AI2Human

Name: AI2Human
Author: ai2humanagent

作者：ai2humanagent版本 0.1.2i★ 1i在你的电脑上运行

注册名称io.github.richard7463/ai2human-mcp

安装

概览

作者提供的说明（英文原文）

Dispatch human-execution tasks with proof verification, local checks, and compliance reviews.

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i2 项中通过 1 项依据公开信息检查；尚未扫描代码
使用情况i非常新↓ 23/周 · ★ 1

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 法律与政府数据
你需要填写：AI2HUMAN_API_KEY, AI2HUMAN_AGENT_KEY

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：2 项中通过 1 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
需要你自己填写： AI2HUMAN_API_KEY, AI2HUMAN_AGENT_KEY, AI2HUMAN_BASE_URL

标为机密的值是你账户的钥匙。千万不要分享给别人，也不要粘贴到聊天里。

你需要

PyPI已安装 Python 的 uv（用于 uvx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "ai2human": {
      "command": "uvx",
      "args": [
        "ai2human-mcp"
      ],
      "env": {
        "AI2HUMAN_API_KEY": "your-value",
        "AI2HUMAN_AGENT_KEY": "your-value",
        "AI2HUMAN_BASE_URL": "your-value"
      }
    }
  }
}

在终端中运行这条命令

claude mcp add ai2human --env AI2HUMAN_API_KEY=your-value --env AI2HUMAN_AGENT_KEY=your-value --env AI2HUMAN_BASE_URL=your-value -- uvx ai2human-mcp

运行前请先填写空着的值。

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "ai2human": {
      "command": "uvx",
      "args": [
        "ai2human-mcp"
      ],
      "env": {
        "AI2HUMAN_API_KEY": "your-value",
        "AI2HUMAN_AGENT_KEY": "your-value",
        "AI2HUMAN_BASE_URL": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "ai2human": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "ai2human-mcp"
      ],
      "env": {
        "AI2HUMAN_API_KEY": "your-value",
        "AI2HUMAN_AGENT_KEY": "your-value",
        "AI2HUMAN_BASE_URL": "your-value"
      }
    }
  }
}

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

需要你填写的值

AI2HUMAN_API_KEY 机密必填 env
AI2Human agent API key for authentication
AI2HUMAN_AGENT_KEY 机密 env
Optional fallback for API key
AI2HUMAN_BASE_URL env
Override the default AI2Human API base URL

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档，检查于 2026年11月10日。

在你的电脑上运行，适用于

Claude Goose LM Studio Msty Studio Cherry Studio Cursor VS Code + GitHub Copilot Visual Studio Windsurf (Devin Desktop)Zed Kiro Cline Continue JetBrains AI Assistant Claude Code Codex CLI Gemini CLI OpenCode nodecode Warp LibreChat Raycast

全部应用及其优缺点 →

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月10日

! 注意
作者与仓库一致
发布者（richard7463）不是仓库所有者（ai2humanagent）；可能是其他人代为上架的
✓ 通过
仍在维护
代码最后更新于3个月前
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“法律与政府数据”中的其他服务器比较i

星标数多于此分类中其他 1792 个服务器的 0%
发布到注册中心的时间比此分类中其他 1792 个服务器的 19% 更新
基础检查结果等于或优于此分类中其他 1792 个服务器的 14%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

AI2Human 安全吗？

它在 2 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

你需要填写：AI2HUMAN_API_KEY, AI2HUMAN_AGENT_KEY

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于3个月前，最新版本（0.1.2）于4个月前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。

有什么可以替代它？

同一分类中有：Korean Law MCP, Tw Legal Rag, Parse-DMARC MCP Server

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Korean Law MCP

Korean law: statutes, precedents, ordinances, treaties and citation verification (법제처 API).

作者：chrisryugj广泛使用★ 28557天前更新

在云端运行

安装

Tw Legal Rag

Taiwan law MCP server: 22M court judgments, statutes, agency rulings, with citation checks

作者：aa0101181514正在增长★ 3454天前更新

在云端运行

安装

Parse-DMARC MCP Server

Lightweight DMARC parser: auto-fetch email reports, visualize compliance in a single all-in-one app

作者：meysam81正在增长★ 2319个月前更新

在你的电脑上运行

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

AI2Human — Human Fallback Infrastructure for AI Agents

Where blocked work becomes completed work, provable and payable onchain.

Website: ai2human.work | Whitepaper: ai2human.work/whitepaper

What Is AI2Human

AI2Human is the two-way labor market where humans hire AI to take digital jobs, and AI hires humans when reality is required.

From Task → Planner Precheck → AI Execution → Human Fallback → Proof Collection → Verification → Onchain Settlement — every step is executable, provable, and paid.

We are not building a chatbot. We are building an execution market. Our thesis is simple: the market does not need more generated answers. It needs completed tasks.

