Doubleoh Mcp

io.github.cheedliv0.1.1更新於 Sep 29, 2026

The fix desk for AI agents: human fixes become skills the whole fleet reuses.

已驗證STDIO僅桌面AI & ML

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Doubleoh Mcp,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

doubleoh-mcp

The DoubleOh fix loop as an MCP server. Any MCP-capable agent — Claude Code, Claude Desktop, and the growing list of clients — gets the loop as three tools with zero integration code.

json
{  "mcpServers": {    "doubleoh": {      "command": "bunx",      "args": ["doubleoh-mcp"],      "env": { "DOUBLEOH_API_KEY": "oo_live_…" }    }  }}

The tools

  • doubleoh_skills_for — before attempting a task it has failed at before, the agent asks what has been learned and receives step-by-step procedures from past human fixes, with each one's track record.
  • doubleoh_request_fix — when stuck, the agent asks for a human. If the fleet already knows the wall, the procedure comes back instantly instead and nobody is paged. Duplicate walls are answered with "already being fixed, N runs blocked" — an agent in a retry loop never spams a team.
  • doubleoh_report_skill — after following a skill, the agent reports whether it worked. Skills that keep failing stop being served.

Refusals (a private URL, a quota) come back as readable tool results, not protocol errors — the model is told what went wrong in a sentence it can act on.

DOUBLEOH_BASE_URL points at a self-hosted deployment; it defaults to the hosted service.

來源:packages/mcp/README.md,提交 1440780

工具

0
工具後設資料尚未被收錄。

版本歷史

1
  1. v0.1.1最新Sep 29, 2026