grade power.

English | 中文 | 日本語

Why CCCC

Durable coordination: working state lives in an append-only ledger, not in terminal scrollback.
Visible delivery semantics: messages have routing, read, ack, and reply-required tracking instead of best-effort prompting.
One control plane: Web UI, CLI, MCP, and IM bridges all operate on the same daemon-owned state.
Multi-runtime by default: Claude Code, Codex CLI, ChatGPT Web, Gemini CLI, and the rest of the first-class runtimes can collaborate in one group.
Local-first operations: one pip install, runtime state in CCCC_HOME, and remote supervision only when you choose to expose it.

The Problem

Using multiple coding agents today usually means:

Lost context — coordination lives in terminal scrollback and disappears on restart
No delivery guarantees — did the agent actually read your message?
Fragmented ops — start/stop/recover/escalate across separate tools
No remote access — checking on a long-running group from your phone is not an option

These aren't minor inconveniences. They're the reason most multi-agent setups stay fragile demos instead of reliable workflows.

What CCCC Does

CCCC is a single pip install with zero external dependencies — no database, no message broker, no Docker required. Yet it gives you the pieces fragile multi-agent setups usually lack:

Capability	How
Single source of truth	Append-only ledger (`ledger.jsonl`) records every message and event — replayable, auditable, never lost
Reliable messaging	Read cursors, attention ACK, and reply-required obligations — you know exactly who saw what
Unified control plane	Web UI, CLI, MCP tools, and IM bridges all talk to one daemon — no state fragmentation
Multi-runtime orchestration	Claude Code, Codex CLI, ChatGPT Web, Gemini CLI, and 5 more first-class runtimes, plus `custom` for everything else
Role-based coordination	Foreman + peer model with permission boundaries and recipient routing (`@all`, `@peers`, `@foreman`)
Local-first runtime state	Runtime data stays in `CCCC_HOME`, not your repo, while Web Access and IM bridges cover remote operations

How CCCC looks

cccc.mp4

Quick Start

Install

# Stable channel (PyPI)
pip install -U cccc-pair

# RC channel (TestPyPI)
pip install -U --pre \
  --index-url https://test.pypi.org/simple/ \
  --extra-index-url https://pypi.org/simple/ \
  cccc-pair

Requirements: Python 3.9+, macOS / Linux / Windows

Upgrade

cccc update

Use cccc update --check to inspect the detected install type and the command that would run.

Launch

cccc

Open http://127.0.0.1:8848 — by default, CCCC brings up the daemon and the local Web UI together.

Create a multi-agent group

cd /path/to/your/repo
cccc attach .                              # bind this directory as a scope
cccc setup --runtime claude                # configure MCP for your runtime
cccc actor add foreman --runtime claude    # first actor becomes foreman
cccc actor add implementer --runtime codex # add a peer
cccc group start                           # start all actors
cccc send "Please inspect the repo and propose the first safe task." --to foreman
cccc tracked-send "Please take the first concrete task and reply with validation evidence." \
  --to implementer \
  --title "First concrete task" \
  --outcome "The change and validation evidence are reported"

You now have two agents collaborating in a persistent group with full message history, delivery tracking, and a web dashboard. The daemon owns delivery and coordination, and runtime state stays in CCCC_HOME rather than inside your repo.

Programmatic Access (SDK)

Use the official SDK when you need to integrate CCCC into external applications or services:

pip install -U cccc-sdk
npm install cccc-sdk

The SDK does not include a daemon. It connects to a running cccc core instance.

