The MCP server dispatches human-execution tasks with proof verification, including local checks and compliance reviews. It is described as “AI2Human — Human Fallback Infrastructure for AI Agents,” positioned as a two-way labor market connecting AI execution with required real-world handling.

🛠️ Key Features

Dispatch human-execution tasks
Proof verification
Local checks
Compliance reviews
Human fallback for AI agents

🚀 Use Cases

Human fallback when AI execution is blocked
Collecting and verifying proofs for completed tasks
Handling “reality required” steps in an execution/verification workflow

⚡ Developer Benefits

Structured proof and verification topics (e.g., structured-proof, verification-network)
Clear focus on human-verification and proof-verification for execution networks
Supports agent workflows involving human fallback and verification-network concepts

⚠️ Limitations

No tool count or specific MCP tools are provided in the available server data.

Catalog Metadata

Name: io.github.richard7463/ai2human-mcp
Topics: ai-agents, proof-verification, ai2human, human-verification, structured-proof, ai2humannetwork, agent-economy, execution-network, verification-network

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

code

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.

code

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

bash

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

env

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.

AI2Human