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gabyic/agentdock-mcp-harness

Use your ChatGPT or Claude Web quota for remote coding without a second server-side API token meter

⭐ 15 stars
⑂ 9 forks
JavaScript
momentum ▲ 48.0
created 2026-09-21
on radar since 2026-09-22
star trend 4 → 15 since 2026-09-22
chatgptcoding-agentgitmcpmodel-context-protocolsoftware-engineering
View on GitHub ↗

About agentdock-mcp-harness

把 ChatGPT / Claude 网页版的大额度、近似无限配额,变成你的远程 Coding Token 池。

Use your ChatGPT / Claude Web quota as a remote coding agent — no second API token meter.

如果你的 ChatGPT / Claude 网页套餐本身提供大额度或近似无限的使用量,AgentDock 就能让这部分现有配额直接驱动你自己 Linux 服务器上的真实开发流程,而不是再额外购买一套 Coding Agent API Token。

If your chat plan gives you high or near-unlimited usage, AgentDock lets that same chat-model quota drive real remote software engineering on your own Linux server.

No second coding model. No extra server-side AI API key. No separate per-token reasoning bill.

AgentDock keeps ChatGPT / Claude / another MCP-capable chat client as the only reasoning agent and adds the missing execution layer: Git worktrees, file editing, shell/process execution, tests, durable tasks, approvals, commits, host access, and audit.

Long coding tasks are token-hungry. A real debugging loop may repeatedly:

With an API-based coding agent, every reasoning loop consumes separately billed API tokens.

With AgentDock, the reasoning stays inside the chat product you already use. If your ChatGPT / Claude plan provides a large or near-unlimited chat allowance, that existing allowance becomes the reasoning budget for remote coding, while the server only executes deterministic MCP tools.

AgentDock does not claim that every chat subscription is literally unlimited. Plans can have usage, rate, or context limits. The value proposition is that AgentDock adds no second model/API token meter on the server.

From the project README.

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