Architecture

graph TB
    subgraph Agents["Agent Runtimes"]
        direction LR
        A1["Claude Code"]
        A2["Codex CLI"]
        A3["ChatGPT Web<br/>GPT-5.x via MCP"]
        A4["Gemini CLI"]
        A5["+ 5 more + custom"]
    end

    subgraph Daemon["CCCC Daemon · single writer"]
        direction LR
        Ledger[("Ledger<br/>append-only JSONL")]
        ActorMgr["Actor<br/>Manager"]
        Auto["Automation<br/>Rules · Nudge · Cron"]
        Ledger ~~~ ActorMgr ~~~ Auto
    end

    subgraph Ports["Control Plane"]
        direction LR
        Web["Web UI<br/>:8848"]
        CLI["CLI"]
        MCP["MCP<br/>(stdio)"]
    end

    subgraph IM["IM Bridges"]
        direction LR
        TG["Telegram"]
        SL["Slack"]
        DC["Discord"]
        FS["Feishu"]
        DT["DingTalk"]
        WC["WeCom"]
        WX["Weixin"]
    end

    A1 <-->|MCP tools<br/>PTY/headless| Daemon
    A2 <-->|MCP tools<br/>PTY/headless| Daemon
    A3 <-->|Browser delivery<br/>Remote MCP| Daemon
    A4 <-->|MCP tools| Daemon
    A5 <-->|MCP tools| Daemon
    Daemon <--> Ports
    Web <--> IM

Key design decisions:

Daemon is the single writer — all state changes go through one process, eliminating race conditions
Ledger is append-only — events are never mutated, making history reliable and debuggable
Ports are thin — Web, CLI, MCP, and IM bridges are stateless frontends; the daemon owns all truth
Runtime home is CCCC_HOME (default ~/.cccc/) — runtime state stays out of your repo

Supported Runtimes

CCCC orchestrates agents across 9 first-class runtimes, with custom available for everything else. Each actor in a group can use a different runtime.

Runtime	Integration	Command / Surface
Claude Code	Auto MCP setup	`claude`
Codex CLI	Auto MCP setup	`codex`
ChatGPT Web	Remote MCP + Browser Delivery	`chatgpt.com` conversation
Gemini CLI	Auto MCP setup	`gemini`
Droid	Auto MCP setup	`droid`
Amp	Auto MCP setup	`amp`
Auggie	Auto MCP setup	`auggie`
Kimi CLI	Auto MCP setup	`kimi`
Neovate	Auto MCP setup	`neovate`
Custom	Manual	Any command

cccc setup --runtime claude    # auto-configures MCP for this runtime
cccc runtime list --all        # show all available runtimes
cccc doctor                    # verify environment and runtime availability

Actors can run as PTY (embedded terminal) or headless (structured I/O without a terminal). Claude Code and Codex CLI support both modes; headless gives the daemon tighter delivery and streaming control.

ChatGPT Web / GPT-5.x local development

ChatGPT Web can join a CCCC group as a real actor, not just an external chat window. CCCC delivers group messages into one explicitly bound ChatGPT conversation through browser delivery, while ChatGPT calls back into CCCC through a single actor-bound remote MCP connector.

In supported ChatGPT sessions, GPT-5.x can participate in local development with the same coordination layer as Claude Code or Codex: receive routed messages, reply visibly through CCCC, inspect and edit repository files, run scoped shell/git commands, and coordinate with peer agents. This gives Plus/Pro paid ChatGPT users an experience close to a native Codex-style local coding agent when the selected chat exposes the CCCC MCP connector.

GPT-5.x Pro note: ChatGPT platform restrictions currently prevent GPT-5.x Pro from using full third-party MCP/local write tools in the same way. In CCCC, GPT-5.x Pro is best used as an advisory surface for planning, architecture review, debugging hypotheses, and critique based on conversation context, pasted diffs, test output, and project summaries. Local execution should remain with MCP-capable runtimes such as Codex, Claude Code, or ChatGPT Web Model using a GPT-5.x session that can access the CCCC connector.

Shortest setup path:

Expose cccc web through a public HTTPS URL or tunnel.
Create an Admin Access Token in Settings > Global > Web Access.
Add an actor with runtime ChatGPT Web Model.
In Settings > Global > ChatGPT Web Model, create/copy the single MCP URL for that actor.
In ChatGPT Developer mode, create a custom MCP connector with that URL and No Auth.
Bind a specific https://chatgpt.com/c/... conversation to the actor, then choose a GPT-5.x model that can see and use the CCCC MCP connector.

