CCCC Coordination Console
Run coding agents as a durable, trackable team across runtimes, machines, and remote operations.
- Source repo
- ChesterRa/cccc
- Stars
- ★ 1.3k
- Last updated
- 1d ago
- License
- Apache-2.0
- Primary language
- Rust
- FA score
- 61/100 · Some gaps
At a glance
- How it runs
- Works with
- Universal · cross-platformCodex · Claude CodeChatGPT (Partial support)
- Cost
- Free software; you pay for model usage
- Setup effort
- Medium · a few setup steps
- You'll need
- Typical use
- An engineering lead coordinating Claude Code and Codex CLI on one repository, with explicit read receipts and validation handoffs.
- Not a fit if
- Users happy with one vendor's native agent team and no cross-runtime coordination
- Teams needing pure DAG workflow orchestration; use a dedicated orchestrator instead
- Source review
- 61/100 · Some gaps
What does this agent do, and when should you use it?
CCCC is a local-first coordination system for multi-agent software development, centered on a daemon that manages groups, actors, and message state. Its append-only JSONL ledger records messages and events, while a Web UI, CLI, MCP surface, and IM bridges use the same control plane. A group can combine 16 first-class runtimes, including Claude Code, Codex CLI, and ChatGPT Web, with a custom runtime path for other commands. It fits teams that need long-running coding work, auditable handoffs, and delivery/read/reply tracking, with runtime state stored in CCCC_HOME rather than the repository.
Run cccc attach . to bind a directory as the work scope, cccc setup to configure runtimes, and cccc actor add <id> --runtime <runtime> to create a foreman and peers. cccc group start launches actors; the daemon delivers cccc send and cccc tracked-send messages and appends messages and events to ledger.jsonl. Actors use the MCP collaboration core for inboxes, messaging, files, context, tasks, and state, while on-demand capabilities include cccc_repo, cccc_terminal, cccc_actor, cccc_automation, and remote-group access tools. The Web UI exposes chat, delivery/read state, embedded terminals, automation rules, and settings; bridges for Telegram, Slack, Discord, Feishu/Lark, DingTalk, WeCom, and Weixin expose coordination and status operations through IM.
- An engineering lead coordinating Claude Code and Codex CLI on one repository, with explicit read receipts and validation handoffs.
- A developer or team supervising long-running coding work from a phone through Telegram, Slack, or another supported IM bridge.
- A distributed team running CCCC groups on Windows, WSL, Macs, servers, or trusted teammate machines and using Group Bridge for explicit cross-group collaboration.
- An engineering organization that needs replayable message and event records to audit whether delegated work was delivered, read, acknowledged, and answered.
- A user who wants to bind a ChatGPT Web conversation as a development actor with browser delivery and a remote MCP connector.
How do you install or deploy this agent?
The default distribution requires Python 3.11+: pip install -U cccc-pair. The native Rust distribution requires Rust 1.88+: cargo install cccc --locked. Do not keep both cccc executables on PATH. Then run cccc; it starts the daemon and local Web UI by default. Open http://127.0.0.1:8848.
How do you use this agent?
From the target repository, run: cccc attach .; cccc setup; cccc actor add foreman --runtime claude; cccc actor add implementer --runtime codex; cccc group start. Send ordinary coordination with cccc send "Please inspect the repo and propose the first safe task." --to foreman. For a durable delegation, run 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". Run cccc doctor if an actor stays stopped. The ChatGPT Web runtime additionally requires exposing CCCC through a public HTTPS URL and configuring a remote MCP connector in one bound ChatGPT conversation.
What are this agent's strengths and limitations?
- A single-writer daemon and append-only ledger.jsonl provide replayable, auditable message and event state.
- Its coordination model includes routing, read cursors, attention acknowledgments, and reply-required obligations rather than only terminal prompting.
- Web UI, CLI, MCP, and IM bridges share daemon-owned state, supporting both local terminal control and phone-based operations.
- It supports 16 first-class runtimes plus custom, allowing combinations such as Claude Code, Codex CLI, and ChatGPT Web in one group.
- The default Python distribution requires Python 3.11+; the native distribution requires Rust 1.88+, and both cccc executables must not coexist on PATH.
- The ChatGPT Web runtime depends on browser delivery, remote MCP, and a public HTTPS exposure; GPT-5.x Pro sessions cannot use this integration.
- Daemon IPC has no authentication and binds to localhost by default; non-local Web exposure requires an Admin Access Token and a network boundary.
- Group Bridge read and full access can let trusted remote groups inspect context or operate on a workspace, so permissions require careful administration.
How does this agent compare with similar options?
Compared with native agent teams such as Claude Code subagents/teams, CCCC adds cross-runtime groups, state that survives restarts, phone/IM operations, and an audit ledger. Compared with isolated parallel task runners, it emphasizes messaging, handoffs, acknowledgments, and daemon-owned coordination; the README positions pure DAG orchestration as a case for a dedicated orchestrator.
Key facts side by side with the most closely related agents.
| Agent | Source review | Form / cost | Stars | Updated | Language | Full support on |
|---|---|---|---|---|---|---|
| CCCC Coordination Console This agent | 61 · Some gaps | CLIFree + model costs | ★ 1.3k | 1d ago | Rust | Codex · Claude Code |
| fkteams | 40 · Major gaps | CLIFree + model costs | ★ 157 | 2mo ago | Go | OpenAI API |
| Ouroboros Agent OS | 53 · Major gaps | CLIFree + model costs | ★ 6.3k | today | Python | Codex · Claude Code |
| CLI Agent Orchestrator | 65 · Some gaps | CLIFree + model costs | ★ 1.5k | today | Python | Codex · Claude Code |
How does FollowAgents rate this agent?