Most AI products stop at output. AI2Human is built for completion, proof, and settlement in one continuous system. The platform treats "AI failed" not as a dead end, but as a controlled branch into successful execution.

The Problem: The Execution Gap

The real bottleneck is not intelligence. It is execution continuity.

Tasks break when AI hits reality constraints:

CAPTCHAs and identity-bound actions
Signatures, on-site checks, physical verification
Compliance gates, merchant coordination

These are steps that software alone cannot finish. Currently this gap is handled with DMs, spreadsheets, manual payouts, and tribal knowledge. One team's work does not compound.

The Core Loop

Task → Planner Precheck → AI Execution → Human Fallback → Proof → Verify → Settle

Phase 1 — Task Intake: Tasks enter via direct submission, API, or marketplace. Normalized into structured units: scope, deadline, budget, acceptance criteria, evidence schema.

Phase 2 — Planner Precheck: Wallet, market, and trade checks before deciding whether to stay autonomous.

Phase 3 — AI Execution: AI-first path by default. OpenClaw-powered browser automation, web workflows, form filling.

Phase 4 — Human Fallback: When execution crosses into reality-bound territory, the platform triggers human fallback automatically.

Architecture: Eight Core Layers

Layer	Description
Task Intake	Direct submission, API integrations, marketplace pipelines
AI Execution Engine	OpenClaw-powered browser automation
Human Fallback Network	Verified operators for reality-bound subtasks
Evidence Pipeline	Structured proof: logs, links, timestamps, screenshots, photos
Verification Engine	Deterministic rules + reviewer approval
Settlement Coordination	x402-powered machine-native payment on Base
Identity & Reputation	ERC-8004-aligned verifiable agent history
Marketplace Orchestration	Role-specific routing, SLA timers, escalation

Six Agent Roles

Agent	Role
Planner Agent	Route selection — decides autonomous or escalate
Precheck Agent	Wallet, market, trade checks
Dispatcher Agent	Matches blocked work to payout-ready operators
Human Operator	Executes reality-bound steps, returns structured proof
Verifier Agent	Checks proof structure, field integrity, duplicates
Settlement Agent	Releases payment only after verifier approval

Onchain Settlement on Base

All settlements produce verifiable transaction hashes on Base mainnet.

Treasury top-up:  0x3fe5b99b2af4934c3b30d3087a703157e4f7cfcb8fc5dc58cecb48e249788f5e

Settlement tx: 0xee543bc107b411edd0202131b82172eb6efaf29c10457e33d2900ae890a72cf0 Settlement wallet: 0x3f665386b41Fa15c5ccCeE983050a236E6a10108 Asset: USDC on Base mainnet

Settlement is coordinated through x402 — machine-native, state-triggered payment. No "analysis-only" outputs. Every task is replayable with evidence.

Task Marketplace

Browse, claim, and complete tasks at ai2human.work/tasks.

Multi-Mode Reward Distribution

Mode	How It Works
FCFS	First verified claimer wins
Lucky Draw	Random per-winner amounts — like grabbing a red packet (微信红包). Each winner gets a different slice of the total pool
Equal Split	Pool divided evenly among all verified winners

Task Categories

Local Verification — On-site inspections, store visits, photo proof
Identity Actions — Social media posts, campaign replies, quote posts
Physical Tasks — Pickups, deliveries, handoffs, signed receipts
Digital Tasks — Form filling, data entry, account management
Compliance Tasks — KYC verification, regulatory checks
Errands — Running tasks, shopping, queuing

Target Users

Role	Description
Task Posters	Businesses, AI agents, developers. Define requirements, set budgets.
Human Operators	Anyone with skills. Complete reality-bound subtasks and earn USDC.
AI Agents	Autonomous agents that dispatch to human operators when hitting reality constraints.
Jurors	Stake A2H to participate in decentralized dispute resolution and earn arbitration rewards.

Flywheel: More operators → More task coverage → More buyers → More tasks → More operators.

Tech Stack

Frontend: Next.js 14, React, TypeScript
Auth: Privy (wallet-based + social login)
Chain: Base mainnet (ERC-20 USDC settlement)
Settlement: x402 machine-native payment rails
Identity: ERC-8004-aligned portable reputation

Getting Started

git clone https://github.com/ai2humanagent/ai2humanwork.git

cd ai2humanwork npm install npm run dev

Open http://localhost:3000 to browse tasks, or http://localhost:3000/app/profile to set up your operator profile.

Environment Variables

BASE_SETTLEMENT_PRIVATE_KEY=<your settlement wallet key>

BASE_RPC_URL=https://mainnet.base.org BASE_SETTLEMENT_TOKEN_ADDRESS=0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913 BASE_SETTLEMENT_TOKEN_SYMBOL=USDC

The Rule

No "analysis-only" outputs. If work is not completed, it is not done. Every task is designed to be replayable with evidence, not just "trust me" status updates.