Full setup and troubleshooting: ChatGPT Web Model Runtime.

Messaging & Coordination

CCCC implements IM-grade messaging semantics, not just "paste text into a terminal":

Recipient routing — @all, @peers, @foreman, or specific actor IDs
Read cursors — each agent explicitly marks messages as read via MCP
Reply & quote — structured reply_to with quoted context
Attention ACK — priority messages require explicit acknowledgment
Reply-required obligations — tracked until the recipient responds
Auto-wake — disabled agents are automatically started when they receive a message

Use ordinary send for chat, questions, and quick requests. Use tracked-send when delegated work needs a durable owner, outcome, evidence, handoff, or acceptance trail. @all remains available for announcements or urgent shared coordination, but it should not be the default way to start concrete work.

Messages are delivered to actor runtimes through the daemon-managed delivery pipeline, and the daemon tracks delivery state for every message.

Automation & Policies

A built-in rules engine handles operational concerns so you don't have to babysit:

Policy	What it does
Nudge	Reminds agents about unread messages after a configurable timeout
Reply-required follow-up	Escalates when required replies are overdue
Actor idle detection	Notifies foreman when an agent goes silent
Keepalive	Periodic check-in reminders for the foreman
Silence detection	Alerts when an entire group goes quiet

Beyond built-in policies, you can create custom automation rules:

Interval triggers — "every N minutes, send a standup reminder"
Cron schedules — "every weekday at 9am, post a status check"
One-time triggers — "at 5pm today, pause the group"
Operational actions — set group state or control actor lifecycles (admin-only, one-time only)

Web UI

The built-in Web UI at http://127.0.0.1:8848 provides:

Chat view with @mention autocomplete and reply threading
Per-actor embedded terminals (xterm.js) — see exactly what each agent is doing
Group & actor management — create, configure, start, stop, restart
Automation rule editor — configure triggers, schedules, and actions visually
Context panel — shared vision, sketch, milestones, and tasks
Group Space — NotebookLM integration for shared knowledge management
ChatGPT Web Model setup — connect one ChatGPT Web conversation as a CCCC actor
IM bridge configuration — connect to Telegram/Slack/Discord/Feishu/DingTalk/WeCom/Weixin
Settings — messaging policies, delivery tuning, terminal transcript controls
Text scale — 90% / 100% / 125% font size with per-browser persistence
Light / Dark / System themes

Chat	Terminal

Remote access

For accessing the Web UI from outside localhost:

LAN / private network — bind Web on all local interfaces: CCCC_WEB_HOST=0.0.0.0 cccc
Cloudflare Tunnel (recommended) — cloudflared tunnel --url http://127.0.0.1:8848
Tailscale — bind to your tailnet IP: CCCC_WEB_HOST=$TAILSCALE_IP cccc
Before any non-local exposure, create an Admin Access Token in Settings > Web Access and keep the service behind a network boundary until that token exists.
In Settings > Web Access, 127.0.0.1 means local-only, while 0.0.0.0 means localhost plus your LAN IP on a normal local host. If CCCC is running inside WSL2's default NAT networking, 0.0.0.0 only exposes Web inside WSL; for LAN devices, use WSL mirrored networking or a Windows portproxy/firewall rule.
Save stores the target binding. If Web was started by cccc or cccc web, use Apply now in Settings > Web Access to perform the short supervised restart. If Web is managed by Docker, systemd, or another external supervisor, restart that service instead.
Start / Stop are only for Tailscale remote access and do not rebind the already-running Web socket.
Token policy is tiered on purpose: localhost-only can stay simple, LAN/private exposure defaults to Access Tokens, and any configured public URL/tunnel exposure requires Access Tokens.