Why each dimension lost points
Evidence shows: README explicitly states Web UI is high-privilege and requires Admin Access Token; daemon IPC binds to localhost by default; IM tokens are read from environment variables; Group Bridge uses a trust model with explicit read/full authorization; capability allowlist governs MCP capabilities. This reflects least privilege. However, user confirmation is only mentioned for Group Bridge pairing and Web Access settings, not covering all high-risk operations, so user_confirmation scores 1. Data flow transparency: README describes ledger recording all messages and events, but does not detail data flow and storage locations, so scores 2. Sensitive data handling: IM tokens from env vars, runtime state in CCCC_HOME, but no mention of encryption, so scores 2. Dependency security: pyproject.toml lists dependency version ranges, CI has caching, but no vulnerability scanning evidence, so scores 2. External effects: Group Bridge allows remote operations but requires explicit authorization, and README warns against public exposure, so scores 2. Rollback: installer tests cover rollback, but no user-level rollback documentation, so scores 2. Source attribution: no contributor guide or author info, so scores 1.
Evidence shows: README and CI config are consistent, Python and Rust implementations coexist, but README clearly states Rust is experimental and Python is stable, reflecting self-consistency. Dependency availability: pyproject.toml lists dependencies, CI has caching, but no availability guarantee, so scores 2. Failure messages: README provides doctor command and FAQ, but no detailed error message examples, so scores 2.
Evidence shows: README defines target audience (multi-agent coordination) and multiple use cases, with a suitability table. Capability boundaries: README describes support for 17 runtimes and custom, and Group Bridge permission levels. Trigger precision: README describes message routing and automation rules, but no detailed trigger conditions, so scores 2. Environment fit: README provides multiple installation methods (pip, Docker, source) and supports multiple platforms, so scores 2.
Evidence shows: README is well-structured with quick start, architecture, CLI reference, etc., good information architecture. Install notes are detailed, including pip, Docker, source. Naming stability: version numbers consistent in Cargo.toml and pyproject.toml, but no naming convention doc, so scores 1. Examples and FAQ: README provides multiple examples and FAQ links, so scores 2. Known limitations: README mentions Rust implementation is experimental and some features unsupported, so scores 2. License: Apache-2.0 license file present, so scores 2. Versioning changelog: no CHANGELOG file, so scores 1. Maintenance responsibility: no maintainer info or contribution guide, so scores 1.
Evidence shows: README describes outputs (Web UI, CLI, MCP tools) and available features, output usability is good. Marginal value: compared to existing tools, CCCC provides cross-runtime coordination and persistent state, unique value. Cost-benefit: simple installation, no extra infrastructure, but learning curve, so scores 2.
Evidence shows: README claims (e.g., support for 17 runtimes) have corresponding documentation, but no independent verification. Cross-source corroboration: CI config and test scripts provide partial verification, but no external verification, so scores 1. Fact-inference separation: README clearly distinguishes stable and experimental features, so scores 2.
- Web UI is high-privilege; must set Admin Access Token before exposing publicly to prevent unauthorized access.
- Group Bridge read/full permissions should be granted cautiously, only to trusted remote groups.
- Rust implementation is experimental; use Python stable version for production.
- Dependency security lacks vulnerability scanning evidence; recommend checking dependencies for vulnerabilities.
Recent releases
Latest entries from the project's GitHub Releases. Notes are quoted from upstream as written, not rewritten or tested by FollowAgents.
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v0.4.48 CCCC 0.4.48
Release notes excerpt
CCCC v0.4.48 Release Notes CCCC v0.4.48 lets you switch the runtime that runs an agent, between native sessions and CCCC-managed runtimes, without losing the agent or automatically resending a message whose delivery is uncertain; see [Switch an Agent's Runtime](#switch-an-agents-runtime). It also keeps more of your work when something goes wrong. A Web send whose result never came back can be restored, and sending it again unchanged does not create a duplicate. Voice recordings keep the words already recognized in more of the ways they can end early, and a stopped voice model download can …View on GitHub ↗ -
v0.4.47 CCCC 0.4.47
Release notes excerpt
CCCC v0.4.47 Release Notes CCCC v0.4.47 introduces Chet, a global assistant you can use by text or voice, message pins, quick replies, and a redesigned Web interface. Managed Claude agents can show Claude's own workspace-trust and permissions confirmation in their terminal. This release also improves message navigation and process recovery and fixes access-control and Group-copy problems. This release covers the changes since v0.4.46; see [Before You Upgrade](#before-you-upgrade) before installing. Before You Upgrade …View on GitHub ↗ -
v0.4.46 CCCC 0.4.46
Release notes excerpt
CCCC v0.4.46 Release Notes CCCC v0.4.46 lets the Codex, Claude Code, Pi and OpenCode sessions you already run work together through CCCC, and adds a terminal interface to a bare cccc. Agents can ask you to decide between options that you answer under the message, browsers can show system notifications for messages and requests waiting for you, and the Web chat gives messages more room on phones. The task board shows more about each task without opening it. This release covers the changes since v0.4.45. **Two changes need attention …View on GitHub ↗