withHuman

ai.withhuman由 withhuman.ai 發布官方發布者v1.0.0更新於 Nov 4, 2026

Set up human approval for your AI agents' tool calls.

已驗證Streamable HTTP可網頁執行效率與工作流開發者工具安全與監控

概覽

AI 產生的概覽

withHuman 是一層審批機制,讓助理在執行有後果的工具呼叫前,交由人工核准、拒絕或自動放行。

可以做什麼
  • 在執行前依審批規則檢查代理的工具呼叫
  • 依工具與其參數自動核准、拒絕或轉交人工決定
  • 透過電子郵件、Slack 或 Discord 通知審核者,並依團隊、層級與工作時間升級
  • 讓審核者在網頁應用中看到完整呼叫參數後作出決定
  • 透過轉接器與 SDK 接入編碼代理與自建框架
適用情境
當助理需要執行退款、部署回復或合併程式碼等實際操作,且高風險動作必須先由人確認時使用。適合希望集中定義哪些代理動作自動執行、哪些被禁止、哪些等待審核的團隊。
執行需求
託管版為遠端端點,需要 OAuth 登入。自架需要 Docker(或以 Go 與 Node 從原始碼執行)與 bootstrap 密鑰;在自有機器之外使用時還需 HTTPS 反向代理、WITHHUMAN_PUBLIC_ORIGIN、WITHHUMAN_TRUSTED_PROXIES、WITHHUMAN_SECRETS_KEY、SMTP 設定以及資料目錄備份。代理透過 withhuman CLI 或 AAP SDK 接入。
安裝前請注意
它位於會改變狀態的操作之前,規則設定不當可能放行高風險呼叫或攔截例行呼叫。自架需妥善保護 WITHHUMAN_SECRETS_KEY 與 bootstrap 密鑰,並備份資料目錄。自架版本每天傳送包含安裝 ID、版本與平台的遙測資料,除非設定 WITHHUMAN_TELEMETRY=off 或 DO_NOT_TRACK=1。託管版另提供稽核記錄、AI 判定、MCP 閘道、電話通知與單一登入。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 withHuman,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/ai.withhuman%2Fwithhuman/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "mcpServers": {
    "withhuman": {
      "type": "http",
      "url": "https://app.withhuman.ai/api/mcp/v1"
    }
  }
}

README

[withHuman] [withHuman]

Approval layer for AI Agents
Put your most consequential agent actions behind human approvals, so your agents can do real work.

[Latest release] [Release build] [Docker image] [Go version] [License: Elastic 2.0] [Agent Approval Protocol] [Chat on Discord] [Follow @withHumanAI on X]

Website · Docs · Quickstart · Protocol · Discord · Contributing


We want agents to do more than read data and suggest what to do next. They should be able to roll back a deployment, issue a refund, or merge code. Those actions have consequences, and teams need a way to bring a person in before they happen.

withHuman is the approval layer for that moment. It checks an agent's tool call before it runs against rules you define in one place. Routine calls can be approved automatically, disallowed calls can be denied, and consequential ones can wait for the right person to decide. Every agent you connect follows those rules.

[The review page for a pending issue_refund request: its arguments, the agent's explanation, and Deny and Approve buttons] [The review page for a pending issue_refund request: its arguments, the agent's explanation, and Deny and Approve buttons]

How it works

An adapter (a runtime hook or an SDK wrapper) sends each tool call to withHuman before it runs, over the open Agent Approval Protocol.

mermaid
sequenceDiagram    participant Agent as Your agent    participant WH as withHuman    participant You as You    Agent->>WH: Wants to call issue_refund(amount: 75)    WH->>WH: Checks your approval pipeline    WH->>You: Asks for approval by email, Slack or Discord    You->>WH: Approve    WH->>Agent: Go ahead    Agent->>Agent: Runs issue_refund
  • Approval pipelines approve, deny or ask a person, based on the tool and its arguments. For example: approve refunds up to $20, ask payments above that.
  • Escalation paths choose who is asked and when, by team, level and working hours. Reviewers get email, Slack or Discord and decide in the web app with the exact arguments in front of them.

See How withHuman works for how the pieces fit together.

Quickstart

You need Docker.

sh
docker run -d --name withhuman -p 8080:8080 -v withhuman-data:/data quay.io/withhuman/bundle:latestdocker exec withhuman cat /data/bootstrap-secret

Open http://localhost:8080, choose First setup and enter the secret. The welcome page connects your first agent and ends with a test call for you to approve. The quickstart guide covers each step.

To run from source instead, install Go (the version in go.mod) and Node 25, then run make frontend && go run ./cmd/withhuman. The secret is in ~/.withhuman/bootstrap-secret.

Connect your agents

  • Coding agents. Claude Code, Codex, OpenClaw, Pi, Hermes and DeepSeek connect with the withhuman CLI:

    sh
    curl -fsSL https://downloads.withhuman.ai/install.sh | shwithhuman agent install --url https://approvals.example.com
  • Agents you build. LangGraph, Pydantic AI, the OpenAI Agents SDK, CrewAI, Mastra and other frameworks connect through the AAP SDKs. See the examples.

Explore further

Agent skills

Teach your coding agent to connect runtimes and write approval pipelines:

sh
npx skills add https://withhuman.ai

The skills live in skills/.

Deploy

Settings are environment variables, listed in .env.example. Before you go beyond your own machine:

  1. Serve it behind HTTPS and set WITHHUMAN_PUBLIC_ORIGIN to that origin.
  2. Set WITHHUMAN_TRUSTED_PROXIES to your proxy's addresses only.
  3. Set WITHHUMAN_SECRETS_KEY and keep it safe.
  4. Configure SMTP so invitations and password resets reach people.
  5. Back up the whole data directory.
  6. Set OTEL_EXPORTER_OTLP_ENDPOINT to collect its OpenTelemetry metrics.

Don't want to run it yourself? withhuman.ai hosts it and adds the audit log, the AI judge, the MCP gateway, phone notifications and single sign-on.

Telemetry

Once a day withHuman sends a random installation ID, its version, the platform and whether it runs as a binary, a container or on Kubernetes. The answer tells administrators about new releases and security fixes on the Version settings page. Nothing about your organizations, people, agents or requests is sent. Set WITHHUMAN_TELEMETRY=off (or DO_NOT_TRACK=1) to turn it off. See Updates and telemetry.

Community

License

withHuman is licensed under the Elastic License 2.0.

來源:README.md,提交 74b8b42

工具

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版本歷史

1
  1. v1.0.0最新Oct 14, 2026

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