IM Bridges

Bridge your working group to your team's IM platform:

cccc im set telegram --token-env TELEGRAM_BOT_TOKEN
cccc im start

Platform	Status
Telegram	✅ Supported
Slack	✅ Supported
Discord	✅ Supported
Feishu / Lark	✅ Supported
DingTalk	✅ Supported
WeCom / 企业微信	✅ Supported
Weixin / 微信	✅ Supported

DingTalk and WeCom support streaming replies (AI Card and aibot streaming respectively); other platforms deliver final messages.

From any supported platform, use plain text or /send @foreman <message> for normal coordination, reserve /send @all <message> for true broadcasts, use /status to check group health, and use /pause / /resume to control operations — all from your phone.

CLI Reference

# Lifecycle
cccc                           # start daemon + web UI
cccc daemon start|status|stop  # daemon management

# Groups
cccc attach .                  # bind current directory
cccc groups                    # list all groups
cccc use <group_id>            # switch active group
cccc group start|stop          # start/stop all actors

# Actors
cccc actor add <id> --runtime <runtime>
cccc actor start|stop|restart <id>

# Messaging
cccc send "message" --to foreman
cccc tracked-send "delegated work" --to implementer --title "Task title" --outcome "Done criterion"
cccc send "announcement" --to @all  # explicit broadcast
cccc reply <event_id> "response"
cccc tail -n 50 -f             # follow the ledger

# Inbox
cccc inbox                     # show unread messages
cccc inbox --mark-read         # mark all as read

# Operations
cccc doctor                    # environment check
cccc setup --runtime <name>    # configure MCP
cccc runtime list --all        # available runtimes

# IM
cccc im set <platform> --token-env <ENV_VAR>
cccc im start|stop|status

MCP Tools

Agents interact with CCCC through a compact action-oriented MCP surface. Core tools are always present, and optional capability packs add more surfaces only when enabled.

Surface	Examples
Session & guidance	`cccc_bootstrap`, `cccc_help`, `cccc_project_info`
Messaging & files	`cccc_inbox_list`, `cccc_inbox_mark_read`, `cccc_message_send`, `cccc_message_reply`, `cccc_file`
Group & actor control	`cccc_group`, `cccc_actor`
Coordination & state	`cccc_context_get`, `cccc_coordination`, `cccc_task`, `cccc_agent_state`, `cccc_context_sync`
Automation & memory	`cccc_automation`, `cccc_memory`, `cccc_memory_admin`
Capability-managed extras	`cccc_capability_*`, `cccc_space`, `cccc_terminal`, `cccc_debug`, `cccc_im_bind`

Agents with MCP access can self-organize: read inbox state, reply visibly, coordinate around tasks, refresh agent state, and enable extra capabilities when the current job actually needs them.

Where CCCC Fits

Scenario	Fit
Multiple coding agents collaborating on one codebase	✅ Core use case
Human + agent coordination with full audit trail	✅ Core use case
Long-running groups managed remotely via phone/IM	✅ Strong fit
Multi-runtime teams (e.g., Claude + Codex + Gemini)	✅ Strong fit
Single-agent local coding helper	⚠️ Works, but CCCC's value shines with multiple participants
Pure DAG workflow orchestration	❌ Use a dedicated orchestrator; CCCC can complement it

CCCC is a collaboration kernel — it owns the coordination layer and stays composable with external CI/CD, orchestrators, and deployment tools.

Security

Web UI is high-privilege. Before non-local exposure, first create an Admin Access Token in Settings > Web Access.
Daemon IPC has no authentication. It binds to localhost by default.
IM bot tokens are read from environment variables, never stored in config files.
Runtime state lives in CCCC_HOME (~/.cccc/), not in your repository.
Capability allowlist governs which optional MCP surfaces agents can enable. Policy is composed from a packaged default and an optional user overlay in CCCC_HOME/config/.

For detailed security guidance, see SECURITY.md.

