Pebbler Human Feedback

io.github.bridge-applicationsv0.1.0更新於 Oct 6, 2026

Buy human image preference comparisons on the Pebbler app with locally controlled USDC payments.

概覽

AI 產生的概覽

讓助理透過本機簽署的 USDC 付款,在 Pebbler 應用程式上購買真人影像 A/B 偏好測試。

功能
此連接器提供工具來讀取 Pebbler 目前的方案與價格目錄、準備影像比較並取得報價、購買已報價的測試,以及查看進度與彙總投票占比。它也能列出本機儲存的測試,方便重新啟動後取回結果。版本 1 僅支援影像 A/B 偏好測試,不支援問卷與純文字比較。
適用情境
當你需要了解人們偏好兩張影像中的哪一張,並願意為 Pebbler 應用程式參與者的回覆付費時使用。它不適合用來衡量產品轉換或因果關係,且不保證完成的回覆數量。
執行需求
支援 stdio 伺服器的本機 MCP 用戶端,以及 Node.js 22 或更新版本;此套件透過 npx 執行。付款需要專用錢包並存入 Base 上的原生 USDC,同時設定 PEBBLER_ALLOW_PAYMENTS、PEBBLER_WALLET_PRIVATE_KEY、PEBBLER_MAX_PURCHASE_USDC 與 PEBBLER_MAX_TOTAL_USDC。每個測試需要兩個可公開存取的 HTTPS 圖片網址與一個明確的問題。
安裝前請注意
啟用付款後,助理會用 PEBBLER_WALLET_PRIVATE_KEY 中的錢包金鑰簽署 USDC 交易;請將該金鑰保存在本機,不要放入提示詞。支出受 PEBBLER_MAX_PURCHASE_USDC 與 PEBBLER_MAX_TOTAL_USDC 限制,累計上限會計入已保留的簽章購買(包含未完成的嘗試),且不會自動重設。購買會產生實際支出,私有狀態資料夾應妥善備份。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Pebbler Human Feedback,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

Pebbler MCP

Let your agent collect human feedback on two images and explain the results. Pebbler runs image preference tests with participants on the Pebbler app.

Your agent retrieves current pricing, package details and availability before creating a test. The purchase uses a live quote and stays within the spending limits you configure. Pricing and package sizes are not fixed by this connector.

Version 1 supports image A/B preference tests. These measure which image people prefer, rather than product conversion or causal effects. Completed response counts are not guaranteed. Surveys and text-only comparisons are not supported.

Connect your agent

Use an MCP app that supports local servers and Node.js 22 or later. Add this configuration to your app:

json
{    "mcpServers": {        "pebbler": {            "command": "npx",            "args": ["-y", "@pebbler/[email protected]"]        }    }}

Pebbler's production settings are included. You can explore current packages and create drafts without enabling payments.

Enable purchases

Use a dedicated wallet funded with native USDC on Base. Configure these settings locally in your MCP app's environment or secret settings:

SettingWhat to provide
PEBBLER_ALLOW_PAYMENTSSet to true when you want the agent to make purchases
PEBBLER_WALLET_PRIVATE_KEYYour wallet's signing key, supplied privately
PEBBLER_MAX_PURCHASE_USDCYour chosen maximum spend per test, as a positive decimal USDC amount
PEBBLER_MAX_TOTAL_USDCYour chosen cumulative spending limit, as a positive decimal USDC amount

Both spending limits are required when payments are enabled. They are your budget, not the price of a test. If a quote exceeds either limit, the connector stops instead of raising your budget. Payments stay disabled until you enable them explicitly.

The wallet key remains local. Do not put it in a prompt or share it in a conversation. Prices and quotes are fetched by the agent; you do not need to configure them.

Ask for a test

For example:

Check the current package and price, then compare these two image URLs. Tell me the quote before buying and stay within my configured budget.

Provide two publicly accessible HTTPS image URLs and a clear question. Use images you own or have permission to use, and keep the URLs available while responses are collected.

Your agent can show the current offer, create a draft, purchase the test and check progress. You can read partial results while collection continues or return later to ask for the final counts and vote shares. Retrieving results is included in the purchase.

Available tools

ToolPurpose
get_catalogRetrieve current packages, prices, supported inputs and availability
create_studyPrepare an image comparison and obtain its quote
quote_studyRefresh a quote before payment has been signed
purchase_studyPurchase the quoted test within your wallet's spending limits
get_study_statusCheck progress and when to check again
get_study_resultsRetrieve aggregate A/B votes and shares
list_local_studiesFind your saved tests after returning or restarting

The agent learns each tool's inputs automatically when connected. It should read the catalog first, use the quote for the purchase, and follow the returned polling interval when checking progress.

Returning to your results

Keep the connector's private local state folder backed up. It retains access to your tests and their purchase history across restarts. You can choose a folder with PEBBLER_STATE_DIR; use the same folder when returning to existing tests.

Your total spending limit counts retained signed purchases, including unresolved attempts, and does not reset automatically. Increase it deliberately if you want to buy more tests. Keep the original state rather than deleting it to reset your budget.

If a purchase is interrupted or pending, ask the agent to retry that same purchase. The connector preserves its identifiers and payment authorization instead of signing another payment. Reading progress and results does not require another purchase.

Try an example

The included examples/run-study.mjs demonstrates discovery and creating an image comparison. It prints the live catalog and quote; purchasing requires the --purchase flag and your locally configured wallet and budgets.

License

MIT. Original example image assets are included under the same license.

來源:README.md,提交 c1ce9a1

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版本歷史

1
  1. v0.1.0最新Oct 6, 2026