by amirfish1
Manage and orchestrate your Claude Code, Codex, Cursor, Antigravity, Kimi, Grok, Devin, Droid sessions on your Machine. Spawn in parallel, ship in parallel. Open source.
# Add to your Claude Code skills
git clone https://github.com/amirfish1/claude-command-centerGuides for using ai agents skills like claude-command-center.
Last scanned: 8/2/2026
{
"issues": [
{
"file": "README.md",
"line": 533,
"type": "secret-exfiltration",
"message": "Instruction appears to send credentials/secrets to an external endpoint",
"severity": "medium"
},
{
"file": "README.md",
"line": 118,
"type": "remote-install",
"message": "Install command (remote install script piped to a shell — review the source before running): \"curl | bash\"",
"severity": "low"
},
{
"file": "README.md",
"line": 312,
"type": "dangerous-command",
"message": "Dangerous command (writes to Claude config): \"> │ ~/.claude/\"",
"severity": "medium"
}
],
"status": "PASSED",
"scannedAt": "2026-08-02T06:31:38.813Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}See how claude-command-center compares with popular alternatives.
claude-command-center is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by amirfish1. Manage and orchestrate your Claude Code, Codex, Cursor, Antigravity, Kimi, Grok, Devin, Droid sessions on your Machine. Spawn in parallel, ship in parallel. Open source. It has 157 GitHub stars.
Yes. claude-command-center passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/amirfish1/claude-command-center" and add it to your Claude Code skills directory (see the Installation section above).
claude-command-center is primarily written in Python. It is open-source under amirfish1 on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh claude-command-center against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
See comparison
Your coding agents outgrew your terminal.
CCC puts every session on one local board and tells you which one needs you.
Start the next while Claude builds the first.
“Hey Amir, great product. I tried about 20 before finding yours. I have been really enjoying it.”
— CCC user
One local dashboard that attaches to every Claude Code, Codex, Cursor, Antigravity, Kilo Code, Kimi Code, OpenCode, and Devin session on your machine, however you launched it — plus read-only ingestion of GitHub Copilot CLI, VS Code Copilot Chat, and Grok CLI sessions. Spawn, monitor, and ingest all eight; steer seven of them with follow-up. Local, source-available, free for non-commercial use.
📢 Shipping fast. Watch → Releases (top-right) to get pinged on new versions without the noise.

Install with curl:
curl -fsSL https://raw.githubusercontent.com/amirfish1/claude-command-center/main/scripts/install.sh | CCC_FROM=readme bash
With Homebrew:
brew tap amirfish1/ccc
brew install ccc
ccc
Or download the macOS DMG and drag CCC.app to Applications:
github.com/amirfish1/claude-command-center/releases/latest
Try the read-only demo first: ccc.amirfish.ai/demo (or amirfish1.github.io/claude-command-center/demo) - the full dashboard with seeded fake data, no install required.
Every Claude Code, Codex, Cursor, Antigravity, Kilo Code, Kimi Code, OpenCode, and Devin session lands on one board — however you launched it. CCC reads each engine's on-disk state, so even sessions you started by hand in a terminal show up.
Group sessions under named, nestable Flow objects — a hierarchical map of your day's work, with a live "Current sessions" triage band riding on top.
Drag any session onto the edge of an open transcript to read two agents side by side — each pane keeps its own input bar.
Full-text search across your entire session history, built in and zero-setup — with an optional semantic mode for when you can't remember the words you used.
Group chats keep two sessions on one goal in sync — post once and every participant is pinged, instead of you relaying output between terminals.
File work into named WatchTower queues instead of remembering what to ask which session. Tickets survive closed sessions, workers drain them in parallel, and the queue inbox shows what needs you.
Each worker reads its queue's shared learnings file before it starts and writes back when it ends, so a queue handling the same kind of ticket for months keeps getting faster, not just busier.
The whole fleet on your phone — monitor sessions, answer agents, and steer from anywhere on your trusted network. Loopback by default, never the open internet.
Also in the box:
<repo>-wt/<slug>/ on feat/<slug>, with optional init scripts.claude -p sessions you keep talking to from the browser, no terminal needed./fix-deploy session on new production errors.claude -p (Haiku by default).~/.claude/command-center/model-policy.json blocks models across every picker, spawn path, and queue; WatchTower workers honor it too./compact as a card — one self-narrating card with stage names, a live clock, and the tokens-freed payoff, instead of a spinner that could report a slow compaction as failed.ccc spawn and queue lanes appear in the list the moment they start.All captures use seeded demo data.
CCC latches onto every Claude Code, Codex, Cursor, Antigravity, Kilo Code, Kimi Code, OpenCode, and Devin session on your machine: terminal sessions, headless processes, and sessions you spawned from the dashboard. It treats each agent's on-disk state as the source of truth, so nothing slips through. Spawn the next task while the first is still building. Switch between projects without losing context. Ship multiple things at once.
See the engine support matrix below for what each engine does. Spawn, monitor, and transcript ingestion work across all eight; follow-up (steering a dormant session) works on seven (Kilo Code is fire-and-forget), and Cursor IDE sync is metadata-only by design.
See your whole fleet, past one session. The way you build faster is a session per workstream: one on the feature, one on its go-to-market, one on the next feature, one on research. CCC puts every model and engine on one board, every row enriched so you read status without clicking in: a needs-you signal, live context left, a cost tier, and, with the Token Optimizer plugin, a quality score. Pin strategy sessions, nest workers under them, group by project, or lay the whole fleet out on a canvas.
Stop wasting tokens, keep quality where it matters. Your best model leads; execution fans out to cheaper models, or another platform entirely, through spawns, queues, and workers you point at any engine. CCC shows your pace against your plan's limits before you hit the wall, attributes a spend spike to the exact session or automation that caused it, and flags sessions running on a tier they don't need.
Sessions that exchange context on their own. Two sessions on one goal stay in sync through group chats and a sibling-ask API, instead of you reading one agent's output off one screen and retyping it into the other. Post once and every participant is pinged; ask a sibling synchronously when you need an answer right now; hand a problem to a fresh spawned session that reports back when it finishes.
Workers that specialize over time. Each worker reads its queue's shared learnings file before it starts and writes back to it