AI Proof of Us MCP Server

AI Proof of Us MCP Server

Records privacy-preserving receipts for AI-assisted tasks and enables optional onchain reward claiming via AIPOU tokens. Integrates with MCP-compatible clients like Claude and Cursor.

Category
访问服务器

README

AI Proof of Us

AI Proof of Us is an MCP-first receipt protocol for humans working with AI.

It starts from a simple belief: when people spend real hours building, debugging, researching, writing, and coordinating through AI agents, that work should be able to leave a private, portable receipt.

AIPOU gives Codex, Claude, Cursor, OpenClaw, local models, and other MCP-compatible clients a shared way to create signed, privacy-preserving receipts for AI-assisted tasks.

The human reward loop is the point: people can keep receipts for the work they do with AI all day, and validator-approved receipts can claim AIPOU on Base. The protocol exists to make that claimable work more honest, portable, and useful across agents.

The developer surface is intentionally small: receipts, hashes, lifecycle hooks, and workReceiptId interoperability. Agents, marketplaces, and services can also reference AIPOU receipts or voluntarily accept AIPOU as settlement when both sides agree to use it.

The first version ships as:

  • an MCP server that records privacy-preserving AI task receipts
  • an installable OpenClaw skill for agent workflows
  • docs for MCP clients, agent builders, lifecycle adapters, anti-abuse, and future attestation design
  • a reward model that converts valid receipts into claimable emissions
  • an ERC-20 reward token on Base: AI Proof of Use (AIPOU)

The core idea is simple:

agent starts task -> MCP creates nonce -> AI work happens -> signed receipt -> validator checks -> optional AIPOU claim

Start here if you are building or testing an agent integration:

Read From AI Work to Onchain Rewards for the complete journey, global farming workflow, reward calculation, and one-command claim experience. Read Human Rewards and Agent Payments for the human reward loop and experimental agent-payment framing. Read AIPOU Tokenomics and Launch Transparency for supply, pool, reward, and experimental launch details. Read Evidence Boundaries and Claim Validation Policy before proposing integrations with receipt, provenance, security, or payment projects.

Official website: https://0xddneto.github.io/AI-Proof-of-Us/ Public explainer: https://huggingface.co/spaces/0xddneto/AI-Proof-of-Us

Official project contact: aipou001@gmail.com

This is not "AI usage mining" and it is not meant to reward raw prompt spam or attract passive token speculation. AIPOU is for humans doing real work with AI and for developers who want to test whether that work can produce portable receipts across agent clients.

In plain language:

Humans work with AI -> agents create receipts -> approved receipts claim AIPOU -> agents and marketplaces may accept AIPOU as settlement.

Base mainnet deployment

Contract: 0x55f0Cc5e51A1284D20337d6cbb18938C8A1ABCbB
Chain:    Base Mainnet (8453)
Token:    AI Proof of Use (AIPOU)
Supply:   100,000,000 AIPOU
Cap:      1,000,000,000 AIPOU
Logo:     assets/token/aipou.png
  • Contract: https://basescan.org/token/0x55f0Cc5e51A1284D20337d6cbb18938C8A1ABCbB
  • Verified source: https://repo.sourcify.dev/contracts/full_match/8453/0x55f0Cc5e51A1284D20337d6cbb18938C8A1ABCbB/
  • Token list: https://raw.githubusercontent.com/0xddneto/AI-Proof-of-Us/main/tokenlist.json
  • BaseScan SVG logo: https://raw.githubusercontent.com/0xddneto/AI-Proof-of-Us/main/assets/token/aipou-32.svg
Claims:   0x4ca4C98fB784D20EdC8E2A7F531dAab4c6e53058
Proof:    EIP-712 + Ed25519 + Merkle
Replay:   blocked by nonce and receiptId
  • Claims contract: https://basescan.org/address/0x4ca4C98fB784D20EdC8E2A7F531dAab4c6e53058
  • Verified claims source: https://repo.sourcify.dev/contracts/full_match/8453/0x4ca4C98fB784D20EdC8E2A7F531dAab4c6e53058/

Aerodrome liquidity pool

Pool:       0x3bEA7b68Af54Da779454f82148Ef848c76F78D02
Pair:       AIPOU/WETH
Type:       Volatile
Initial LP: 100,000,000 AIPOU + 0.000632035343416403 ETH
  • Pool: https://basescan.org/address/0x3bEA7b68Af54Da779454f82148Ef848c76F78D02

This pool was initialized with intentionally minimal ETH liquidity. Its price is highly volatile and easy to move; it should not be treated as a reliable market price until deeper liquidity is added.

The initial experimental pool buy was later returned through Aerodrome so the large early purchase would not remain as a misleading concentrated holder balance. See AIPOU Tokenomics and Launch Transparency.

Repository layout

contracts/     ERC-20 token, deploy scripts, Hardhat tests
mcp-server/    MCP server that records AI task receipts
docs/          architecture, anti-abuse model, Base launch notes
skills/        installable agent skills, including OpenClaw
huggingface-space/  static public protocol explainer

Token

Name:   AI Proof of Use
Symbol: AIPOU
Chain:  Base
Cap:    1,000,000,000 AIPOU

The token emission controller is AIPOUClaims. It mints only receipts included in a validator-published Merkle root and rejects a receiptId after its first claim.

AIPOU claims are optional settlement for approved receipts. They do not prove hidden AI use, objective task value, provider endorsement, provider inference without cryptographic provider evidence, or security-policy compliance.

