MCP.Market

AI2Human MCP server

by richard7463·io.github.richard7463/ai2human-mcp·v0.1.2·1 stars
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Dispatch human-execution tasks with proof verification, local checks, and compliance reviews.

B74/100grade B
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Safety scan
B74/100

full report

Adoption
New

1 stars

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If you have run it, two minutes of your experience saves the next person an afternoon.

AI2Human tools (4, 1 write)

write = sends, deletes, buys or posts

Read from the package source without running it. The installed server may list more.

  • ai2human_check_task

    Check human execution, proof verification, and settlement state for a dispatched task.

  • ai2human_create_taskwrite action
  • ai2human_get_proof

    Retrieve the structured evidence bundle and recorded settlement receipt for a dispatched task.

  • ai2human_list_categories

    List supported reality-bound task categories and proof types before dispatching human work.

Public scan report

scanner v0.1.9 · 2026-09-25 · same rubric, same numbers if you re-run it

no findings
  • Code scan5 source files scanned25/25
  • –Live reliabilityno gateway calls yet and no remote to proben/a
  • –Tool poisoningtools not inspected (local package is not executed); not countedn/a
  • Auth qualitystatic API keys via environment variables6/15
  • Maintenancelast push 36 days ago12/15
  • Maintainer identitynamespace and repository owner differ; GitHub account older than a year5/10
Overall 74/100. Components that don't apply are left out of the denominator. Any critical finding is an F.RubricAppeal a findingJSON

How AI2Human compares

Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.

Safety score
74/100
higher than 40% of 48,255 servers
Tools
4
the typical server has 7
Tools that change things
25%
typical: 0%. Fewer write tools means less an agent can break
GitHub stars
1
more than 65% of 28,688 servers

What its tools let an agent do: 3 read · 1 change

Install AI2Human in Claude Code, Cursor or VS Code

claude mcp add ai2human-mcp -- uvx ai2human-mcp
Add to Cursor

What the publisher says

From the AI2Human repository's README, as published. We do not edit it. Read it on GitHub

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

Six Agent Roles

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

Shortened. The full README is on GitHub.

Nothing above is checked by us. What we check is on the safety report.

AI2Human: common questions

Is AI2Human MCP server safe?
Mostly: it is graded B (74/100). Read the AI2Human safety report
How do I install AI2Human?
It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
Does AI2Human need an API key?
Yes. The registry entry asks for AI2HUMAN_API_KEY, AI2HUMAN_AGENT_KEY.
Is AI2Human maintained?
The last commit was 75 days ago (2026-08-21). The latest release is v0.1.2.
How does AI2Human compare with other MCP servers?
safety score 74/100 (higher than 40% of 48,255 servers); tools 4 (the typical server has 7); tools that change things 25% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.