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cc-fleet

Skill Development Usable

🚢 Spawn any vendor LLM — DeepSeek · GLM · Qwen · Kimi · MiniMax … — as real Claude Code teammates or ⚡ one-shot subagents 🚀 |🤖 让 Claude Code 接入任意第三方模型(DeepSeek · GLM · Qwen · Kimi · MiniMax ……),作为原生 Agent Team Teammate 或 ⚡ 一次性 subagent 为你干活 🚀

110 starsApache-2.0 (commercial OK)FreeQuick setup
Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Enables teams to leverage multiple vendor LLMs within Claude's native agent framework, reducing dependency on single-model constraints and optimizing cost-to-capability tradeoffs for large-scale development workflows.

Engineering teams managing multi-model LLM deployments seeking vendor flexibility and cost optimization in AI-assisted code generation.

Claude Code Claude Cowork Claude Chat

https://github.com/ethanhq/cc-fleet

By ethanhq

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install ethanhq/cc-fleet

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Auto-scanned

Stars110Last updated2026-06-07LicenseApache-2.0 (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-06-07 · scanner v1

Community Pulse Emerging

Discussed on Hacker News

2 mentions across 1 sources

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 110 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
3/5
Versatility
3/5
Reliability
3/5
Security
3/5
Overall score3.00 / 5.00 UsableEvaluatedJun 2026
Scored from trust signals (evidence-eval-v1): 110 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.

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