MCP server

The MCP server exposes tools for creating task receipts:

  • get_aipou_contract
  • get_aipou_identity
  • estimate_ai_reward
  • begin_ai_task
  • complete_ai_task
  • export_ai_receipts
  • get_aipou_status (recorded, pending, claimed, and onchain balance summary)
  • settle_ai_rewards (one limited validator batch)
  • settle_all_ai_rewards (one-command claim path for all pending eligible receipts)

Receipts store hashes and metadata, not raw prompts or model outputs.

The dedicated farming key signs EIP-712 authorizations locally. Never paste it into a chat or use a primary wallet. The collector has a separate Ed25519 key that cannot move funds.

Frameworks do not need to understand Merkle trees, Base, or token claims to integrate the receipt layer. The minimal adapter watches task start and task end, records provider/model metadata and hashes, and exposes the AIPOU receiptId as workReceiptId for workflow metadata, traces, UI, audit exports, payment/session records, or later optional settlement.

Quick start

Test The Receipt Adapter

This is the fastest path for maintainers and agent-framework builders. It creates a local receipt with an ephemeral wallet and prints the workReceiptId object that a framework can attach to run metadata, traces, audit exports, or payment/session metadata.

npm install
npm run build -w mcp-server
cd examples/lifecycle-adapter
npm install
npm run demo

No claim is made. No funds move. No raw prompt or output is uploaded.

Run The MCP Server

Install dependencies:

npm install

Build all packages:

npm run build

Run contract tests:

npm run test -w contracts

Run the MCP server locally:

npm run dev -w mcp-server

MCP clients can launch the published server with:

npx -y aipou-mcp-server

Publication status: aipou-mcp-server@0.2.0 is published on npm and io.github.0xddneto/ai-proof-of-us@0.2.0 is published to the official MCP Registry. See docs/npm-publication.md.

Local MCP config example

Keep the farming private key in a .env file next to the repo and point the server at it with DOTENV_CONFIG_PATH. Never paste the private key into the MCP client config itself: client configs are often synced, logged, or read by other tools.

{
  "mcpServers": {
    "aipou": {
      "command": "node",
      "args": ["/path/to/AI-Proof-of-Us/mcp-server/dist/index.js"],
      "env": {
        "DOTENV_CONFIG_PATH": "/path/to/AI-Proof-of-Us/.env",
        "AIPOU_DATA_DIR": "/path/to/AI-Proof-of-Us/.aipou"
      }
    }
  }
}

The .env file holds AIPOU_AGENT_PRIVATE_KEY and AIPOU_CLAIMS_ADDRESS. On the validator machine, keep the validator key out of that shared .env: store it in a separate file and reference it with AIPOU_VALIDATOR_KEY_FILE so farming-only processes never load it.

Reward flow

  1. The agent calls begin_ai_task and signs a unique nonce with its farming wallet.
  2. The client collects usage and calls complete_ai_task with the output hash.
  3. The MCP derives the trust tier and signs the receipt with Ed25519.
  4. The validator rejects repeated nonces and repeated task/output evidence.
  5. get_aipou_status lets the user see how much has already been recorded, claimed, and left pending.
  6. After an explicit settlement request, settle_all_ai_rewards processes all currently eligible pending receipts from the shared AIPOU_DATA_DIR in bounded batches.
  7. AIPOUClaims rejects claimed receipt IDs and mints AIPOU to each farming wallet.

Users should normally ask for status first, for example show my AIPOU status, to see already claimed rewards, pending receipts, and the farming wallet's onchain balance. An explicit request such as claim my AIPOU is the trigger for settlement only when pending eligible receipts exist. Broad claim requests use settle_all_ai_rewards; settle_ai_rewards remains available for a single limited batch. The MCP client and its user keep the final say on how on-chain transactions are confirmed; the server never asks a client to skip its own confirmation policy. The validator can optionally enforce a settlement policy (minimum work floor per receipt via AIPOU_MIN_RECEIPT_TOKENS, per-wallet daily receipt limit via AIPOU_MAX_DAILY_RECEIPTS_PER_WALLET); both checks are disabled by default.

The trust tier is derived by the MCP and recomputed by the validator. Users cannot self-report provider_signed; a provider tier requires a valid provider signature from a configured public key.

See docs/base-launch.md for the deployment checklist.

Public launch

  • Hugging Face Space: https://huggingface.co/spaces/0xddneto/AI-Proof-of-Us
  • Reddit announcement: https://www.reddit.com/user/Any_Praline805/comments/1uklabn/i_built_an_open_mcp_protocol_that_rewards/
  • Outreach kit: docs/outreach
  • Official contact: aipou001@gmail.com

Security and abuse warning

AI work is easy to fake if the protocol only counts tokens or session time. AIPOU should evolve toward stronger signals:

  • provider-signed usage assertions
  • MCP client signatures
  • task hashes linked to real work
  • staking or slashing for reward operators
  • human or community validation for high-value claims

The token can launch early, but emissions should start conservative.

Clear limits:

  • AIPOU is not an AI-use detector.
  • AIPOU is not a scanner or policy gate.
  • AIPOU does not trustlessly prove "useful work" today.
  • The current validator is a protocol authority for client_signed receipts.
  • AIPOU work receipts do not replace narrower tool-call, boundary-event, payment, or policy receipts; they can reference each other.
  • AIPOU does not replace SLSA-style provenance, agent-security scanners, or observability traces.
  • AIPOU does not replace x402, AP2, stablecoins, or wallet automation.
  • AIPOU can be used as payment only where participants voluntarily accept it.
  • client_signed receipts currently rely on validator policy and trusted collector fingerprints.
  • Serious adoption should move owner and validator authority to multisig and publish explicit validator rules.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选