Documentation

📚 Full documentation

Section	Description
Getting Started	Install, launch, create your first group
Use Cases	Practical multi-agent scenarios
Web UI Guide	Navigating the dashboard
IM Bridge Setup	Connect Telegram, Slack, Discord, Feishu, DingTalk, WeCom, Weixin
Group Space	NotebookLM knowledge integration
ChatGPT Web Model Runtime	Connect ChatGPT Web / MCP-capable GPT-5.x as a CCCC actor; use GPT-5.x Pro for advisory review
Capability Allowlist	MCP capability governance
Best Practices	Recommended patterns and workflows
FAQ	Frequently asked questions
Operations Runbook	Recovery, troubleshooting, maintenance
CLI Reference	Complete command reference
SDK (Python/TypeScript)	Integrate apps/services with official daemon clients
Architecture	Design decisions and system model
Features Deep Dive	Messaging, automation, runtimes in detail
CCCS Standard	Collaboration protocol specification
Daemon IPC Standard	IPC protocol specification

Installation Options

pip (stable, recommended)

pip install -U cccc-pair

pip (RC from TestPyPI)

pip install -U --pre \
  --index-url https://test.pypi.org/simple/ \
  --extra-index-url https://pypi.org/simple/ \
  cccc-pair

From source

git clone https://github.com/ChesterRa/cccc
cd cccc
pip install -e .

uv (fast, recommended on Windows)

uv venv -p 3.11 .venv
uv pip install -e .
uv run cccc --help

Native Windows Notes

For local development on Windows, prefer the repo-root start.ps1.
If cccc doctor reports Windows PTY: NOT READY, run python -m pip install pywinpty or reinstall with uv pip install -e ..
Use scripts/build_web.ps1 for the bundled UI and scripts/build_package.ps1 for a full package build.

Docker

cd docker
docker compose up -d  # then create an Admin Access Token in Settings > Web Access before exposing beyond localhost

The Docker image bundles Claude Code, Codex CLI, Gemini CLI, and Factory CLI. See docker/ for full configuration.

Upgrading from 0.3.x

The 0.4.x line is a ground-up rewrite. Clean uninstall first:

pipx uninstall cccc-pair || true
pip uninstall cccc-pair || true
rm -f ~/.local/bin/cccc ~/.local/bin/ccccd

Then install fresh and run cccc doctor to verify your environment.

The tmux-first 0.3.x line is archived at cccc-tmux.

Community

📱 Join our Telegram group: t.me/ccccpair

Share workflows, troubleshoot issues, and connect with other CCCC users.

Contributing

Contributions are welcome. Please:

Check existing Issues before opening a new one
For bugs: include cccc version, OS, exact commands, and reproduction steps
For features: describe the problem, proposed behavior, and operational impact
Keep runtime state in CCCC_HOME — never commit it to the repo

License

Apache-2.0

Name		Name	Last commit message	Last commit date
Latest commit History 974 Commits
.github/workflows		.github/workflows
docker		docker
docs		docs
screenshots		screenshots
scripts		scripts
src/cccc		src/cccc
tests		tests
web		web
.dockerignore		.dockerignore
.gitignore		.gitignore
CHANGELOG.md		CHANGELOG.md
LICENSE		LICENSE
MANIFEST.in		MANIFEST.in
README.ja.md		README.ja.md
README.md		README.md
README.zh-CN.md		README.zh-CN.md
SECURITY.md		SECURITY.md
SUPPORT.md		SUPPORT.md
pyproject.toml		pyproject.toml
start.ps1		start.ps1

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CCCC

Local-first Multi-agent Collaboration Kernel

Why CCCC

The Problem

What CCCC Does

How CCCC looks

Quick Start

Install

Upgrade

Launch

Create a multi-agent group

Programmatic Access (SDK)

Architecture

Supported Runtimes

ChatGPT Web / GPT-5.x local development

Messaging & Coordination

Automation & Policies

Web UI

Remote access

IM Bridges

CLI Reference

MCP Tools

Where CCCC Fits

Security

Documentation

Installation Options

pip (stable, recommended)

pip (RC from TestPyPI)

From source

uv (fast, recommended on Windows)

Native Windows Notes

Docker

Upgrading from 0.3.x

Community

Contributing

License

About

Topics

Resources

License

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